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Budi Setiyono

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University of California, Santa Barbara

Antioch University

University of British Columbia

Albert Akyeampong

Ohio Northern University

Md. Saifuddin Khalid

Technical University of Denmark (DTU)

Ignacio Aguaded

Huelva University

Universitas Pendidikan Indonesia (UPI) Bandung

University College London

Guilherme Moerbeck

UERJ - Universidade do Estado do Rio de Janeiro / Rio de Janeiro State University

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Papers by Budi Setiyono

The application of statistic image analysis for classification of breast cancer based on mammograms

Journal of Physics: Conference Series, 2019

Cancer is a disease characterized by the ability of abnormal cells to grow uncontrollably. In the... more Cancer is a disease characterized by the ability of abnormal cells to grow uncontrollably. In the medical field, detection of breast cancer is done using a mammogram. Examination of the mammogram image is still done manually by the doctor / radiologist, so it is necessary to use technology as supporting information. In this research, mammogram image classification based on gray-level co-occurrence (GLCM) matrix and gray-tone difference matrix (GTDM) has been done with backpropagation method. The stages of the mammogram image classification process include the process of image acquisition, pre-processing, feature extraction with GLCM and GTDM and classification using backpropagation. The preprocessing process carried out is gray-scalling, contrast enhancement, image segmentation with Otsu thresholding, edge detection process, and image thickening process with widening morphology method. The highest performance results for accuracy are 85% and precision is 85.7%. This result was obtai...

Road Defect Classification Using Gray Level Co-Occurrence Matrix (GLCM) and Radial Basis Function (RBF)

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), 2018

The road is an important infrastructure, so it is necessary to maintain the road periodically. Cu... more The road is an important infrastructure, so it is necessary to maintain the road periodically. Currently, the road defect assessment is still manual. Unfortunately, this method takes a long time and can cause ambiguity because of the subjectivity factor. Along with the development of science on image processing technology and machine learning, assessment of road defects can be done automatically by the machine. Road defect classification is the first step in automated road assessment. The image of road defect will be taken from the machine, taking on the features of each defect and classifying the image of its features. GLCM is a feature extract method that has been widely used for image processing. This study classifies some types of road defects, ie potholes, cracks and other defects using the Gray Level Co-occurrence Matrix (GLCM) as a feature extract, while Radial Basis Function (RBF) as an object classification. The proposed method can classify defects with an average of 93% accuracy, 93% precision and 100% recall.

Vehicle detection using histogram of oriented gradients and real adaboost

The vehicle detection system is an important technology because it has many applications in traff... more The vehicle detection system is an important technology because it has many applications in traffic fields such as traffic monitoring, counting the number of vehicles passing, calculating the speed of an oncoming vehicle, and so on. Histogram Of Oriented Gradients (HOG) is a feature descriptor used for object detection. HOG describes features based on some local histogram of gradient orientation weighted by gradient magnitude. Real AdaBoost is a learning algorithm which combined weak classifier into a strong classifier that represents the final output of the boosted classifier. This research aims to detect vehicles in the static image using a Histogram Of Oriented Gradients methods and Real Adaboost. The steps of vehicle detection are pra-processing, feature extraction process with HOG, and classification process with Real AdaBoost. The testing result shows that the system can detect vehicles with an accuracy level of 91.78 % from 292 testing images, from 257 images of the vehicle a...

Himpunan Kritis Pada Graf Caterpillar Untuk Penyusunan Skema Pembagian Rahasia

Pelabelan pada graf caterpillar Cn adalah memberi label simpul dan sisi pada graf caterpillar Cn.... more Pelabelan pada graf caterpillar Cn adalah memberi label simpul dan sisi pada graf caterpillar Cn. Graf tersebut mempunyai sifat ajaib, jika jumlah label sisi dan label simpul yang inseden dengan sisi mempunyai jumlah yang sama pada semua sisi. Karena graf caterpillar Cn dapat dilabeli sedemikian hingga jumlah setiap sisi dan simpul yang insiden adalah sama maka graf caterpillar Cn mempunyai sifat ajaib. Himpunan kritis adalah suatu himpunan yang beranggotakan elemen-elemen yang dapat menentukan elemen lain dari suatu himpunan secara tunggal. Oleh karena itu, jumlah anggota dari himpunan kritis harus seminimal mungkin. Karena graf caterpillar ajaib, maka dapat ditemukan himpunan kritis dari graf tersebut. Dengan mengetahui himpunan kritis dari suatu graph, khususnya graph cater¬pillar, maka dapat direkonstruksi pelabelan dari graph tersebut beserta label yang lain sehingga graph ajaib (tetap ajaib). Dari hasil analisa pembahasan ditemukan anggota dari himpunan kritis dari graph cater...

Multi Vehicle Speed Detection Using Euclidean Distance Based on Video Processing

International Journal of Computing, 2019

One component of smart city is smart transportation, known as Intelligent Transportation Systems ... more One component of smart city is smart transportation, known as Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on the video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the background and foreground is conducted using Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

Investigation of Superresolution using Phase based Image Matching with Function Fitting

Higher resolution image provide more detail information, so that it obtain more accurate image an... more Higher resolution image provide more detail information, so that it obtain more accurate image analysis. Many areas require high resolution image, such as medical, sensing satellite, image of the telescope and pattern recognition. This research make a process to obtain high resolution images, known as superresolution. This superresolution using a series of images in the same scene as the reference image. Two main stages in the super resolution are the registration and reconstruction. This research propose a composite between Phase-Based Image Matching (PBIM) registration, and reconstruction using structure - adaptive normalized convolution algorithm (SANC) and projection onto convext sets algorithm (POCs). PBIM was used to estimate translational registration stage. We used the function fitting around the peak point, to obtain sub pixel accurate shift. The results of this registration were used for reconstruction. Two registration method and reconstruction algorithms have been tested...

Superresolution Using Papoulis-Gerchberg Algorithm Based Phase Based Image Matching

SUPERRESOLUTION USING PAPOULIS-GERCHBERG ALGORITHM BASED PHASE BASED IMAGE MATCHING aBudi Setiyon... more SUPERRESOLUTION USING PAPOULIS-GERCHBERG ALGORITHM BASED PHASE BASED IMAGE MATCHING aBudi Setiyono, bMochamad Hariadi, cMauridhi Hery Purnomo aMathematical Dept., Faculty of Mathematics and Natural Science Sepuluh Nopember Institute of Technology, Surabaya 60111 b,cElectrical Engineering Dept., Faculty of Industrial Technology Sepuluh Nopember Institute of Technology, Surabaya 60111 E-Mail: [email protected] Abstrak Citra resolusi tinggi (High Resolution Image) akan memberikan informasi yang lebih detail, sehingga analisis terhadap citra tersebut menjadi lebih akurat. Banyak bidang memerlukan citra resolusi tinggi antara lain adalah medical, penginderaan satelite, citra dari teleskop serta pengenalan pola.Pada penelitian ini dilakukan proses untuk mendapatkan citra resolusi tinggi, yang dikenal dengan superresolution. Sebagai citra referensi, digunakan lebih dari satu citra, namun demikian, citra-citra tersebut berada pada scene yang sama. Dua tahap utama dalam superresolut...

Convolutional Neural Networks Untuk Pengenalan Wajah Secara Real-Time

Identifikasi identitas individu melalui pengenalan wajah secara otomatis merupakan suatu persoala... more Identifikasi identitas individu melalui pengenalan wajah secara otomatis merupakan suatu persoalan besar yang menarik dan banyak sekali berbagai macam pendekatan untuk menyelesaikan persoalan ini. Apalagi di dalam skenario kehidupan nyata yang tidak terkontrol, wajah akan terlihat dari berbagai sisi dan tidak selalu menghadap ke depan yang membuat permasalahan klasifikasi menjadi lebih sulit diselesaikan. Dalam Tugas Akhir ini digunakan salah satu metode deep neural networks yaitu Convolutional Neural Networks (CNN) sebagai pengenalan wajah secara real-time yang sudah terbukti sangat efisien dalam klasifikasi wajah. Metode diimplementasikan dengan bantuan library OpenCV untuk deteksi multi wajah dan perangkat Web Cam M-Tech 5MP. Dalam penyusunan arsitekur model Convolutional Neural Networks dilakukan konfigurasi inisialisasi parameter untuk mempercepat proses training jaringan. Hasil uji coba dengan munggunakan konstruksi model Convolutional Neural Networks sampai kedalaman 7 lapisa...

Watermelon Plant Classification Based on Shape and Texture Feature Leaf Using Support Vector Machine (SVM)

Nowadays, some efforts are used to increase results of agriculture production. One of those is ut... more Nowadays, some efforts are used to increase results of agriculture production. One of those is utilizing herbisides to exterminate the weeds. However, there are some of the weeds having resemblance with the plant, with the result that we need to classify the plant and the weeds before utilizing herbisides as an extermination weeds. In this paper, we use watermelon plant classification as case study. The recognition of the plant owned by the similarity of leaves of these plants are divided into three phases. At the first phase we perform preprocessing to convert the RGB image into a grayscale images. Further, the grayscale images are changed into segmentation of edge detection using Canny operator. In the second, we use feature extraction to retrieve important informations for the recognition of those leaves. The last phase we classify that leaves as watermelon plants or weeds using Support Vector Machine (SVM) algorithm. The results of early trials indicate that this method has an a...

Survey of Superresolution Using Phased Based Image Matching

Superresolution (SR) is a method of enhancing image resolution by combining information from mult... more Superresolution (SR) is a method of enhancing image resolution by combining information from multiple images. Two main processes in superresolution are r egist ation and image reconstruction. Both of these processes greatly affect the quality image of the s uperresolution. Accurate registration is required t o obtain high-resolution image quality. This research propos e a collaboration between Phase-Based Image Matchin g (PBIM) registration, and reconstruction using Struc ture Adaptive Normalized convolution algorithm (SANC) and Projection Onto Convex sets algorithm (P OCs). PBIM was used to estimate translational registration stage. We used the function fitting ar ound the peak point, to obtain sub pixel accurate s hift. The results of this registration were used for reconstr uction. Three registration method and two reconstru ction algorithms have been tested to obtain the most appr opriate collaboration by measuring the value of Pea k Signal to Noise Ratio (PSNR). The result show...

Kajian Algoritma GDBScan, Clarans dan Cure untuk Spatial Clustering

Limits: Journal of Mathematics and Its Applications, 2005

Spatial data mining merupakan salah satu bidang kajian dalam data mining dan menjadi salah satu b... more Spatial data mining merupakan salah satu bidang kajian dalam data mining dan menjadi salah satu bidang yang sangat cepat perkembangannya. Salah satu cabang dari spatial data mining adalah geographic data mining. Geographic data mining adalah penemuan pengetahuan baru dari sejumlah besar data geo-spatial (geo-reference). Beberapa metode dalam data mining telah dikembangkan para ahli. Salah satu metode yang paling banyak dikembangkan adalah clustering. Pada penelitian ini akan dilakukan kajian tentang tiga buah algoritma, yaitu algoritma density-based clustering, algoritma CLARANS clustering, serta algoritma CURE. Selanjutnyadilakuan implementasi dalam bentuk perangkat lunak. Studi kasus yang digunakan adalah clustering wilayah (peta) kota Surabaya berdasarkan parameter rasio jumlah penduduk miskin dan sangat miskin, kepadatan, dan tingkat kesejateraan tiap-tiap kelurahan kota Surabaya.

Registrasi Citra Pada Domain Frekuensi Menggunakan Metode Power Cepstrum

Limits: Journal of Mathematics and Its Applications, 2012

Bagaimana proses Registrasi Citra untuk mendapatkan nilai pergeseran diantara dua citra  Bagaima... more Bagaimana proses Registrasi Citra untuk mendapatkan nilai pergeseran diantara dua citra  Bagaimana implementasi metode Power Cepstrum dalam proses Registrasi Citra untuk menghasilkan keakuratan yang cukup baik  Bagaimana pengaruh metode Power Cepstrum terhadap pendeteksian nilai pergeseran jika citra yang digunakan diberi noise RUMUSAN MASALAH

Web-based decision support system to predict risk level of long term rice production

Journal of Physics: Conference Series, 2017

View the article online for updates and enhancements. Content from this work may be used under th... more

Speed Estimation On Moving Vehicle Based On Digital Image Processing

International Journal of Computing Science and Applied Mathematics, 2017

Along with the development of information and communication technology, the world urban people no... more Along with the development of information and communication technology, the world urban people now recognize a new term called Smart City. One of Smart City components is smart transportation, known as Intelligent Transportation System (ITS) in which there is transportation management on the highway. Installation of CCTV (Closed Circuit Television) on the streets are now widely performed. It can be used to monitor conditions and detect problems such as traffic jam and vehicle speed limit violation. This research focuses on vehicle speed estimation using image processing from video data and Euclidean distance method with many different camera angles. The first step, video data is extracted into frames and applied preprocessing to extracted frames to minimize shadow effect. Then, using Gaussian Mixture Model (GMM) to extract foreground image. In the next step, the obtained foreground is filtered using median filter, shadow removing, and morphology operation. The detected vehicle object will be tracked to determine the location in each frame to estimate the speed based on its distance between frames. From the obtained results, this system is capable on estimating the speed of moving vehicle with the lowest accuracy is 87.01% and the highest accuracy is 99.38%. Index Terms-Digital image processing, moving vehicle, speed estimation.

Vehicle speed detection based on gaussian mixture model using sequential of images

Journal of Physics: Conference Series, 2017

Intelligent Transportation System is one of the important components in the development of smart ... more Intelligent Transportation System is one of the important components in the development of smart cities. Detection of vehicle speed on the highway is supporting the management of traffic engineering. The purpose of this study is to detect the speed of the moving vehicles using digital image processing. Our approach is as follows: The inputs are a sequence of frames, frame rate (fps) and ROI. The steps are following: First we separate foreground and background using Gaussian Mixture Model (GMM) in each frames. Then in each frame, we calculate the location of object and its centroid. Next we determine the speed by computing the movement of centroid in sequence of frames. In the calculation of speed, we only consider frames when the centroid is inside the predefined region of interest (ROI). Finally we transform the pixel displacement into a time unit of km/hour. Validation of the system is done by comparing the speed calculated manually and obtained by the system. The results of software testing can detect the speed of vehicles with the highest accuracy is 97.52% and the lowest accuracy is 77.41%. And the detection results of testing by using real video footage on the road is included with real speed of the vehicle.

Bullet Image Classification using Support Vector Machine (SVM)

Journal of Physics: Conference Series, 2016

All Quality control of the bullet is usually done manually. Manual inspection process has some di... more All Quality control of the bullet is usually done manually. Manual inspection process has some disadvantages for instance human error factor and the time inspection are relatively longer. In this study, defect detection and classification of bullets by using Support Vector Machine (SVM)has been done. The stages of classification of scheme bullets in this study include pre-processing, feature extraction with Principal Component Analysis (PCA) and classification of bullets by using SVM normalized. Performance of the proposed classification of scheme was tested using 80 images of bullets in which 40 images free of defects and 40 images with defect. The results show that the scheme can classify images of bullets with a 90% accuracy rate with test data in the form of 10 images free-defect and 10 image defects.

Critical set of caterpillar graph for secret sharing scheme

ABSTRACT We investigate the critical set of edge-magic labelling on caterpillar graphs and applic... more ABSTRACT We investigate the critical set of edge-magic labelling on caterpillar graphs and application on secret sharing scheme. We construct a distribution scheme based on supervisional secret sharing scheme. The schemes use the notion of critical sets tu distribute tile share and reconstruct the key.

Rain Removal Using Guided Image Filtering For Surveillance Videos

2019 International Conference on Information and Communications Technology (ICOIACT), 2019

The Intelligent Transportation System includes management of vehicle transportation. Video from s... more The Intelligent Transportation System includes management of vehicle transportation. Video from surveillance cameras can be used for monitoring the number of vehicles and speed using digital image processing. However, in rainy conditions the monitoring process will be less accurate. So, removing rain noise is a solution that can be used. The method that will be presented in our paper is the method of rain removal using the low frequency and high frequency parts of the video frame. For each frame, low frequency as an image non-rain. Then, high frequency part as input from the guided filter, so we get a non-rain component from the high frequency part, and add a low frequency part is the restored frames. we also restore the nature of the background edge. The experiment will generate rain noise from videos without rain. The type of rain is heavy rain, moderate rain and light rain. The result of rain removal will be calculated image quality with a peak signal to noise ratio (PSNR). In addition, proper selection of radius and regulation parameters will reduce the rain effect more optimally. To be more detailed, we also test the performance of method on videos with static and moving foreground. The application of guided filter algorithm for three times, contained in preprocessing, filtering and recovering, can improve image quality.

THE RAIN NOISE REDUCTION USING GUIDED FILTER TO IMPROVE PERFORMANCE OF VEHICLE COUNTING

International Journal of Innovative Computing, Information and Control, 2020

The calculation of the number of vehicles on the road using digital image processing technology i... more The calculation of the number of vehicles on the road using digital image processing technology is expected to be faster and more accurate. Nevertheless, there are obstacles such as noise that arises due to rain because it can reduce the accuracy of the calculation of the number of vehicles. Therefore, we need a rain noise reduction process to improve the accuracy of vehicle calculations. The guided filter has the advantage of reducing noise, including snow noise and fog noise. The experiment was conducted by comparing the accuracy of the calculation of the number of vehicles in noise conditions after and before they were reduced with heavy rain, moderate rain, and drizzle data. The results show that accuracy is increasing for heavy and moderate rainfall data, while the drizzle data has decreased. Therefore, the guided filter is suitable for heavy and moderate rain conditions.

MULTI VEHICLE SPEED DETECTION USING EUCLIDEAN DISTANCE BASED ON VIDEO PROCESSING

International Journal of Computing, 2019

One component of the smart city is smart transportation, known as Intelligent Transportation Syst... more One component of the smart city is smart transportation, known as
Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the
background and foreground is conducted using the Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain a speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

The application of statistic image analysis for classification of breast cancer based on mammograms

Journal of Physics: Conference Series, 2019

Cancer is a disease characterized by the ability of abnormal cells to grow uncontrollably. In the... more Cancer is a disease characterized by the ability of abnormal cells to grow uncontrollably. In the medical field, detection of breast cancer is done using a mammogram. Examination of the mammogram image is still done manually by the doctor / radiologist, so it is necessary to use technology as supporting information. In this research, mammogram image classification based on gray-level co-occurrence (GLCM) matrix and gray-tone difference matrix (GTDM) has been done with backpropagation method. The stages of the mammogram image classification process include the process of image acquisition, pre-processing, feature extraction with GLCM and GTDM and classification using backpropagation. The preprocessing process carried out is gray-scalling, contrast enhancement, image segmentation with Otsu thresholding, edge detection process, and image thickening process with widening morphology method. The highest performance results for accuracy are 85% and precision is 85.7%. This result was obtai...

Road Defect Classification Using Gray Level Co-Occurrence Matrix (GLCM) and Radial Basis Function (RBF)

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), 2018

The road is an important infrastructure, so it is necessary to maintain the road periodically. Cu... more The road is an important infrastructure, so it is necessary to maintain the road periodically. Currently, the road defect assessment is still manual. Unfortunately, this method takes a long time and can cause ambiguity because of the subjectivity factor. Along with the development of science on image processing technology and machine learning, assessment of road defects can be done automatically by the machine. Road defect classification is the first step in automated road assessment. The image of road defect will be taken from the machine, taking on the features of each defect and classifying the image of its features. GLCM is a feature extract method that has been widely used for image processing. This study classifies some types of road defects, ie potholes, cracks and other defects using the Gray Level Co-occurrence Matrix (GLCM) as a feature extract, while Radial Basis Function (RBF) as an object classification. The proposed method can classify defects with an average of 93% accuracy, 93% precision and 100% recall.

Vehicle detection using histogram of oriented gradients and real adaboost

The vehicle detection system is an important technology because it has many applications in traff... more The vehicle detection system is an important technology because it has many applications in traffic fields such as traffic monitoring, counting the number of vehicles passing, calculating the speed of an oncoming vehicle, and so on. Histogram Of Oriented Gradients (HOG) is a feature descriptor used for object detection. HOG describes features based on some local histogram of gradient orientation weighted by gradient magnitude. Real AdaBoost is a learning algorithm which combined weak classifier into a strong classifier that represents the final output of the boosted classifier. This research aims to detect vehicles in the static image using a Histogram Of Oriented Gradients methods and Real Adaboost. The steps of vehicle detection are pra-processing, feature extraction process with HOG, and classification process with Real AdaBoost. The testing result shows that the system can detect vehicles with an accuracy level of 91.78 % from 292 testing images, from 257 images of the vehicle a...

Himpunan Kritis Pada Graf Caterpillar Untuk Penyusunan Skema Pembagian Rahasia

Pelabelan pada graf caterpillar Cn adalah memberi label simpul dan sisi pada graf caterpillar Cn.... more Pelabelan pada graf caterpillar Cn adalah memberi label simpul dan sisi pada graf caterpillar Cn. Graf tersebut mempunyai sifat ajaib, jika jumlah label sisi dan label simpul yang inseden dengan sisi mempunyai jumlah yang sama pada semua sisi. Karena graf caterpillar Cn dapat dilabeli sedemikian hingga jumlah setiap sisi dan simpul yang insiden adalah sama maka graf caterpillar Cn mempunyai sifat ajaib. Himpunan kritis adalah suatu himpunan yang beranggotakan elemen-elemen yang dapat menentukan elemen lain dari suatu himpunan secara tunggal. Oleh karena itu, jumlah anggota dari himpunan kritis harus seminimal mungkin. Karena graf caterpillar ajaib, maka dapat ditemukan himpunan kritis dari graf tersebut. Dengan mengetahui himpunan kritis dari suatu graph, khususnya graph cater¬pillar, maka dapat direkonstruksi pelabelan dari graph tersebut beserta label yang lain sehingga graph ajaib (tetap ajaib). Dari hasil analisa pembahasan ditemukan anggota dari himpunan kritis dari graph cater...

Multi Vehicle Speed Detection Using Euclidean Distance Based on Video Processing

International Journal of Computing, 2019

One component of smart city is smart transportation, known as Intelligent Transportation Systems ... more One component of smart city is smart transportation, known as Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on the video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the background and foreground is conducted using Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

Investigation of Superresolution using Phase based Image Matching with Function Fitting

Higher resolution image provide more detail information, so that it obtain more accurate image an... more Higher resolution image provide more detail information, so that it obtain more accurate image analysis. Many areas require high resolution image, such as medical, sensing satellite, image of the telescope and pattern recognition. This research make a process to obtain high resolution images, known as superresolution. This superresolution using a series of images in the same scene as the reference image. Two main stages in the super resolution are the registration and reconstruction. This research propose a composite between Phase-Based Image Matching (PBIM) registration, and reconstruction using structure - adaptive normalized convolution algorithm (SANC) and projection onto convext sets algorithm (POCs). PBIM was used to estimate translational registration stage. We used the function fitting around the peak point, to obtain sub pixel accurate shift. The results of this registration were used for reconstruction. Two registration method and reconstruction algorithms have been tested...

Superresolution Using Papoulis-Gerchberg Algorithm Based Phase Based Image Matching

SUPERRESOLUTION USING PAPOULIS-GERCHBERG ALGORITHM BASED PHASE BASED IMAGE MATCHING aBudi Setiyon... more SUPERRESOLUTION USING PAPOULIS-GERCHBERG ALGORITHM BASED PHASE BASED IMAGE MATCHING aBudi Setiyono, bMochamad Hariadi, cMauridhi Hery Purnomo aMathematical Dept., Faculty of Mathematics and Natural Science Sepuluh Nopember Institute of Technology, Surabaya 60111 b,cElectrical Engineering Dept., Faculty of Industrial Technology Sepuluh Nopember Institute of Technology, Surabaya 60111 E-Mail: [email protected] Abstrak Citra resolusi tinggi (High Resolution Image) akan memberikan informasi yang lebih detail, sehingga analisis terhadap citra tersebut menjadi lebih akurat. Banyak bidang memerlukan citra resolusi tinggi antara lain adalah medical, penginderaan satelite, citra dari teleskop serta pengenalan pola.Pada penelitian ini dilakukan proses untuk mendapatkan citra resolusi tinggi, yang dikenal dengan superresolution. Sebagai citra referensi, digunakan lebih dari satu citra, namun demikian, citra-citra tersebut berada pada scene yang sama. Dua tahap utama dalam superresolut...

Convolutional Neural Networks Untuk Pengenalan Wajah Secara Real-Time

Identifikasi identitas individu melalui pengenalan wajah secara otomatis merupakan suatu persoala... more Identifikasi identitas individu melalui pengenalan wajah secara otomatis merupakan suatu persoalan besar yang menarik dan banyak sekali berbagai macam pendekatan untuk menyelesaikan persoalan ini. Apalagi di dalam skenario kehidupan nyata yang tidak terkontrol, wajah akan terlihat dari berbagai sisi dan tidak selalu menghadap ke depan yang membuat permasalahan klasifikasi menjadi lebih sulit diselesaikan. Dalam Tugas Akhir ini digunakan salah satu metode deep neural networks yaitu Convolutional Neural Networks (CNN) sebagai pengenalan wajah secara real-time yang sudah terbukti sangat efisien dalam klasifikasi wajah. Metode diimplementasikan dengan bantuan library OpenCV untuk deteksi multi wajah dan perangkat Web Cam M-Tech 5MP. Dalam penyusunan arsitekur model Convolutional Neural Networks dilakukan konfigurasi inisialisasi parameter untuk mempercepat proses training jaringan. Hasil uji coba dengan munggunakan konstruksi model Convolutional Neural Networks sampai kedalaman 7 lapisa...

Watermelon Plant Classification Based on Shape and Texture Feature Leaf Using Support Vector Machine (SVM)

Nowadays, some efforts are used to increase results of agriculture production. One of those is ut... more Nowadays, some efforts are used to increase results of agriculture production. One of those is utilizing herbisides to exterminate the weeds. However, there are some of the weeds having resemblance with the plant, with the result that we need to classify the plant and the weeds before utilizing herbisides as an extermination weeds. In this paper, we use watermelon plant classification as case study. The recognition of the plant owned by the similarity of leaves of these plants are divided into three phases. At the first phase we perform preprocessing to convert the RGB image into a grayscale images. Further, the grayscale images are changed into segmentation of edge detection using Canny operator. In the second, we use feature extraction to retrieve important informations for the recognition of those leaves. The last phase we classify that leaves as watermelon plants or weeds using Support Vector Machine (SVM) algorithm. The results of early trials indicate that this method has an a...

Survey of Superresolution Using Phased Based Image Matching

Superresolution (SR) is a method of enhancing image resolution by combining information from mult... more Superresolution (SR) is a method of enhancing image resolution by combining information from multiple images. Two main processes in superresolution are r egist ation and image reconstruction. Both of these processes greatly affect the quality image of the s uperresolution. Accurate registration is required t o obtain high-resolution image quality. This research propos e a collaboration between Phase-Based Image Matchin g (PBIM) registration, and reconstruction using Struc ture Adaptive Normalized convolution algorithm (SANC) and Projection Onto Convex sets algorithm (P OCs). PBIM was used to estimate translational registration stage. We used the function fitting ar ound the peak point, to obtain sub pixel accurate s hift. The results of this registration were used for reconstr uction. Three registration method and two reconstru ction algorithms have been tested to obtain the most appr opriate collaboration by measuring the value of Pea k Signal to Noise Ratio (PSNR). The result show...

Kajian Algoritma GDBScan, Clarans dan Cure untuk Spatial Clustering

Limits: Journal of Mathematics and Its Applications, 2005

Spatial data mining merupakan salah satu bidang kajian dalam data mining dan menjadi salah satu b... more Spatial data mining merupakan salah satu bidang kajian dalam data mining dan menjadi salah satu bidang yang sangat cepat perkembangannya. Salah satu cabang dari spatial data mining adalah geographic data mining. Geographic data mining adalah penemuan pengetahuan baru dari sejumlah besar data geo-spatial (geo-reference). Beberapa metode dalam data mining telah dikembangkan para ahli. Salah satu metode yang paling banyak dikembangkan adalah clustering. Pada penelitian ini akan dilakukan kajian tentang tiga buah algoritma, yaitu algoritma density-based clustering, algoritma CLARANS clustering, serta algoritma CURE. Selanjutnyadilakuan implementasi dalam bentuk perangkat lunak. Studi kasus yang digunakan adalah clustering wilayah (peta) kota Surabaya berdasarkan parameter rasio jumlah penduduk miskin dan sangat miskin, kepadatan, dan tingkat kesejateraan tiap-tiap kelurahan kota Surabaya.

Registrasi Citra Pada Domain Frekuensi Menggunakan Metode Power Cepstrum

Limits: Journal of Mathematics and Its Applications, 2012

Bagaimana proses Registrasi Citra untuk mendapatkan nilai pergeseran diantara dua citra  Bagaima... more Bagaimana proses Registrasi Citra untuk mendapatkan nilai pergeseran diantara dua citra  Bagaimana implementasi metode Power Cepstrum dalam proses Registrasi Citra untuk menghasilkan keakuratan yang cukup baik  Bagaimana pengaruh metode Power Cepstrum terhadap pendeteksian nilai pergeseran jika citra yang digunakan diberi noise RUMUSAN MASALAH

Web-based decision support system to predict risk level of long term rice production

Journal of Physics: Conference Series, 2017

View the article online for updates and enhancements. Content from this work may be used under th... more

Speed Estimation On Moving Vehicle Based On Digital Image Processing

International Journal of Computing Science and Applied Mathematics, 2017

Along with the development of information and communication technology, the world urban people no... more Along with the development of information and communication technology, the world urban people now recognize a new term called Smart City. One of Smart City components is smart transportation, known as Intelligent Transportation System (ITS) in which there is transportation management on the highway. Installation of CCTV (Closed Circuit Television) on the streets are now widely performed. It can be used to monitor conditions and detect problems such as traffic jam and vehicle speed limit violation. This research focuses on vehicle speed estimation using image processing from video data and Euclidean distance method with many different camera angles. The first step, video data is extracted into frames and applied preprocessing to extracted frames to minimize shadow effect. Then, using Gaussian Mixture Model (GMM) to extract foreground image. In the next step, the obtained foreground is filtered using median filter, shadow removing, and morphology operation. The detected vehicle object will be tracked to determine the location in each frame to estimate the speed based on its distance between frames. From the obtained results, this system is capable on estimating the speed of moving vehicle with the lowest accuracy is 87.01% and the highest accuracy is 99.38%. Index Terms-Digital image processing, moving vehicle, speed estimation.

Vehicle speed detection based on gaussian mixture model using sequential of images

Journal of Physics: Conference Series, 2017

Intelligent Transportation System is one of the important components in the development of smart ... more Intelligent Transportation System is one of the important components in the development of smart cities. Detection of vehicle speed on the highway is supporting the management of traffic engineering. The purpose of this study is to detect the speed of the moving vehicles using digital image processing. Our approach is as follows: The inputs are a sequence of frames, frame rate (fps) and ROI. The steps are following: First we separate foreground and background using Gaussian Mixture Model (GMM) in each frames. Then in each frame, we calculate the location of object and its centroid. Next we determine the speed by computing the movement of centroid in sequence of frames. In the calculation of speed, we only consider frames when the centroid is inside the predefined region of interest (ROI). Finally we transform the pixel displacement into a time unit of km/hour. Validation of the system is done by comparing the speed calculated manually and obtained by the system. The results of software testing can detect the speed of vehicles with the highest accuracy is 97.52% and the lowest accuracy is 77.41%. And the detection results of testing by using real video footage on the road is included with real speed of the vehicle.

Bullet Image Classification using Support Vector Machine (SVM)

Journal of Physics: Conference Series, 2016

All Quality control of the bullet is usually done manually. Manual inspection process has some di... more All Quality control of the bullet is usually done manually. Manual inspection process has some disadvantages for instance human error factor and the time inspection are relatively longer. In this study, defect detection and classification of bullets by using Support Vector Machine (SVM)has been done. The stages of classification of scheme bullets in this study include pre-processing, feature extraction with Principal Component Analysis (PCA) and classification of bullets by using SVM normalized. Performance of the proposed classification of scheme was tested using 80 images of bullets in which 40 images free of defects and 40 images with defect. The results show that the scheme can classify images of bullets with a 90% accuracy rate with test data in the form of 10 images free-defect and 10 image defects.

Critical set of caterpillar graph for secret sharing scheme

ABSTRACT We investigate the critical set of edge-magic labelling on caterpillar graphs and applic... more ABSTRACT We investigate the critical set of edge-magic labelling on caterpillar graphs and application on secret sharing scheme. We construct a distribution scheme based on supervisional secret sharing scheme. The schemes use the notion of critical sets tu distribute tile share and reconstruct the key.

Rain Removal Using Guided Image Filtering For Surveillance Videos

2019 International Conference on Information and Communications Technology (ICOIACT), 2019

The Intelligent Transportation System includes management of vehicle transportation. Video from s... more The Intelligent Transportation System includes management of vehicle transportation. Video from surveillance cameras can be used for monitoring the number of vehicles and speed using digital image processing. However, in rainy conditions the monitoring process will be less accurate. So, removing rain noise is a solution that can be used. The method that will be presented in our paper is the method of rain removal using the low frequency and high frequency parts of the video frame. For each frame, low frequency as an image non-rain. Then, high frequency part as input from the guided filter, so we get a non-rain component from the high frequency part, and add a low frequency part is the restored frames. we also restore the nature of the background edge. The experiment will generate rain noise from videos without rain. The type of rain is heavy rain, moderate rain and light rain. The result of rain removal will be calculated image quality with a peak signal to noise ratio (PSNR). In addition, proper selection of radius and regulation parameters will reduce the rain effect more optimally. To be more detailed, we also test the performance of method on videos with static and moving foreground. The application of guided filter algorithm for three times, contained in preprocessing, filtering and recovering, can improve image quality.

THE RAIN NOISE REDUCTION USING GUIDED FILTER TO IMPROVE PERFORMANCE OF VEHICLE COUNTING

International Journal of Innovative Computing, Information and Control, 2020

The calculation of the number of vehicles on the road using digital image processing technology i... more The calculation of the number of vehicles on the road using digital image processing technology is expected to be faster and more accurate. Nevertheless, there are obstacles such as noise that arises due to rain because it can reduce the accuracy of the calculation of the number of vehicles. Therefore, we need a rain noise reduction process to improve the accuracy of vehicle calculations. The guided filter has the advantage of reducing noise, including snow noise and fog noise. The experiment was conducted by comparing the accuracy of the calculation of the number of vehicles in noise conditions after and before they were reduced with heavy rain, moderate rain, and drizzle data. The results show that accuracy is increasing for heavy and moderate rainfall data, while the drizzle data has decreased. Therefore, the guided filter is suitable for heavy and moderate rain conditions.

MULTI VEHICLE SPEED DETECTION USING EUCLIDEAN DISTANCE BASED ON VIDEO PROCESSING

International Journal of Computing, 2019

One component of the smart city is smart transportation, known as Intelligent Transportation Syst... more One component of the smart city is smart transportation, known as
Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the
background and foreground is conducted using the Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain a speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

Application of Semantic Web Technology in System Repository Javanese Language Vocabularies

by Journal of Computer Science IJCSIS, Budi Setiyono, and Tito Rizky

Semantic Web is one of the web technologies that has capability to understand the meaning of the... more Semantic Web is one of the web technologies that has capability to understand the meaning of the information in a web and can understand more complex language as conversation. Indonesia has various local languages which one Javanese language requires the storage media for a wide range of vocabulary and its meaning as well as getting the relationship in every vocabulary. This final project is done through the stages of system design that includes design ontologies, the ontology of the configuration and design of the repository, and then the repository web application design of the Javanese language. The system design is then implemented to include creating ontologies using protégé, then do the configuration using openRDF-Sesame and thus achieve the creation of applications repository Javanese language in PHP code. Finally this system produced an ontology of the repository Javanese language which has been used as the basic of knowledge in the implementation of the web application repository Javanese language. The survey results of testing the use of applications with sample data as many as 30 users obtained that about 82% of the stated application is already good in providing ease of use to obtain information about the Javanese language and about 72% of users stated data concerning the vocabulary of the Javanese language contained in the application is sufficient help to learn it.