Weather forecasting is one of the uses of data mining innovation to predict the condition of atmo... more Weather forecasting is one of the uses of data mining innovation to predict the condition of atmosphere for a future time and a given area as regards heat, cloudiness, dryness, wind, rain, and so on. At the same time Prediction of weather must be precise and furthermore the weather ought to be determined before will be useful for some applications like agriculture, air traffic, military etc. In recent years, analysis and modeling of big data has becoming the tedious task for any data analytics. This paper proposes modeling of complex structure of climate data using CDF function and analysis are done for prediction of extreme climate change in near by future.
Image Compression Based on Discrete Wavelet and Lifting Wavelet Transform Technique
Image compression is one of the important technologies in multimedia communications, that has bee... more Image compression is one of the important technologies in multimedia communications, that has been much attention in the past decades, where the two techniques discrete wavelet transform (DWT) and set-partitioning in hierarchical trees(SPIHT) have great influence on its performance. Due to the properties of fast computation, low memory requirement, adaptive Lifting DWT has been adopted as a new technique for still image compression. Furthermore, the traditional DWT and SPIHT have the drawback of long bits output and time consuming. In this paper we produce a new technique named adaptive Lifting DWT. An Adaptive Lifting DWT that locally adapts the filtering directions to image content based on directional lifting. This technique using the new algorithm that detects all the blocks in a given image to decide whether the block is homogenous or heterogeneous block. For homogeneous block, the simple Discrete Wavelet Transform (DWT) is used. And for the heterogeneous block Lifting Wavelet ...
Person identification using face is very exigent and knotty problem. Recognition of a person from... more Person identification using face is very exigent and knotty problem. Recognition of a person from an arbitrary perspective is crucial requirements for security measures and access control. Recognition of a particular face can be helpful for lots of problems like person - computer interaction, criminal detection, etc. The current system has more calculation due to upper dimensionality and not more effectual as well. Thus, instead of acquiring the face vectors with high dimensionality it is better to use face vectors with lower dimensionality. This implemented face recognition system is easy and comparatively simple to recognize the faces from videos taken from a distance and web cams. The improved PCA algorithm takes out facial features and classification is performed by minimum distance classification.
Orientation Calculation of human face using Symbolic Computing techniques and ANFIS
International Journal of Engineering and Future Technology, 2016
Face recognition techniques have come a long way since last six decade. There are several techniq... more Face recognition techniques have come a long way since last six decade. There are several techniques which mainly focus on improving the performance of face recognition. In the present work symbolic computing and ANFIS is use. ANFIS classifier is used as neuro-fuzzy approach and symbolic computing is used for calculating the degree of orientation of human face. By using ANFIS mapping can be done between the input and output of the developed system. The whole process is divided into two part: modeling and understanding. The modeling phase is carried out using template of face image with different pose. Each template is representing a dummy face and an angle of orientation as a symbol. Different geometrical feature are extracted from dummy face which is store in data base as template and angle as symbol. This process has been carried out using switching pattern of the face. The understanding phasetesting process is carried out using unknown-view of human face image and sufficient amou...
Image Segmentation Based on Particle Swarm Optimization Technique
Digital Image segmentation is one of the major tasks in digital image processing. It is the proce... more Digital Image segmentation is one of the major tasks in digital image processing. It is the process of subdividing a digital image into its constituent objects. This paper gives an overview of image segmentation techniques based on Particle Swarm Optimization (PSO) based clustering techniques. PSO is one of the latest and emerging digital image segmentation techniques inspired from the nature. It was developed by Dr Kenney and Dr Eberhart in 1995, and it has been widely used as an optimization tool in areas including tele-communications , computer graphics, biological or medical science, signal processing, data mining, robotics, neural networks etc. The paper study PSO based methods to search cluster center in the arbitrary data set automatically without any input knowledge about the number of naturally occurring regions in the data, and their applications to image segmentation.
Face Recognition Practices for Partial Occlusion: A Survey
Over the years, biometrics has gained unparalleled popularity in digital medium and has proven it... more Over the years, biometrics has gained unparalleled popularity in digital medium and has proven its usefulness for several applications concerned with the threats and crime or security purposes. Face recognition is a widely emerging biometric for automating the surveillance, as it has aid in strengthening the security from several types of terrorist or criminal threats. However, there are several face recognition techniques which are categorized based on its error rates in recognition but there are few that gives the marginal rate for sufficient and validated recognition rates for occlude images. This survey illustrates the precise overview of the major face recognition techniques which paves strong foothold for the partially occlude images.
Application of Group Mobility Model for Ad Hoc Network
The mobility model represents the movement pattern of mobile nodes, position, velocity and accele... more The mobility model represents the movement pattern of mobile nodes, position, velocity and acceleration with respect to time. Mobility management is a perilous issue in the wireless ad hoc network. Mobility model can be organized into two sorts: Entity Mobility Model (EMM) and Group Mobility Model (GMM). This paper presents a classification of GMM for wireless ad hoc network and their appropriate application with respect to GMM. Group motion happens repeatedly in an ad hoc network and further change in group motion parameters, the behavior of mobility model changes. Different GMM behaviors are observed and compared these models on different parameters. Further, it is reviewed to see that GMM can be easily adapted for existing applications.
Synthesis and Characterization of Sensor for Biological Real Time Applications Using Conducting Polymers, Nanocomposites and Signal Processing Technique
As far as the present state is concerned in detecting the behavioral pattern of humans (subject) ... more As far as the present state is concerned in detecting the behavioral pattern of humans (subject) using morphological image processing, a considerable portion of the study has been conducted utilizing frontal vision data of human faces. The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach. In this example, hybridization includes an artificial neural network (ANN) with a genetic algorithm (GA). We researched the geometrical properties extracted from side-vision human-face data. An additional study was conducted to determine the ideal number of geometrical characteristics to pick while clustering. The close vicinity of minimum distance measurements is done for these clusters, mapped for proper classification and decision process of behavioral pattern. To identify the data acquired, support vector machines and artificial neural networks are utilized. A method known as an adaptiveunidirectional associative memory (AUTAM) was used to map one side of a human face to the other side of the same subject. The behavioral pattern has been detected based on two-class problem classification, and the decision process has been done using a genetic algorithm with best-fit measurements. The developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET, Multi-PIE, Yale Face database, RTR, CASIA, etc. The complexity measures have also been calculated under worst-case and best-case situations.
Assessment Methods of Cognitive Ability of Human Brains for Inborn Intelligence Potential Using Pattern Recognitions
This research aims to examine the scientific study related to fingerprint patterns and brains lob... more This research aims to examine the scientific study related to fingerprint patterns and brains lobes. Generally, this method is used to find and develop the inborn potential and personality especially of children. Every person is having inborn potential and personality, which will help us to analyze strength and weakness. The present work is based only on the analysis and used as a reference for scientific research in the field of Galtian and statistical study conducted based on the fingerprint processing. Human brain is divided into two parts, left hemispheres and right hemispheres. Fingers of right hand represent the functions of left brain and fingers of left hand represent the functions of right brain. Human brain is divided into 10 lobes and each lobe is related with each finger. Each lobe represents different intelligences. A detailed analysis of the fingerprint would help the researchers to find the inborn talents. It will provide them the most appropriate learning habits from...
Tracking an Object Using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter
Algorithms for Intelligent Systems
Nowadays object tracking is a challenge in the fields of computer vision, many algorithms are put... more Nowadays object tracking is a challenge in the fields of computer vision, many algorithms are put forward to overcome the issues such as noisy, colored background, and occlusion of object and also illusion which is low and sudden changes in real-time videos, trackers cannot perform well in real-time environment. An efficient algorithm is needed for effective tracing of an object because of variation in position under various conditions. Here, the MS algorithm is used due to its efficiency and performance. MS tracking algorithm is used to obtain the position of an object by using a Kalman filter, therefore, the performance of tracking an object for different videos is evaluated but it does not improve the target localization. The advanced version is developed for tracking and representing the object in different video sequences are MS and CBWH MS using Kalman filter. Therefore, the proposed method is better than the traditional MS track, which results in the constant tracking of an object throughout the video. It does not get influenced by occlusions and less subjected to background cluttering.
Weather forecasting is one of the uses of data mining innovation to predict the condition of atmo... more Weather forecasting is one of the uses of data mining innovation to predict the condition of atmosphere for a future time and a given area as regards heat, cloudiness, dryness, wind, rain, and so on. At the same time Prediction of weather must be precise and furthermore the weather ought to be determined before will be useful for some applications like agriculture, air traffic, military etc. In recent years, analysis and modeling of big data has becoming the tedious task for any data analytics. This paper proposes modeling of complex structure of climate data using CDF function and analysis are done for prediction of extreme climate change in near by future.
Image Compression Based on Discrete Wavelet and Lifting Wavelet Transform Technique
Image compression is one of the important technologies in multimedia communications, that has bee... more Image compression is one of the important technologies in multimedia communications, that has been much attention in the past decades, where the two techniques discrete wavelet transform (DWT) and set-partitioning in hierarchical trees(SPIHT) have great influence on its performance. Due to the properties of fast computation, low memory requirement, adaptive Lifting DWT has been adopted as a new technique for still image compression. Furthermore, the traditional DWT and SPIHT have the drawback of long bits output and time consuming. In this paper we produce a new technique named adaptive Lifting DWT. An Adaptive Lifting DWT that locally adapts the filtering directions to image content based on directional lifting. This technique using the new algorithm that detects all the blocks in a given image to decide whether the block is homogenous or heterogeneous block. For homogeneous block, the simple Discrete Wavelet Transform (DWT) is used. And for the heterogeneous block Lifting Wavelet ...
Person identification using face is very exigent and knotty problem. Recognition of a person from... more Person identification using face is very exigent and knotty problem. Recognition of a person from an arbitrary perspective is crucial requirements for security measures and access control. Recognition of a particular face can be helpful for lots of problems like person - computer interaction, criminal detection, etc. The current system has more calculation due to upper dimensionality and not more effectual as well. Thus, instead of acquiring the face vectors with high dimensionality it is better to use face vectors with lower dimensionality. This implemented face recognition system is easy and comparatively simple to recognize the faces from videos taken from a distance and web cams. The improved PCA algorithm takes out facial features and classification is performed by minimum distance classification.
Orientation Calculation of human face using Symbolic Computing techniques and ANFIS
International Journal of Engineering and Future Technology, 2016
Face recognition techniques have come a long way since last six decade. There are several techniq... more Face recognition techniques have come a long way since last six decade. There are several techniques which mainly focus on improving the performance of face recognition. In the present work symbolic computing and ANFIS is use. ANFIS classifier is used as neuro-fuzzy approach and symbolic computing is used for calculating the degree of orientation of human face. By using ANFIS mapping can be done between the input and output of the developed system. The whole process is divided into two part: modeling and understanding. The modeling phase is carried out using template of face image with different pose. Each template is representing a dummy face and an angle of orientation as a symbol. Different geometrical feature are extracted from dummy face which is store in data base as template and angle as symbol. This process has been carried out using switching pattern of the face. The understanding phasetesting process is carried out using unknown-view of human face image and sufficient amou...
Image Segmentation Based on Particle Swarm Optimization Technique
Digital Image segmentation is one of the major tasks in digital image processing. It is the proce... more Digital Image segmentation is one of the major tasks in digital image processing. It is the process of subdividing a digital image into its constituent objects. This paper gives an overview of image segmentation techniques based on Particle Swarm Optimization (PSO) based clustering techniques. PSO is one of the latest and emerging digital image segmentation techniques inspired from the nature. It was developed by Dr Kenney and Dr Eberhart in 1995, and it has been widely used as an optimization tool in areas including tele-communications , computer graphics, biological or medical science, signal processing, data mining, robotics, neural networks etc. The paper study PSO based methods to search cluster center in the arbitrary data set automatically without any input knowledge about the number of naturally occurring regions in the data, and their applications to image segmentation.
Face Recognition Practices for Partial Occlusion: A Survey
Over the years, biometrics has gained unparalleled popularity in digital medium and has proven it... more Over the years, biometrics has gained unparalleled popularity in digital medium and has proven its usefulness for several applications concerned with the threats and crime or security purposes. Face recognition is a widely emerging biometric for automating the surveillance, as it has aid in strengthening the security from several types of terrorist or criminal threats. However, there are several face recognition techniques which are categorized based on its error rates in recognition but there are few that gives the marginal rate for sufficient and validated recognition rates for occlude images. This survey illustrates the precise overview of the major face recognition techniques which paves strong foothold for the partially occlude images.
Application of Group Mobility Model for Ad Hoc Network
The mobility model represents the movement pattern of mobile nodes, position, velocity and accele... more The mobility model represents the movement pattern of mobile nodes, position, velocity and acceleration with respect to time. Mobility management is a perilous issue in the wireless ad hoc network. Mobility model can be organized into two sorts: Entity Mobility Model (EMM) and Group Mobility Model (GMM). This paper presents a classification of GMM for wireless ad hoc network and their appropriate application with respect to GMM. Group motion happens repeatedly in an ad hoc network and further change in group motion parameters, the behavior of mobility model changes. Different GMM behaviors are observed and compared these models on different parameters. Further, it is reviewed to see that GMM can be easily adapted for existing applications.
Synthesis and Characterization of Sensor for Biological Real Time Applications Using Conducting Polymers, Nanocomposites and Signal Processing Technique
As far as the present state is concerned in detecting the behavioral pattern of humans (subject) ... more As far as the present state is concerned in detecting the behavioral pattern of humans (subject) using morphological image processing, a considerable portion of the study has been conducted utilizing frontal vision data of human faces. The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach. In this example, hybridization includes an artificial neural network (ANN) with a genetic algorithm (GA). We researched the geometrical properties extracted from side-vision human-face data. An additional study was conducted to determine the ideal number of geometrical characteristics to pick while clustering. The close vicinity of minimum distance measurements is done for these clusters, mapped for proper classification and decision process of behavioral pattern. To identify the data acquired, support vector machines and artificial neural networks are utilized. A method known as an adaptiveunidirectional associative memory (AUTAM) was used to map one side of a human face to the other side of the same subject. The behavioral pattern has been detected based on two-class problem classification, and the decision process has been done using a genetic algorithm with best-fit measurements. The developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET, Multi-PIE, Yale Face database, RTR, CASIA, etc. The complexity measures have also been calculated under worst-case and best-case situations.
Assessment Methods of Cognitive Ability of Human Brains for Inborn Intelligence Potential Using Pattern Recognitions
This research aims to examine the scientific study related to fingerprint patterns and brains lob... more This research aims to examine the scientific study related to fingerprint patterns and brains lobes. Generally, this method is used to find and develop the inborn potential and personality especially of children. Every person is having inborn potential and personality, which will help us to analyze strength and weakness. The present work is based only on the analysis and used as a reference for scientific research in the field of Galtian and statistical study conducted based on the fingerprint processing. Human brain is divided into two parts, left hemispheres and right hemispheres. Fingers of right hand represent the functions of left brain and fingers of left hand represent the functions of right brain. Human brain is divided into 10 lobes and each lobe is related with each finger. Each lobe represents different intelligences. A detailed analysis of the fingerprint would help the researchers to find the inborn talents. It will provide them the most appropriate learning habits from...
Tracking an Object Using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter
Algorithms for Intelligent Systems
Nowadays object tracking is a challenge in the fields of computer vision, many algorithms are put... more Nowadays object tracking is a challenge in the fields of computer vision, many algorithms are put forward to overcome the issues such as noisy, colored background, and occlusion of object and also illusion which is low and sudden changes in real-time videos, trackers cannot perform well in real-time environment. An efficient algorithm is needed for effective tracing of an object because of variation in position under various conditions. Here, the MS algorithm is used due to its efficiency and performance. MS tracking algorithm is used to obtain the position of an object by using a Kalman filter, therefore, the performance of tracking an object for different videos is evaluated but it does not improve the target localization. The advanced version is developed for tracking and representing the object in different video sequences are MS and CBWH MS using Kalman filter. Therefore, the proposed method is better than the traditional MS track, which results in the constant tracking of an object throughout the video. It does not get influenced by occlusions and less subjected to background cluttering.
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Papers by Rohit Raja