Papers by Yiannis Boutalis
Journal of Data Analysis and Information Processing
The identification of objects in binary images is a fundamental task in image analysis and patter... more The identification of objects in binary images is a fundamental task in image analysis and pattern recognition tasks. The Euler number of a binary image is an important topological measure which is used as a feature in image analysis. In this paper, a very fast algorithm for the detection and localization of the objects and the computation of the Euler number of a binary image is proposed. The proposed algorithm operates in one scan of the image and is based on the Image Block Representation (IBR) scheme. The proposed algorithm is more efficient than conventional pixel based algorithms in terms of execution speed and representation of the extracted information.
Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics, 2005
Fuzzy Cognitive Maps (FCMs) have found many applications in social -financial -political problems... more Fuzzy Cognitive Maps (FCMs) have found many applications in social -financial -political problems. In this paper we propose a method of FCM operation, which can be used to represent and control any real system, including traditional electro-mechanical systems. In the proposed approach the FCM reaches its equilibrium point using direct feedback from the node values of the real system and the limitations imposed by the control objectives for the node values of the system. The experts' knowledge, which is represented in the weights of the nodes' interconnections, undergoes a continuous on-line adaptation based on feedback from the real system. An algorithm for weight updating is proposed, which is based on system feedback and which includes specially designed matrices that lead the FCM and consequently the real system associated with it in a balanced equilibrium state. The proposed methodology is tested by simulating the operation of a hydro-electric plant.
Hybrid Jordan Elman nets in portfolio selection
2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA), 2015
We examine the efficiency of various Jordan Elman models either in neural or in hybrid neuro-gene... more We examine the efficiency of various Jordan Elman models either in neural or in hybrid neuro-genetic networks form to conclude on an optimal model that will be valuable in portfolio selection. The Jordan and Elman neural networks on a hybrid form of genetic algorithms optimization, in a specific topology, outperformed all the other Jordan Elman models and the financial evaluation of corporations had excellent results.
IFAC Proceedings Volumes, 2009
Recently, several approaches for the control of fuzzy discrete event systems (FDES) have been pro... more Recently, several approaches for the control of fuzzy discrete event systems (FDES) have been proposed. First results towards the use of FDES in mobile robot navigation have also been presented, which however mainly build on sensory information processing. In this paper, we develop a methodology to compute control actions for the navigation of a mobile robot based on distributed FDES. The FDES description permits to take into account possible uncertainties in sensory information and enables a prediction of the future behavior of the robot depending on potential control actions. This prediction can then be used to select the most appropriate control action in each time instant. Our approach is tested by simulations of a mobile robot that encounters unknown obstacles on a pre-defined path.
Journal of Real-Time Image Processing, 2009
Moments constitute a well-known tool in the field of image analysis and pattern recognition, but ... more Moments constitute a well-known tool in the field of image analysis and pattern recognition, but they suffer from the drawback of high computational cost. Efforts for the reduction of the required computational complexity have been reported, mainly focused on binary images, but recently some approaches for gray images have been also presented. In this study, we propose a simple but effective approach for the computation of gray image moments. The gray image is decomposed in a set of binary images. Some of these binary images are substituted by an ideal image, which is called ''half-intensity'' image. The remaining binary images are represented using the image block representation concept and their moments are computed fast using block techniques. The proposed method computes approximated moment values with an error of 2-3% from the exact values and operates in real time (i.e., video rate). The procedure is parameterized by the number m of ''half-intensity'' images used, which controls the approximation error and the speed gain of the method. The computational complexity is O(kL 2), where k is the number of blocks and L is the moment order.
Multi-objective decision making using fuzzy discrete event systems: A mobile robot example
18th Mediterranean Conference on Control and Automation, MED'10, 2010
Computer Science and Information Systems, 2011
Kernel vectors represent an elegant representation for the retrieval of pattern associations, whe... more Kernel vectors represent an elegant representation for the retrieval of pattern associations, where the input patterns are corrupted by both erosive and dilative noise. However, their action completely fails when a particular kind of erosive noise, even of very low percentage, corrupts the input pattern. In this paper, a theoretical justification of this fact is given and a new method is proposed for the construction of kernel vectors for binary patterns associations. The new kernels are not binary but ?gray?, because they contain elements with values in the interval [0, 1]. It is shown, both theoretically and experimentally that the new kernel vectors carry the good properties of conventional kernel vectors and, at the same time, they can be easily computed. Moreover, they do not suffer from the particular noise deficiency of the conventional kernel vectors. The recalling result is in general a gray pattern, which in the sequel undergoes a simple thresholding action and passes thro...
Proceedings First International IEEE Symposium Intelligent Systems
The paper deals with the intelligent pattern recognition control systems. The concept of strateg... more The paper deals with the intelligent pattern recognition control systems. The concept of strategic situation is introduced, in the context of hierarchical structured control systems. It allows the investigation of the properties of the pattern recognition based control systems. The interaction between the system that recognizes strategies and the environment is described, along with the examples of control systems that allow such an approach. A case study, carried out on a simple process, is presented, to illustrate the method in a plausible context.
Stable indirect adaptive switching control for fuzzy dynamical systems based on T–S multiple models
International Journal of Systems Science, 2013
Intelligent Decision Technologies, 2007
In this paper, we present a general computational and operational framework for the Fuzzy Cogniti... more In this paper, we present a general computational and operational framework for the Fuzzy Cognitive Network (FCN), which is a direct extension of Fuzzy Cognitive Maps (FCM). The proposed framework assumes a network operation, which continuously receives feedback from the system it describes and outputs control or decision values. This way, its knowledge is continuously updated making it suitable for adaptive decision making or even for adaptive control tasks. The interconnection weights are continuously updated based on a modified delta rule that provides smooth and fast convergence and prevents the concept and weight values from being saturated. To avoid intensive interference of the updating mechanism with the real system, a technique is proposed that stores the previously encountered operational situations in a fuzzy rule database. The explanation of the proposed methodology is interweaved with the FCN description of a simulated hydroelectric plant, which is also used for the experimental results. The proposed framework can be used both for on-line control and decision making tasks.
International Journal of Artificial Life Research, 2011
In this paper, a new methodology is proposed for deterministic learning with neural networks. Usi... more In this paper, a new methodology is proposed for deterministic learning with neural networks. Using an observer that employs the integral of the sign of the error term, asymptotic estimation of the respective nonlinear vector field is achieved. Patchy Neural Networks (PNNs) are introduced to identify the unknown nonlinearity from the observer’s output and the state measurements. The proposed scheme achieves learning with a single pass from the respective patches and does not need standard persistency of excitation conditions. Furthermore, the PNN weights are updated algebraically, reducing the computational load of learning significantly. Simulation results for a Duffing oscillator and a fuzzy cognitive network illustrate the effectiveness of the proposed approach.
New Maximum Power Point Tracker for PV Arrays Using Fuzzy Controller in Close Cooperation With Fuzzy Cognitive Networks
IEEE Transactions on Energy Conversion, 2006
Electric Power Systems Research, 2007
Maximum power point trackers (MPPTs) play an important role in photovoltaic (PV) power systems be... more Maximum power point trackers (MPPTs) play an important role in photovoltaic (PV) power systems because they maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency. This paper presents a novel MPPT method based on fuzzy cognitive networks (FCN). The new method gives a good maximum power operation of any PV array under different conditions such as changing insolation and temperature. The numerical results show the effectiveness of the proposed algorithm.
In this paper, a new low level feature suitable for Hand Drawn Color Sketches retrieval is presen... more In this paper, a new low level feature suitable for Hand Drawn Color Sketches retrieval is presented. The proposed feature structure combines color and spatial color distribution information. The combination of these two features in one vector classifies the proposed descriptor to the family of Composite Descriptors. In order to extract the color information, a fuzzy system is being used, which is mapping the number of colors that are included in the image into a custom palette of 8 colors. The way by which the vector of the proposed descriptor is being formed, describes the color spatial information contained in images. To be applicable in the design of large image databases, the proposed descriptor is compact, requiring only 48 bytes per image. Experiments demonstrate the effectiveness of the proposed technique.
2021 17th International Conference on Distributed Computing in Sensor Systems (DCOSS), 2021
This paper introduces a plug-and-play descriptor that can be effectively adopted for image retrie... more This paper introduces a plug-and-play descriptor that can be effectively adopted for image retrieval tasks without prior initialization or preparation. The description method utilizes the recently proposed Vision Transformer network while it does not require any training data to adjust parameters. In image retrieval tasks, the use of Handcrafted global and local descriptors has been very successfully replaced, over the last years, by the Convolutional Neural Networks (CNN)-based methods. However, the experimental evaluation conducted in this paper on several benchmarking datasets against 36 stateof-the-art descriptors from the literature demonstrates that a neural network that contains no convolutional layer, such as Vision Transformer, can shape a global descriptor and achieve competitive results. As fine-tuning is not required, the presented methodology's low complexity encourages adoption of the architecture as an image retrieval baseline model, replacing the traditional and well adopted CNN-based approaches and inaugurating a new era in image retrieval approaches.
Concurrency and Computation: Practice and Experience, 2017
SummaryIn this paper, a novel visual Place Recognition approach is evaluated based on a visual vo... more SummaryIn this paper, a novel visual Place Recognition approach is evaluated based on a visual vocabulary of the Color and Edge Directivity Descriptor (CEDD) to address the loop closure detection task. Even though CEDD was initially designed so as to globally describe the color and texture information of an input image addressing Image Indexing and Retrieval tasks, its scalability on characterizing single feature points has already been proven. Thus, instead of using CEDD as a global descriptor, we adopt a bottom‐up approach and use its localized version, Local Color And Texture dEscriptor, as an input to a state‐of‐the‐art visual Place Recognition technique based on Visual Word Vectors. Also, we use a parallel execution pipeline based on a previous work of ours using the well established General Purpose Graphics Processing Unit (GPGPU) computing. Our experiments show that the usage of CEDD as a local descriptor produces high accuracy visual Place Recognition results, while the para...
2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015
Image indexing refers to describing the visual multimedia content of a medium, using high level t... more Image indexing refers to describing the visual multimedia content of a medium, using high level textual information or/and low level descriptors. In most cases, images and videos are associated with noisy and incomplete usersupplied textual annotations, possibly due to omission or the excessive cost associated with the metadata creation. In such cases, Content Based Image Retrieval (CBIR) approaches are adopted and low level image features are employed for indexing and retrieval. We employ the Colour and Edge Directivity Descriptor (CEDD), which incorporates both colour and texture information in a compact representation and reassess it for parallel execution, utilizing the multicore power provided by General Purpose Graphic Processing Units (GPGPUs). Experiments conducted on four different combinations of GPU-CPU technologies revealed an impressive gained acceleration when using a GPU, which was up to 22 times faster compared to the respective CPU implementation, while real-time indexing was achieved for all tested GPU models.
The Journal of Supercomputing, 2014
In this paper, we focus on implementing the extraction of a well-known lowlevel image descriptor ... more In this paper, we focus on implementing the extraction of a well-known lowlevel image descriptor using the multicore power provided by general-purpose graphic processing units (GPGPUs). The color and edge directivity descriptor, which incorporates both color and texture information achieving a successful trade-off between effectiveness and efficiency, is employed and reassessed for parallel execution. We are motivated by the fact that image/frame indexing should be achieved real time, which in our case means that a system should be capable of indexing a frame or an image as it becomes part of a database (ideally, calculating the descriptor as the images are captured). Two strategies are explored to accelerate the method and bypass resource limitations and architectural constrains. An approach that exclusively uses the GPU together with a hybrid implementation that distributes the computations to both available GPU and CPU resources are proposed. The first approach is strongly based on the compute unified device architecture and excels compared to all other solutions when the GPU resources are abundant. The second implementation suggests a hybrid scheme where the extraction process is split in two sequential stages, allowing the input data (images or video frames) to be pipelined through the central and the graphic processing units. Experimental results were conducted on four different combinations of GPU-CPU technologies in order to highlight the strengths and the weaknesses of all implementations. Real-time indexing is obtained over all computational setups for both GPU-only and Hybrid techniques. An impressive 22 times acceleration is recorded for the GPU-only method. The proposed Hybrid implementation outperforms the GPU-only implementation and becomes the preferred solution when a low-cost setup (i.e., more advanced CPU combined with a relatively weak GPU) is employed.
WIAMIS 2008 - Proceedings of the 9th International Workshop on Image Analysis for Multimedia Interactive Services, 2008
This paper deals with the extraction of a new low level feature that combines, in one histogram, ... more This paper deals with the extraction of a new low level feature that combines, in one histogram, color and texture information. This feature is named FCTH-Fuzzy Color and Texture Histogram-and results from the combination of 3 fuzzy systems. FCTH size is limited to 72 bytes per image, rendering this descriptor suitable for use in large image databases. The proposed feature is appropriate for accurately retrieving images even in distortion cases such as deformations, noise and smoothing. It is tested on a large number of images selected from proprietary image databases or randomly retrieved from popular search engines. To evaluate the performance of the proposed feature, the averaged normalized modified retrieval rank was used. An online demo that implements the proposed feature in an image retrieval system is available at: http://orpheus.ee.duth.gr/image_retrieval.
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Papers by Yiannis Boutalis