[Auto Generated] . DEDICATION ACKNOWLEDGEMENT ABSTRACT TABLE OF CONTENTS Chapter I. INTRODUCTION Chpater II. STATE OF THE ART: PAST AND PRESENT 2.1 Thresholding 2.2 Spatial Differencing: Noise Free images 2.3 Spatial ...
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[Auto Generated] . DEDICATION ACKNOWLEDGEMENT ABSTRACT TABLE OF CONTENTS Chapter I. INTRODUCTION Chpater II. STATE OF THE ART: PAST AND PRESENT 2.1 Thresholding 2.2 Spatial Differencing: Noise Free images 2.3 Spatial Differencing: Noisy images 2.4 Spatial Differentiation: High Order Derivatives 2.5 Contour Following 2.6 Statistical Differencing 2.7 Replacement processing 2.8 Horizontally Convex Object Chapter III. ESTIMATION OF OBJECT BOUNDARY: FORMULATION 3. 1 Modeling 3.2 Scanning 3.3 Represen
This book constitutes the refereed proceedings of the 12th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2016, and three parallel workshops, held in Thessaloniki, ...
ISBN:
(数字)9783319449449
ISBN:
(纸本)9783319449432
This book constitutes the refereed proceedings of the 12th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2016, and three parallel workshops, held in Thessaloniki, Greece, in September 2016. The workshops are the Third Workshop on New Methods and Tools for Big Data, MT4BD 2016, the 5th Mining Humanistic Data Workshop, MHDW 2016, and the First Workshop on 5G - Putting Intelligence to the Network Edge, 5G-PINE 2016. The 30 revised full papers and 8 short papers presented at the main conference were carefully reviewed and selected from 65 submissions. The 17 revised full papers and 7 short papers presented at the 3 parallel workshops were selected from 33 submissions. The papers cover a broad range of topics such as artificial neural networks, classification, clustering, control systems - robotics, data mining, engineering application of AI, environmental applications of AI, feature reduction, filtering, financial-economics modeling, fuzzy logic, genetic algorithms, hybrid systems, image and video processing, medical AI applications, multi-agent systems, ontology, optimization, pattern recognition, support vector machines, text mining, and Web-social media data AI modeling.
Steganalysis is capable of identifying the carrier(s) which have information hidden in them in such a way that their very existence is concealed. In this paper we propose a classification system with neural networks w...
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ISBN:
(纸本)9781509010226
Steganalysis is capable of identifying the carrier(s) which have information hidden in them in such a way that their very existence is concealed. In this paper we propose a classification system with neural networks which reduces computational complexity through a pre-processing step (feature selection) performed by Bhattacharyya distance for image steganalysis. This approach is able to identify relevant features which are a subset of original features extracted from spatial as well as transform domain. It helps in overcoming the problem of "curse of dimensionalty" by removing redundant features by feature selection step before classifying the dataset. The experiments are performed on dataset obtained by four steganography algorithms outguess, steghide, PQ and nsF5 with two classifiers Support Vector Machine and Back Propagation neural networks. Classifier in combination with Bhattacharyya distance filter feature selection approach shows an improvement of 2-20% against total number of features.
image denoising is a quite active research area in the domain of imageprocessing. The essential requirement for a good denoising method is to preserve significant image structures (e.g., edges) after denoising. Wavel...
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ISBN:
(数字)9789811007552
ISBN:
(纸本)9789811007552;9789811007545
image denoising is a quite active research area in the domain of imageprocessing. The essential requirement for a good denoising method is to preserve significant image structures (e.g., edges) after denoising. Wavelet transforms and singular value decomposition (SVD) have been independently used to achieve edge-preserving denoising results for natural images. Numerous denoising algorithms have utilized these two techniques independently. In this paper, a novel technique for edge-preserving image denoising, which combines wavelet transforms and SVD, is proposed. It is adaptive to the inhomogeneous nature of natural images. The multiresolution representation of the corrupted image in wavelet domain is obtained through the application of a discrete wavelet transform to it. A block-SVD based edge-adaptive thresholding scheme which relies on estimation of noise level is employed to reduce the noise contents while preserving significant details of the original version. Comparison of the experimental results with other state-of-the-art methods reveals the fact that the proposed approach achieves very impressive gain in denoising performance.
Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the obje...
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ISBN:
(纸本)9781509035687
Content-Based image Retrieval (CBIR) aims to retrieve similar graphical objects from large databases based on their contents. CBIR requires definition of descriptors, algorithms that condense information from the object in order to represent it usually as a real number or a vector in Rn. This article presents the Spectral Descriptor, a new descriptor designed for retrieving three-dimensional geometric objects applied to aid the diagnosis of Congestive Heart Failure (CHF). Our descriptor is based on techniques of compressive sensing and rewrites the coordinates of 3D objects vertices on a basis on which they have a sparse representation. Tests with surfaces reconstructed from heart MRI images, specifically from left ventricle, show that the descriptor has presented a good performance, reaching an average precision of approximately 85% for CHF and 71% for non-CHF cases, maintaining high levels of precision. Results also showed that the Spectral Descriptor can decrease the high dimensionality of features vectors in CBIR systems.
This paper focuses on the effective reducing of operating costs in the Smart Home Care system. The applied developed system components are designed for seniors auxiliary monitoring of the energy consumption. The paper...
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This paper focuses on the effective reducing of operating costs in the Smart Home Care system. The applied developed system components are designed for seniors auxiliary monitoring of the energy consumption. The paper describes the solution of information processing about quantity of the consumed electric and heat energy, gas and water consumption by using of the advanced system for consumption meters with recognition of video camera signal in the Smart Home Care monitoring system. The concept structure and principles of energy monitoring are designed with developed advanced electronic components, which are realized and verified for industry and commerce sphere.
The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. The Sentinel-2 for Agriculture project S2Agri (http://***/SitePages/***) is designed to ...
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The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. The Sentinel-2 for Agriculture project S2Agri (http://***/SitePages/***) is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring for many agricultural systems across the globe. In the framework of this project, this article studies the construction of a dynamic cropland mask. This mask consists of a binary annual-cropland/no-annual-cropland map produced several times during the season to serve as a mask for monitoring crop growing conditions over the growing season. The construction of the mask relies on two classical pattern recognition techniques: feature extraction and classification. One pixel- and two object-based strategies are proposed and compared. A set of 12 test sites are used to benchmark the methods and algorithms with regard to the diversity of the agro-ecological context, landscape patterns, agricultural practices and actual satellite observation conditions. The classification results yield promising accuracies of around 90% at the end of the agricultural season. Efforts will be made to transition this research into operational products once Sentinel-2 data become available.
The proceedings contain 104 papers. The topics discussed include: a comparative study using the methods of simulated annealing and non-linear hebbian learning for fuzzy cognitive maps performances;self-labeled hidden ...
ISBN:
(纸本)9781509034291
The proceedings contain 104 papers. The topics discussed include: a comparative study using the methods of simulated annealing and non-linear hebbian learning for fuzzy cognitive maps performances;self-labeled hidden naive bayes algorithm for semi-supervised classification;performance analyses and improvement of multilayer neural networks;algorithms for imageprocessing in graph-based volumetric segmentation;optimizing signal and discriminant information for hyperspectral images;fake banknote detection using multispectral images;hand tracking as a tool to quantify carpal tunnel syndrome preventive exercises;and sound and stereoscopic 3D: examining the effects of sound on depth perception in stereoscopic.
The integration of advance human motion analysis techniques in low-cost video cameras has emerged for consumer applications, particularly in video surveillance systems. These smart and cheap devices provide the practi...
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The integration of advance human motion analysis techniques in low-cost video cameras has emerged for consumer applications, particularly in video surveillance systems. These smart and cheap devices provide the practical solutions for improving the public safety and homeland security with the capability of understanding the human behaviour automatically. In this sense, an intelligent video surveillance system should not be constrained on a person viewpoint, as in natural, a person is not restricted to perform an action from a fixed camera viewpoint. To achieve the objective, many state-of-the-art approaches require the information from multiple cameras in their processing. This is an impractical solution by considering its feasibility and computational complexity. First, it is very difficult to find an open space in real environment with perfect overlapping for multi-camera calibration. Secondly, the processing of information from multiple cameras is computational burden. With this, a surge of interest has sparked on single camera approach with notable work on the concept of view specific action recognition. However in their work, the viewpoints are assumed in a priori. In this paper, we extend it by proposing a viewpoint estimation framework where a novel human contour descriptor namely the fuzzy qualitative human contour is extracted from the fuzzy qualitative Poisson human model for viewpoint analysis. Clustering algorithms are used to learn and classify the viewpoints. In addition, our system is also integrated with the capability to classify front and rear views. Experimental results showed the reliability and effectiveness of our proposed viewpoint estimation framework by using the challenging IXMAS human action dataset.
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