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CIREC: Cluster correlogram image retrieval and categorization using MPEG-7 descriptors

CIREC: Cluster correlogram image retrieval and categorizatio...

引用

ieee symposium on computational intelligence in image and signal processing

作者： Abdullah, A. Wiering, Marco A. Univ Utrecht Dept Informat & Comp Sci Intelligent Syst Grp NL-3508 TB Utrecht Netherlands

ISBN: (纸本)9781424407071

Content-based image retrieval is generally about understanding of information in the images concerned. The more the system is able to understand the content of images the more effective it will be in retrieving desired images. In this paper, we have developed a method that combines a clustering technique with the color correlation histogram. According to this method, an image is divided into several blocks using a fixed partitioning scheme. Then, selected lower-level MPEG-7 features are used to represent the partitions and a clustering technique is applied to group similar patterns into a cluster. The cluster indices will then be used to construct a corellogram which is not based on the lower-level primitives, but on regions consisting of a distribution of primitives. The result shows that the proposed method significantly outperforms other methods on image retrieval and categorization.

关键词： content-based retrieval image classification image coding image colour analysis image retrieval pattern clustering CIREC MPEG-7 descriptors cluster correlogram image retrieval color correlation histogram content-based image retrieval fixed partitioning image retrieval content-based image retrieval image colour analysis Content retrieval image coding image classification Cluster Analysis

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Evolutionary algorithms in the classification of mammograms

Evolutionary algorithms in the classification of mammograms

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ieee symposium on computational intelligence in image and signal processing

作者： Hope, D. C. Munday, E. Smith, S. L. Univ York Dept Elect York YO10 5DD N Yorkshire England

ISBN: (纸本)9781424407071

The application of pattern recognition techniques to radiology has the potential to detect cancer earlier and save lives, and consequently much research has been devoted to this problem. This worked tackled a subset of the problem, investigating a novel method of classifying mammograms using an evolutionary approach known as Cartesian Genetic Programming (CGP). Microcalcifications, one of two major indicators of cancer on mammograms, were used for the classification. A large software framework was written in order to investigate this, which allows the viewing of images, manual segmentation of lesions and then automatic classification. Two classification approaches were pursued, the first classifying on texture features and the second, a new approach, classifying by using the lesion's raw pixel array. Early results using the system showed some potential. It was found that during training, networks could obtain correct classification rates of between 80 and 100%. The best results were approaching those in the contemporary literature and suggest the technique warrants further investigation.

关键词： cancer diagnostic radiography feature extraction genetic algorithms image classification image texture mammography medical image processing Cartesian genetic programming cancer detection cancer indicators evolutionary algorithms lesi image classification evolutionary algorithm Genetic Algorithm (GA) diagnostic radiography image texture Medical image processing cancer test Feature extraction pictorial pattern recognition algorithm

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A pseudo-labeling framework for content-based image retrieval

A pseudo-labeling framework for content-based image retrieva...

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ieee symposium on computational intelligence in image and signal processing

作者： Yap, Kim-Hui Wu, Kui Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781424407071

This paper presents a new pseudo-label fuzzy support vector machine (PLFSVM)-based active learning framework in interactive content-based image retrieval (CBIR) systems. One of the main issues associated with relevance feedback in CBIR systems is the small sample problem where only a limited number of labeled samples are available for learning. This is because image labeling is time consuming and users are often reluctant to label too many images for feedback. Learning from insufficient training samples often constrains the retrieval performance. To address this problem, we propose a new algorithm based on the concept of pseudo-labeling. It incorporates carefully selected unlabeled images to enlarge the training data set and assigns proper pseudo-labels to them. Further, some fuzzy rules are utilized to automatically estimate class membership of the pseudo-labeled images. Fuzzy support vector machine (FSVM) is designed to take into account the fuzzy nature of some training samples during its training. In order to exploit the advantages of pseudo-labeling, active learning and the structure of FSVM, we develop a unified framework to perform content-based image retrieval. Experimental results based on a database of 10,000 images demonstrate the effectiveness of the proposed method.

关键词： Content based retrieval

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A wavelet-fuzzy logic based system to detect and identify electric power disturbances

A wavelet-fuzzy logic based system to detect and identify el...

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ieee symposium on computational intelligence in image and signal processing

作者： Chacon, M. I. Duran, J. L. Santiesteban, L. A. Chihuahua Inst Technol Power Elect Lab DSP & Vis Lab Chihuahua 31310 Chih Mexico

ISBN: (纸本)9781424407071

In this paper a method to detect and classify typical electric power disturbances is presented. Voltage sags, swells, momentary outage and capacitor switching transient events (CSTs) are the electric disturbances considered in this work. Disturbance detection and some disturbance features are obtained by the discrete wavelet transform. These features are used in the design of a fuzzy rule classification system. Both methods, wavelet detection and the fuzzy classifier, are extensively tested on the detection and classification of several simulated electric disturbances. In particular, capacitor switching transients events (CSTs) are presented to validate the proposed methodologies. The performance of the Wavelet-Fuzzy logic system turned out to be 95% of correct identification. The performance of the fuzzy classifier outperforms a classifier based on crisp decisions also presented in this paper. This performance is acceptable compared with other methodologies reported in the literature with performances varying from 92% to 95%.

关键词： capacitor switching discrete wavelet transforms fuzzy logic fuzzy set theory power engineering computing power system faults signal classification capacitor switching transient events discrete wavelet transform electric power disturbance detection electr discrete wavelet transform capacitor switching Power system faults Power engineering computing Fuzzy logic signal classification Fuzzy Set Theory Classifiers

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Enhanced shot-based video adaptation using MPEG-21 generic bitstream syntax schema

Enhanced shot-based video adaptation using MPEG-21 generic b...

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ieee symposium on computational intelligence in image and signal processing

作者： De Bruyne, Sarah De Schrijver, Davy De Neve, Wesley Van Deursen, Davy Van de Walle, Rik Univ Ghent IBBT Dept Elect & Informat Syst Multimedia Lab B-9050 Ledeberg Ghent Belgium

ISBN: (纸本)9781424407071

Semantic video adaptation takes into account the relevance of the different fragments of the video content in order to create a tailored video stream based on the user's preferences. As a shot can be considered as the smallest semantic unit in a video sequence, metadata can be added to each shot using MPEG-7 descriptions. Based on these metadata and the user's preferences, the original bitstream can be adapted in order to obtain the desired fragments. MPEG-21 DIA offers a tool, gBS Schema, for exposing the high-level structure of a binary resource as an XML description. In this paper, shot information is inserted in these descriptions to create a link between metadata and semantic video adaptation. Furthermore, this paper proposes to keep the structure of these descriptions format-agnostic. As a result, only one generic transformation style sheet has to be implemented to support shot-based video adaptation of sequences compliant with different video specifications. Special attention is payed to sequences coded with the H.264/AVC standard as this specification contains several interesting features important for shot-based video adaptation.

关键词： image enhancement

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Boundary refined texture segmentation based on K-Views and datagram methods

Boundary refined texture segmentation based on K-Views and d...

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ieee symposium on computational intelligence in image and signal processing

作者： Song, Emnin Jin, Renchao Hung, Chih-Cheng Luo, Yu Xu, Xiangyang Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China Southern Polytech State Univ Sch Comp & Software Engn Marietta GA 30060 USA

ISBN: (纸本)9781424407071

We propose a new texture segmentation algorithm to improve the segmentation of boundary areas in the image. In some applications such as medical image segmentation, an exact segmentation on the boundary areas is needed. But satisfactory segmentation results cannot be obtained on the boundary areas among different texture classes with some existing texture segmentation algorithms in our preliminary experiments. The proposed algorithm consists of three steps. The first step is to apply the K-View-datagram segmentation method to the image to obtain an initial segmentation;the second step is to find a boundary set which includes the pixels with high probabilities to be misclassified by the initial K-View-datagram segmentation;the third step is to apply a modified K-views template method with a small scanning window to the boundary set to refine the segmentation. The evaluation of the proposed algorithm was carried out with the benchmark images randomly taken from Brodatz Gallery and the ultrasonic prostate images provided by the hospitals. Initial experimental results show that the concept of boundary set defined in this paper can catch most of misclassified pixels of the output of the initial K-View-datagram segmentation. The new segmentation algorithm gives high segmentation accuracy and classifies the boundary areas better than the existing algorithms.

关键词： image segmentation

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X-ray image segmentation using active contour model with global constraints

X-ray image segmentation using active contour model with glo...

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ieee symposium on computational intelligence in image and signal processing

作者： Jiang, Y. Meng, J. Babyn, P. Ryerson Univ Dept Comp Sci 350 Victoria St Toronto ON M5B 2K3 Canada Hosp Sick Children 555 Univ Ave Toronto ON M5G 1X8 Canada

ISBN: (纸本)9781424407071

This paper presents an image segmentation method that outlines fractured bones in an X-ray image of a patient's arm within cast materials, and displays the alignment between the fractured bones. The cast material overlaying on the fractured bones creates extra noises to the X-ray image and provides challenges to the segmentation method. Our segmentation method aims on outlining the objects from a low contrast and high noise ratio of the X-ray images. A geodesic active contour model with global constraints is applied to this segmentation task. A prior shape is collected and embedded into the active contour model as a global constraint. A maximum-likelihood function is derived and used as a feedback system for each evolving process to a decision making procedure. Mutual Information is employed to measure the difference or the likelihood between the prior shape and the evolving curve. Experimental results show that the method produces the outlines of the fractured bones on the low contrast X-ray images robustly and accurately. The computation of our segmentation method is fast and efficient.

关键词： bone diagnostic radiography feature extraction image segmentation maximum likelihood estimation medical image processing X-ray image segmentation cast materials fractured bone alignment geodesic active contour model maximum-likelihood function patient ar image segmentation diagnostic radiography casting material Medical image processing maximum likelihood estimation Feature extraction Feedback X-rays

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Concurrent self-organizing maps for multispectral facial image recognition

Concurrent self-organizing maps for multispectral facial ima...

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ieee symposium on computational intelligence in image and signal processing

作者： Neagoe, Victor-Emil Mugioiu, Alexandru-Cristian Tudoran, Cristian-Tudor Univ Politehn Bucuresti Dept Elect Telecommun & Informat Technol Bucharest 062510 Romania

ISBN: (纸本)9781424407071

This paper is dedicated to multispectral facial recognition, based on the model of Concurrent Self-Organizing Maps (CSOM), previously proposed by first author. The first approach of this paper is to apply CSOM classifier for color face recognition. Main variant of this approach has the follwing processing stages: (a) color conversion from the 3D RGB space into an optimum 2D selected color feature space;(b) Principal Component Analysis (PCA) for each resulted color component;(c) feature fusion;(d) CSOM/SOM classification. The proposed system is experimented using the ESSEX database of color facial images;it contains 151 subjects, where each is represented by 20 pictures of 200 x 180 pixels. The obvious advantage of CSOM over SOM is proved. The second approach of this paper is the implementation of a real time CSOM face recognition system using the decision fusion that combines the recognition scores generated from visual channels M G, B, and Y classifiers) with the thermal infrared classifier. As a source of color and infrared images, we used our VICFACE database of 38 subjects. Any picture has 160 x 120 pixels;for each subject there are pictures corresponding to various face expressions and illuminations, in the visual and infrared spectrum. The spectral sensitivity of infrared images corresponds to the longwave range of 7.5 - 13 pm. The very good experimental results are given, proving nearly invariance to illumination conditions.

关键词： Face recognition

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Welcome to ciisp 2007 and Honolulu

Welcome to CIISP 2007 and Honolulu

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