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image Indexing and Retrieval in Compressed Domain Using Color Clusters

Image Indexing and Retrieval in Compressed Domain Using Colo...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Meekal Bajaj Jose A. lay Electronics and Communication Engineering Department Netaji Subhas Institute of Technology New Delhi India School of Electrical and Information Engineering University of Sydney NSW Australia

A compressed domain color-based image indexing method that avoids overheads associated with full decompression and color space transformation by operating in the YCbCr space has been presented. The proposed method performs a hard segmentation of the color space into predefined clusters based on perceptual similarity. A three dimensional color descriptor is generated by extracting the average intensity value of the Y, Cb and Cr components for each 8times8 DCT block. Each blocks descriptor is subsequently allocated to its corresponding cluster, whose centroid is updated using a weighted mean. The similarity measure is evaluated using a compact four dimensional feature vector from each cluster, which consists of the quantized centroid coordinates and the percentage contribution to the image composition by the cluster. Retrieval is performed by comparing the feature attributes of the clusters having significant membership in the query image, to those with the database images; the obtained matches are then integrated to evaluate the final ranking. The experimental results of the proposed model on a database of 7380 images are reported

关键词： Indexing image retrieval image coding image databases Spatial databases image segmentation Chromium Discrete cosine transforms Coordinate measuring machines Information retrieval

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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, ciisp

作者： Y Jiang J Meng P Babyn Department of Computer Science Ryerson University Toronto ONT Canada Hospital for Sick Children Toronto ONT Canada

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： X-ray imaging image segmentation Active contours Bones Noise shaping Shape measurement Displays signal to noise ratio Active shape model Feedback

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An Efficient RLS Algorithm For Output-Error Adaptive IIR Filtering And Its Application To Acoustic Echo Cancellation

An Efficient RLS Algorithm For Output-Error Adaptive IIR Fil...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Jafar Ramadhan Mohammed Gurnam Singh Electronics Engineering College Communication Engineering University of Mosul Mosul Iraq Electrical Engineering Department Punjab Engineering College Chandigarh India

In this letter, an efficient recursive least squares (RLS) algorithm using infinite impulse response (IIR) filter for acoustic echo cancellation (AEC) is proposed. The RLS adaptive filter is naturally extended from the finite impulse response (FIR) structure to the IIR structure. One of the main advantages of an IIR RLS filter is that a long-delay echo can be synthesized by a relatively small number of filter coefficients leading to lesser computational complexity. In addition it is more suitable for modeling physical systems, due to its pole-zero structure, over their FIR counterparts. To investigate the tracking performance and the stability of the proposed IIR RLS filter in a practical implementation, real data for far end speech signal and its echo were used in car environment. The proposed algorithm is shown to have global convergence. To demonstrate the effectiveness of the proposed IIR RLS filter, it is compared to the usual FIR RLS filter. The good performance of the proposed IIR RLS algorithm for AEC have been verified via computer simulations

关键词： Resonance light scattering Filtering algorithms Adaptive filters IIR filters Acoustic applications Echo cancellers Finite impulse response filter Least squares methods computational complexity Stability

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An Integrated Neuro-Fuzzy Approach to MPEG Video Transmission in Bluetooth

An Integrated Neuro-Fuzzy Approach to MPEG Video Transmissio...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： H. B. Kazemian S. Chantaraskul Computing Communications Technology and Mathematics Department London Metropolitan University London UK

This paper presents an integrated neuro-fuzzy (NF) scheme and a rule-based-fuzzy (RBF) scheme applications to Moving Picture Expert Group (MPEG) video transmission in Bluetooth. In a Bluetooth network, transmission rate is unpredictable due to interferences by other wireless devices or general Bluetooth channel noises. MPEG variable bit rate (VBR) video transmission is also unreliable and presents long delay and excessive data loss, due to variations in bit rate. It is therefore almost impossible to transmit MPEG VBR video over a Bluetooth channel, without data loss, excessive time delay or image quality degradation. In this work, a traffic-shaping buffer is introduced before the host controller interface (HCI) of the Bluetooth protocol stack. An integrated NF scheme reduces the burstiness of the traffic-shaper output rate to enable the MPEG VBR video to comply with the generic cell rate algorithm contract before entering the Bluetooth channel. The computer simulation results show that the application of the proposed scheme reduces excessive time delay and data loss at the HCI, as compared with a conventional video transmission in Bluetooth

关键词： Bluetooth Propagation losses Noise measurement Bit rate Delay effects Traffic control Human computer interaction MPEG standards Interference image quality

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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, ciisp

作者： Sarah De Bruyne Davy De Schrijver Wesley De Neve Davy Van Deursen Rik Van de Walle Department of Electronics and Information Systems-Multimedia Laboratory-IBBT Ghent University Ledeberg-Ghent Belgium

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 paid 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： XML Streaming media Video sequences MPEG 7 Standard computational intelligence Video signal processing Information systems Multimedia systems Automatic voltage control Code standards

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Evolving Fuzzy Rule-based Classifiers

Evolving Fuzzy Rule-based Classifiers

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Plamen Angelov Xiaowei Zhou Frank Klawonn Department of Communication Systems InfoLab21 Lancaster University Lancaster UK Department of Computer Science University of Applied Sciences Wolfenbuettel Germany

A novel approach to on-line classification based on fuzzy rules with an open/evolving structure is introduced in this paper. This classifier can start `from scratch', learning and adapting to the new data samples or from an initial rule-based classifier that can be updated based on the new information contained in the new samples. It is suitable for real-time applications such as classification streaming data, robotic applications, e.g., target and landmark recognition, real-time machine health monitoring and prognostics, fault detection and diagnostics, etc. Each prototype is a data sample that represents the focal point of a fuzzy rule per class and is selected based on the data density by an incremental and evolving procedure. This approach is transparent, linguistically interpretable, and applicable to both fully unsupervised and partially supervised learning. It has been validated by two well known benchmark problems and by real-life data in a parallel paper. The contributions of this paper are: i) introduction of the concept of evolving (open structure) classification (eClass) of streaming data; ii) experiments with well known benchmark classification problems (Iris and wine reproduction data sets)

关键词： Fuzzy systems Data mining Knowledge based systems Fault detection Classification tree analysis signal processing Learning systems Decision trees Bayesian methods Evolution (biology)

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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, ciisp

作者： Victor-Emil Neagoe Alexandru-Cristian Mugioiu Cristian-Tudor Tudoran Department of Electronics Telecommunications and Information Technology Polytechnic University of Bucharest Bucharest Romania

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 times 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 (R, G, B, and Y classifiers) with the thermal infrared classifier. As a source of color and infrared images, we used our VICE ACE database of 38 subjects. Any picture has 160 - 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 mum. The very good experimental results are given, proving nearly invariance to illumination conditions

关键词： Self organizing feature maps image recognition Face recognition image color analysis Principal component analysis image databases Infrared imaging Lighting Infrared spectra image converters

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A Pilot Study of Automatic Lung Tumor Segmentation from Positron Emission Tomography images using Standard Uptake Values

A Pilot Study of Automatic Lung Tumor Segmentation from Posi...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Aparna Kanakatte Jayavardhana Gubbi Nallasamy Mani Tomas Kron David Binns Department of Electrical and Computer Systems Monash University Clayton VIC Australia Department of Electrical and Electronics Engineering University of Melbourne Parville VIC Australia Peter MacCallum Cancer Centre East Melbourne VIC Australia

Positron emission tomography (PET) is a medical imaging procedure that shows the physiological function of an organ or tissue. The role of PET during the past decade has evolved rapidly in the detection of lung tumors but the research on quantitative evaluation of PET images is still in its infancy. PET commonly involves scanning the patient after administration of a radioactive analogue of glucose called fluorodeoxy-glucose (FDG). Tumor cells metabolise more glucose than most normal cells. In PET lung images the heart is often visible and because of its constant pumping of blood it requires more glucose and hence both the tumor and the heart appear brighter than the rest in the PET image. In this paper we present a novel segmentation scheme for detecting the tumor alone in lung PET images using standard uptake values (SUV) and connected component analysis. We perform the segmentation in two steps. In coarse segmentation, a non linear scaling of SUV values is performed and then a threshold is chosen adaptively to convert the gray image into the binary image. Fine segmentation is performed on the coarse segmented data in order to narrow down the region of interest using connected component labeling. To our knowledge no one has used connected component analysis for segmenting PET images. We compare our proposed scheme with several commonly used medical image segmentation techniques like threshold, Sobel edge detector, Laplacian of Gaussian (LoG) edge detector, region growing and SUV based segmentation (applied only to PET as SUV is specific to PET). One of the problems in lung tumor detection is the presence of the heart in the image which accumulates activity and often gets recognized as a hot spot (a probable tumor). All the other segmentation schemes detected both the heart and the tumor as hot spots while our segmentation scheme detected the tumor alone as the hot spot. The preliminary study of the proposed scheme has yielded very promising results and will be stu

关键词： Lung neoplasms image segmentation Positron emission tomography Heart image edge detection Sugar Tumors Biomedical imaging image analysis Detectors

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A Flexible Fully-Multiplicative Orthogonal-Group Based ICA Algorithm

A Flexible Fully-Multiplicative Orthogonal-Group Based ICA A...

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ieee symposium on computational intelligence and Bioinformatics and computational Biology (CIBCB)

作者： Yalan Ye Jing Wan Zhi-Lin Zhang Chen Jia Wu Lei School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Institute of Image Processing and Pattern Recognition Shanghai JiaoTong University Shanghai China

In this paper, we propose a flexible fully-multiplicative orthogonal-group based ICA (FlexibleOgICA) algorithm, which can instantaneously separate the mixture of sub-Gaussian and super-Gaussian source signals. It adopts a self-adaptive nonlinear function, which adjusts its parameter to achieve better performance based on the estimation of the kurtosis of super-Gaussian source signals. We also have successfully applied the algorithm to obtain the fetal electrocardiogram (FECG) signal, showing its fast convergence speed and high separation performance

关键词： Independent component analysis signal processing algorithms Convergence computational intelligence Bioinformatics computational biology signal processing Multidimensional signal processing Biomedical signal processing Switches

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ieee symposium on Foundations of computational intelligence (FOCI'07)

IEEE Symposium on Foundations of Computational Intelligence ...

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ieee symposium on Foundations of computational intelligence, FOCI

The following topics are dealt with: computational intelligence; fuzzy system; evolutionary algorithms; fuzzy classification; real-life computing; lifelog data sensing; lifelog data modeling; artificial immune system; information theoretic learning; neural network learning architecture; granular computing; rough sets; inteval methodologies; evolutionary games; fuzzy sets; fuzzy aggregation; fuzzy logic control; image and signal processing; and fuzzy clustering

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