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Shape classification via image-based multiscale description

pattern recognition 2011年第9期44卷 2134-2146页

作者： Direkoglu, Cem Nixon, Mark S. Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

We introduce a new multiscale Fourier-based object description in 2-D space using a low-pass Gaussian filter (LPGF) and a high-pass Gaussian filter (HPGF), separately. Using the LPGF at different scales (standard deviation) represents the inner and central part of an object more than the boundary. On the other hand using the HPGF at different scales represents the boundary and exterior parts of an object more than the central part. Our algorithms are also organized to achieve size, translation and rotation invariance. Evaluation indicates that representing the boundary and exterior parts more than the central part using the HPGF performs better than the LPGF-based multiscale representation, and in comparison to Zernike moments and elliptic Fourier descriptors with respect to increasing noise. Multiscale description using HPGF in 2-D also outperforms wavelet transform-based multiscale contour Fourier descriptors and performs similar to the perimeter descriptors without any noise. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Shape classification Fourier-based description Multiscale representation Gaussian filter Feature extraction computer vision

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A novel approach for delineation and feature extraction in QRS complex of ECG signal

A novel approach for delineation and feature extraction in Q...

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2011 International Conference on Image Information Processing, ICIIP 2011

作者： Pramanik, Sayak Mitra, Rupendra Nath Mitra, Sucharita Chaudhuri, Bidyut Baran Department of Electronics and Communication Institute of Engineering and Management Kolkata India Network Planning and Optimization Nokia Siemens Networks Pvt. Ltd. Kolkata India Department of Electronics Netaji Nagar Day College Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781612848617

This paper reports the development of a software suite to be accessed in future with any General Packet Radio Service (GPRS) enabled mobile phone or Personal Digital Assistant (PDA) for the extraction and analysis of disease-related features from the images of paper based ECG records. In India and other developing countries, the cheaper paper based ECG machines are mainly used. Also in rural areas of these countries - where there is acute dearth of qualified cardiologists, the cardiac diseases are still the major silent killers. One way of addressing this problem is cellular medicine which necessitates an intelligent cardiac parameter extraction algorithm. In our bid to address exactly this requirement, a software is developed with the help of few image processing techniques. At first, the background noises i.e. the gridlines are removed by thresholding technique. Binarization and thinning has been done for extraction of digital time data and then Discrete Wavelet Transform (DWT) and water reservoir based pattern recognition technique are subsequently used to delineate other important ECG parameters for ECG interpretation. © 2011 IEEE.

关键词： Electrocardiograms

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Proceedings of the 2011 International Conference on pattern Analysis and Intelligent Robotics - Special Track on Human Centered Multimedia Analysis, ICPAIR 2011

Proceedings of the 2011 International Conference on Pattern ...

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2011 International Conference on pattern Analysis and Intelligent Robotics - Special Track on Human Centered Multimedia Analysis, ICPAIR 2011

ISBN: (纸本)9781612844046

The proceedings contain 43 papers. The topics discussed include: intelligence technology for cyber-physical robot system;vision-based automatic incident detection system using image sequences for intersections;new image compression algorithm using proposed quantization approach;neighborhood discriminative manifold projection for face recognition in video;shock coupled coherence enhancing diffusion for robust core-point detection in fingerprints;a modified three level block truncation coding for image compression;mobile learning course content application as a revision tool: the effectiveness and usability;accessible targets for motion impaired users with hidden click zone technique;remedial software for negative numbers subtraction operation: meta-cognitive/constructivism approach;factoring culture as the main role to design game interface model;and self efficiency and social influence of computer support collaborative learning teaching and learning blog.

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Building look & feel concept models from color combinations With applications in image classification, retrieval, and color transfer

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VISUAL computer 2011年第12期27卷 1039-1053页

作者： Csurka, Gabriela Skaff, Sandra Marchesotti, Luca Saunders, Craig XRCE Xerox Res Ctr Europe Textual & Visual Pattern Anal Grp Meylan France

In this paper, we tackle the problem of associating combinations of colors to abstract concepts (e. g. capricious, classic, cool, delicate, etc.). Since such concepts are difficult to represent using single colors, we consider combinations of colors or color palettes. We leverage two novel databases for color palettes, and learn categorization models using both low and high level descriptors. It is shown that the Bag of Colors and Fisher Vectors are the most rewarding descriptors for palettes categorization and retrieval. A simple but novel and efficient method for cleaning weakly annotated data, whilst preserving the visual coherence of categories is also given. Finally, we demonstrate that abstract category models learned on color palettes can be used in different applications such as image personalization, concept-based palette, and image retrieval and color transfer.

关键词： pattern recognition Color vision Aesthetics

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Semantic image segmentation using oriented pattern analysis

Semantic image segmentation using oriented pattern analysis

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8th International Conference on Information, Communications and Signal Processing, ICICS 2011

作者： Ong, Hui Ting Ma, Kai-Kuang School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781457700309

Semantic image segmentation is often served as an instrumental front-end preprocessing of many image processing and computer vision applications. Different from the existing semantic segmentation methods which mostly rely on database training, a simple and effective approach is proposed in this paper by employing the oriented pattern as a class-discriminative feature, besides the use of color and texture. The developed algorithm is to discriminate three specific semantic classes sky, foliage, and building, which are commonly encountered in typical color images containing outdoor scene. In our approach, two maps will be generated from the input image: 1) the over-segmented map by using JSEG, and 2) the oriented pattern map by measuring the orientation coherence at each pixel position. Based on these maps, the region coherence of each over-segmented patch can be obtained by taking the average of all the orientation coherence values within the patch. The semantic class labeling for the patch can be simply conducted by checking the computed region coherence value against two empirically determined thresholds. Extensive simulation experiments have been conducted by testing various color images acquired from various sources, including the Microsoft Research Cambridge (MSRC) Object recognition Image Database that contains manually-segmented regions as the ground truth. All experimental results clearly show that the proposed method is able to consistently deliver highly attractive performance. © 2011 IEEE.

关键词： Object recognition

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Detection of Multiple Preceding Cars in Busy Traffic Using Taillights

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8th International Conference on Image Analysis and recognition (ICIAR) / 2nd International Conference on Autonomous and Intelligent Systems (AIS)

作者： Gupta, Rachana A. Snyder, Wesley E. N Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9783642215957;9783642215964

This paper presents an improved method for detecting and segmenting taillight pairs of multiple preceding cars in busy traffic in day as well as night. Novelties and advantages of this method are that it is designed to detect multiple car simultaneously, it does not require knowledge of lanes, it works in busy traffic in daylight as well as night, and it is fast irrespective of number of preceding vehicles in the scene, and therefore suitable for real-time applications. The time to process the scene is independent of the size of the vehicle in pixels, and the number of preceding cars detected. One of the previous night taillight detection methods in literature is modified to detect taillight pairs in the scene for both day and night conditions. This paper further introduces a novel hypothesis verification method based on the mathematical relationship between the vehicle distance from the vanishing point and the location of and distance between its taillights. This method enables the detection of multiple preceding vehicles in multiple lanes in a busy traffic environment in real-time. The results are compared with state-of-the-art algorithms for preceding vehicle detection performance, time and ease of implementation.

关键词： Taillight detection preceding vehicle detection autonomous vehicles computer vision

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A Biologically Inspired Model for Occluded patterns

A Biologically Inspired Model for Occluded Patterns

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18th International Conference on Neural Information Processing (ICONIP)

作者： Saifullah, Mohammad Linkoping Univ Dept Comp & Informat Sci S-58183 Linkoping Sweden

ISBN: (纸本)9783642249549;9783642249556

In this paper a biologically-inspired model for partly occluded patterns is proposed. The model is based on the hypothesis that in human visual system occluding patterns play a key role in recognition as well as in reconstructing internal representation for a pattern's occluding parts. The proposed model is realized with a bidirectional hierarchical neural network. In this network top-down cues, generated by direct connections from the lower to higher levels of hierarchy, interact with the bottom-up information, generated from the un-occluded parts, to recognize occluded patterns. Moreover, positional cues of the occluded as well as occluding patterns, that are computed separately but in the same network, modulate the top-down and bottom-up processing to reconstruct the occluded patterns. Simulation results support the presented hypothesis as well as effectiveness of the model in providing a solution to recognition of occluded patterns. The behavior of the model is in accordance to the known human behavior on the occluded patterns.

关键词： vision Neural network model Occluded patterns Biologically-inspired

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Image Analysis and recognition 2011

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丛书名： Lecture Notes in computer Science

2011年

作者： Mohamed Kamel Aurelio Campilho

ISBN: (数字)9783642215933

ISBN: (纸本)9783642215926

The two-volume set LNCS 6753/6754 constitutes the refereed proceedings of the 8th International Conference on Image and recognition, ICIAR 2011, held in Burnaby, Canada, in June 2011. The 84 revised full papers presented were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.

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Image Denoising by Scaled Bilateral Filtering

Image Denoising by Scaled Bilateral Filtering

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National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Shashaank M. Aswatha Jayanta Mukhopadhyay Partha Bhowmick Department of Computer Science & Engineering Indian Institute of Technology Kharagpur West Bengal India

A nonlinear weighted averaging filter called bilateral filter depends mainly on two parameters. The spatial distance indicates the size, and the intensity distance indicates the contrast of the features to be preserved, with respect to a center pixel. Its simplicity in behavior and implementation makes it easily adaptable to many applications with minor variations. This paper brings out one such variation by using different scales of the image for computing the parametric functions of the filter. Experimental results demonstrate the efficacy of the proposed technique.

关键词： Graphics computer vision Image processing pattern recognition

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Accurate eye centre localisation by means of gradients

Accurate eye centre localisation by means of gradients

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作者： Timm, Fabian Barth, Erhardt Institute for Neuro- and Bioinformatics University of Lübeck Ratzeburger Allee 160 D-23538 Lübeck Germany Pattern Recognition Company GmbH Innovations Campus Lübeck Maria-Goeppert-Strasse 1 D-23562 Lübeck Germany

ISBN: (纸本)9789898425478

The estimation of the eye centres is used in several computer vision applications such as face recognition or eye tracking. Especially for the latter, systems that are remote and rely on available light have become very popular and several methods for accurate eye centre localisation have been proposed. Nevertheless, these methods often fail to accurately estimate the eye centres in difficult scenarios, e.g. low resolution, low contrast, or occlusions. We therefore propose an approach for accurate and robust eye centre localisation by using image gradients. We derive a simple objective function, which only consists of dot products. The maximum of this function corresponds to the location where most gradient vectors intersect and thus to the eye's centre. Although simple, our method is invariant to changes in scale, pose, contrast and variations in illumination. We extensively evaluate our method on the very challenging BioID database for eye centre and iris localisation. Moreover, we compare our method with a wide range of state of the art methods and demonstrate that our method yields a significant improvement regarding both accuracy and robustness.

关键词： Eye tracking

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