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2012 IEEE 12th International Conference on computer and Information Technology, CIT 2012

作者： Gao, Zunqi Ming, Delie Xiao, Liping Wang, Hai Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China National Laboratory of Aerospace Intelligence Control Technology Beijing Aerospace Automatic Control Institute Beijing China Department of Computer Science and Engineering Pohang University of Science and Technology Pohang Korea Republic of

ISBN: (纸本)9780769548586

The SIFT algorithm had a profound impact on the area of image local feature extraction and computer vision, since its inception. Because of its robustness and anti-interference performance, it has been widely applied in engineering. However, in practical usage of SIFT, there are actually no sufficient feature points that can be extracted to perform the image registration. For tiny scale targets, this situation becomes even worse. Based on the analysis of the scale-space, this paper puts forward a scale-adaptive feature points extraction method (SFPE). SFPE can extract more feature points than traditional SIFT algorithm, especially when the target scale is tiny. Furthermore, a dual-scale based high-precision image registration process (DHIR) is proposed in this paper. In DHIR, a small-scale matching (precise matching) process is performed after the large-scale registration. Experimental results show that the DHIR is more effective to eliminate mismatches than traditional SIFT algorithm. © 2012 IEEE.

关键词： Feature extraction

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RE-RANKING USING COMPRESSION-BASED DISTANCE MEASURE FOR CONTENT-BASED COMMERCIAL PRODUCT IMAGE RETRIEVAL

RE-RANKING USING COMPRESSION-BASED DISTANCE MEASURE FOR CONT...

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IEEE International Conference on Image Processing

作者： Lunshao Chai Zhen Qin Honggang Zhang Jun Guo Christian R. Shelton Pattern Recognition and Intelligence Systems Laboratory Beijing University of Posts and Telecommunications China Computer Science and Engineering Department University of California Riverside USA

With the prevalence of E-Commerce sites such as eBay, Content-based Commercial Product Image Retrieval (CBCPIR) has become an emerging application-oriented field of Content-based Image Retrieval (CBIR). Though a number of traditional CBIR techniques and evaluation criterions have been applied directly or with minor modifications, they tend to neglect one critical factor that greatly affects user experience: users usually care about the exact ranks of the results, especially few top ones, which should share very high similarity with the query image. In this work, we propose a novel two-stage retrieval framework that uses a compression-based re-ranking method and a new subjective retrieval evaluation criterion to address such a problem. More specifically, we extend the state-of-art texture descriptor Campana-Keogh (CK) method from data mining in several aspects and validate the superiority of our framework via extensive experiments and real-world user feedback. We also make our code and CBCPIR dataset publicly available. The number of images of the latter is much larger than current freely accessible ones and better represents real-world commercial product images.

关键词： Transform coding Image color analysis Image coding Image retrieval Educational institutions Data mining Video compression

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Rear lights vehicle detection for collision avoidance

Rear lights vehicle detection for collision avoidance

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Evangelos Skodras George Siogkas Evangelos Dermatas Nikolaos Fakotakis Artificial Intelligence Group Wire Communications Laboratory Department of Electrical and Computer Engineering University of Patras Patras Greece Pattern Recognition Group Wire Communications Laboratory Department of Electrical and Computer Engineering University of Patras Patras Greece

Vehicle detection based on on-board mounted cameras is an integral component of many driver assistance systems aiming at alerting the driver about impending collisions. In this paper an automated algorithm for detection of preceding vehicles is proposed, based on the detection of rear vehicle lights. Unlike many systems which make use of static threshold boundaries for the red color segmentation of rear lights, our method combines color and radial symmetry cues while the threshold is dynamically adapted. The extracted candidate rear lights are morphologically paired in order to define possible areas where vehicles are present. The verification of vehicle presence is then carried out through axial symmetry check. Experimental results that demonstrate the system's high detection rates and robustness even in adverse illumination and weather conditions are finally presented.

关键词： Vehicles Vehicle detection Image color analysis Image edge detection Color Lighting Cameras

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Automated classification of local patches in colon histopathology

Automated classification of local patches in colon histopath...

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International Conference on pattern recognition

作者： Habil Kalkan Marius Nap Robert P.W. Duin Marco Loog Pattern Recognition Laboratory Delft University of Technology Netherlands Department of Computer Engineering Suleyman Demirel University Isparta Turkey Atrium Medical Center Heerlen Netherlands

An automated histology analysis is proposed for classification of local image patches of colon histopathology images into four principle classes: normal, cancer, adenomatous and inflamed classes. Shape features based on stroma, lumen and imperfectly segmented nuclei are combined with texture features for classification. The classification is analyzed under the three scenarios: normal vs. abnormal, cancer vs. non-cancer and four-class classification on a labeled dataset consisting of 2000 patches per class which were collected from 55 different slices. The proposed method achieves 79.28% mean accuracy between normal and abnormal; 87.67% accuracy between cancer and non-cancer and 75.15% between the four classes with equal class priories.

关键词： Cancer Feature extraction Colon Accuracy Shape Image segmentation pattern recognition

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Locating high-density clusters with noisy queries

Locating high-density clusters with noisy queries

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International Conference on pattern recognition

作者： Chen Cao Shifeng Chen Changqing Zou Jianzhuang Liu Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong China

ISBN: (纸本)9781467322164

Semi-supervised learning (SSL) relies on a few labeled samples to explore data's intrinsic structure through pairwise smooth transduction. The performance of SSL mainly depends on two folds: (1) the accuracy of labeled queries, (2) the integrity of manifolds in data distribution. Both of these qualities would be poor in real applications as data often consist of several irrelevant clusters and discrete noise. In this paper we propose a novel framework to simultaneously remove discrete noise and locate the high-density clusters. Experiments demonstrate that our algorithm is quite effective to solve several problems such as non-feedback image re-ranking and image co-segmentation.

关键词： Noise Noise measurement Clustering algorithms Databases Vectors Manifolds Semisupervised learning

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Handwritten and Machine Printed Text Separation in Document Images Using the Bag of Visual Words Paradigm

Handwritten and Machine Printed Text Separation in Document ...

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International Workshop on Frontiers in Handwriting recognition

作者： Konstantinos Zagoris Ioannis Pratikakis Apostolos Antonacopoulos Basilis Gatos Nikos Papamarkos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Greater Manchester UK Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos Athens Greece

In a number of types of documents, ranging from forms to archive documents and books with annotations, machine printed and handwritten text may be present in the same document image, giving rise to significant issues within a digitisation and recognition pipeline. It is therefore necessary to separate the two types of text before applying different recognition methodologies to each. In this paper, a new approach is proposed which strives towards identifying and separating handwritten from machine printed text using the Bag of Visual Words paradigm (BoVW). Initially, blocks of interest are detected in the document image. For each block, a descriptor is calculated based on the BoVW. The final characterization of the blocks as Handwritten, Machine Printed or Noise is made by a Support Vector Machine classifier. The promising performance of the proposed approach is shown by using a consistent evaluation methodology which couples meaningful measures along with a new dataset.

关键词： Visualization Noise Image segmentation Hidden Markov models Gabor filters Handwriting recognition Text recognition

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Multiple-image encryption by compressive holography

Multiple-image encryption by compressive holography

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作者： Di, Hong Zheng, Kangfeng Zhang, Xin Lam, Edmund Y. Kim, Taegeun Kim, You Seok Poon, Ting-Chung Zhou, Changhe Information Security Center Beijing University of Posts and Telecommunications Beijing 100876 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China Imaging Systems Laboratory Department of Electrical and Electronic Engineering University of Hong Kong Pokfulam Road Hong Kong Hong Kong Department of Optical Engineering Sejong University 98 Kunja-dong Kwangjin-gu Seoul 134-747 Korea Republic of Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA 24061 United States Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences P.O. Box 800-211 Shanghai 201800 China

We present multiple-image encryption (MIE) based on compressive holography. In the encryption, a holographic technique is employed to record multiple images simultaneously to form a hologram. The twodimensional Fourier data of the hologram are then compressed by nonuniform sampling, which gives rise to compressive encryption. Decryption of individual images is cast into a minimization problem. The minimization retains the sparsity of recovered images in the wavelet basis. Meanwhile, total variation regularization is used to preserve edges in the reconstruction. Experiments have been conducted using holograms acquired by optical scanning holography as an example. computer simulations of multiple images are subsequently demonstrated to illustrate the feasibility of the MIE scheme. © 2012 Optical Society of America.

关键词： Holograms

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Review of recent patents on cancelable biometrics

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Recent Patents on Electrical engineering 2011年第2期4卷 125-132页

作者： Yang, Kai Du, Eliza Yingzi Pattern Recognition and Biometrics Laboratory Department of Electrical and Computer Engineering Indiana University Purdue University Indianapolis 723 W. Michigan Street SL 160 Indianapolis IN 46202 United States

In general, the biometric patterns of an individual are permanently bound with him/her and it is almost impossible to replace. As a result, once stolen or compromised, the biometric data are either lost forever or are very hard to recover. Thus, it is desirable to secure the original patterns and design a method to ensure their revocability when compromised, which is known as "cancelable biometrics". In this paper, recent patents and related papers on cancelable biometrics are reviewed, including different biometrics encryption algorithms and feature transformation methods. © 2011 Bentham Science Publishers.

关键词： Biometrics

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An Accessibility Assessment Framework for Improving Designers Experience in Web Applications

An Accessibility Assessment Framework for Improving Designer...

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6th International Conference on Universal Access in Human-computer Interaction (UAHCI)/14th International Conference on Human-computer Interaction (HCI)

作者： Oikonomou, Theofanis Kaklanis, Nikolaos Votis, Konstantinos Tzovaras, Dimitrios Informatics and Telematics Institute Thermi-Thessaloniki GR-57001 6th Km Charilaou-Thermi Road Greece Pattern Recognition Laboratory Computer Engineering and Informatics University of Patras Rio Patras Greece Department of Computing University of Surrey Guildford United Kingdom

ISBN: (纸本)9783642216718

The current situation for the accessibility assessment of web applications is encouraging, though not sufficient. Many efforts have been made for the development of various tools that carry out the evaluation of web pages. However, their effectiveness is somehow incomplete. In this work we propose a new framework that has adopted the latest web standard and supports a plethora of assessment configurations to meet the user needs.

关键词： Websites

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Automatic motion-guided video stylization and personalization 11

Automatic motion-guided video stylization and personalizatio...

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19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Cao, Chen Chen, Shifeng Zhang, Wei Tang, Xiaoou Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781450306164

Video stylization transfers a source video into an artistic version while maintaining temporal coherence between adjacent frames. In this paper, we formulate the unsupervised example-based video stylization with Markov random field model. In our algorithm, we implement an improved optical flow algorithm to maintain temporal coherence while improve the accuracy of estimation along motion boundaries. We also extend our algorithm to the application of video personalization, in which human faces keep clear and distinguishable. A series of techniques are fused in video personalization, including face detection and alignment, motion flow, skin detection, and illumination blending. Given a source video and a style template image, our algorithm produces the stylized and/or personalized video(s) automatically. Experimental results demonstrate that our algorithm performs excellently in both video stylization and personalization. Copyright 2011 ACM.

关键词： Face recognition

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