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RIDED-2D: A RULE-BASED INSTANTANEOUS DENOISING AND EDGE DETECTION METHOD FOR 2D RANGE SCAN LINE

INTERNATIONAL JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2011年第6期25卷 807-833页

作者： Wang, Jian Yao, Zhen-Qiang An, Quan-Zhang Zhu, Yao-Jie Zhang, Xue-Ping Gu, Wei-Bin Liang, Xin-Guang Mei, Lin Wu, Jin Shen, Dong-Qing Xin, Yun-Chang Lu, Fang-Fang Shanghai Jiao Tong Univ State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China Minist Publ Secur Res Inst 3 Cyber Phys Syst R&D Ctr Shanghai 201204 Peoples R China Changzhou EGing Photovolta Technol Co Ltd Jintan 213213 Jiangsu Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Mat Laser Proc & Modificat Shanghai 200240 Peoples R China Shanghai Yanfeng Visteon Automot Trim Syst Co Ltd Shanghai 200233 Peoples R China Chongqing Univ Sch Mat Sci & Engn Chongqing 400030 Peoples R China Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200240 Peoples R China

Edge detection is often regarded as a basic step in range image processing by virtue of its crucial effect. The majority of existing edge detection methods cannot satisfy the requirement of efficiency in many industrial applications due to huge computational costs. In this paper, a novel instantaneous method, named RIDED-2D is proposed for denoising and edge detection for 2D scan line in range images. In the method, silhouettes of 2D scan line are classified into eight types by de fining a few new coefficients. Several discriminant criteria on large noise filtering and edge detection are stipulated based on qualitative feature analysis on each type. Selecting some feature point candidates, a practical parameter learning method is provided to determine the threshold set, along with the implementation of an integrated algorithm by merging calculation steps. Because all the coefficients are established based on distances among the points or their ratio, RIDED-2D is inherently invariant to translation and rotation transformations. Furthermore, a forbidden region approach is proposed to eliminate interference of the mixed pixels. Key performances of RIDED-2D are evaluated in detail by including computational complexity, time expenditure, accuracy and stability. The results indicate that RIDED-2D can detect edge points accurately from several real range images, in which large noises and systematic noises are involved, and the total processing time is less than 0.1 millisecond on an ordinary PC platform using the integrated algorithm. Comparing with other state-of-the-art edge detection methods qualitatively, RIDED-2D exhibits a prominent advantage on computational efficiency. Thus, the proposed method qualifies for real-time processing in stringent industrial applications. Besides, another contribution of this paper is to introduce CPU clock counting technique to evaluate the performance of the proposed algorithm, and suggest a convenient and objective way to estimate the

关键词： Instantaneous edge detection real-time image processing laser range finder large noise filtering 3D range image understanding computer vision RIDED

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Rapid reconstruction of small objects on mobile phones

Rapid reconstruction of small objects on mobile phones

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Andreas Hartl Lukas Gruber Clemens Arth Stefan Hauswiesner Dieter Schmalstieg Institute of Computer Graphics and Vision Graz Technical University Austria

Augmented Reality (AR) on mobile phones is receiving more and more attention recently, becoming a popular research topic and an important commercial field. In this paper we present a lightweight method to create coarse 3D models of small-scale objects. The goal is to give the users the possibility to create and maintain AR content themselves without the need for expensive tools and complex interaction. Our algorithm is based on shape-from-silhouette using voxel carving and runs on modern smartphone hardware. 3D models of certain object groups can be generated interactively and instantly. The actual result is visualized continuously using image based rendering methods to inform the user about the actual model quality. Given a suitably accurate model it can further be used for any means of AR and can easily be shared with other users. The usability of our approach is evaluated using modern smartphone hardware (see Figure 1). The advantages are demonstrated using a set of models for playing a board game.

关键词： Solid modeling Computational modeling Three dimensional displays Visualization Hardware Image color analysis Rendering (computer graphics)

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An analysis on the two-phase test sample sparse representation method and an improved method

An analysis on the two-phase test sample sparse representati...

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2011 International conference on Instrumentation,Measurement,computer,Communication and Control (IMCCC2011)(第一届仪器测量、计算机通信与控制国际会议)

作者： Yuwu Lu Dept. of Mathematics of science school Inner Mongol University of TechnologyHohhotInner MongoliaChina

The recently proposed two-phase test sample sparse representation (TPTSR) method makes a great contribution to the field of face *** TPTSR uses a computationally very efficient algorithm,it can obtain a better performance than the well-known sparse representation *** the first phase of TPTSR,the determined M nearest neighbors for the test sample seem not to be optimal in terms of the representation *** other words,it is probably that there exist M training samples whose linear combination has a smaller deviation from the test *** deviation is referred to as representation error of the test *** the smaller the representation error,the higher the accuracy,then it will be possible that one can obtain a better face recognition *** this paper,in order to explore this issue,we propose an improved *** method revises the first phase of TPTSR as a step that uses the global search algorithm to determine the M " optimal " nearest neighbors of the test *** show the representation error and classification accuracy of the improved method and TPTSR by experimental results.

关键词： Face recognition pattern recognition sparse representation transform methods computer vision

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Atousa Torabi Guillaume-Alexandre Bilodeau LITIV Laboratory Department of computer engineering and software engineering École Polytechnique de Montréal Montreal QUE Canada

The robustness of Mutual Information (MI), the most used multimodal dense stereo correspondence measure, is restricted by the size of the matching windows. However, obtaining the appropriately sized MI windows for matching thermal-visible pair of images of multiple people with various poses, clothes, distances to cameras, and different levels of occlusions is quite challenging. In this paper, we propose local self-similarity (LSS) as a multimodal dense stereo correspondence measure. We integrated LSS as a similarity metric with a disparity voting registration method to demonstrate the suitability of LSS for a visible-thermal stereo registration method. We have analyzed comparatively LSS and MI as multimodal correspondence measures and discussed LSS advantages compared to MI. We have also tested our LSS-based registration method in several indoor videos of multiple people and shown that our registration method outperforms the most recent MI-based registration method in the state-of-the-art.

关键词： Bismuth pattern matching Joints Robustness Cameras Humans Layout

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Theory for evidence to detect

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TRAITEMENT DU SIGNAL 2011年第5期28卷 515-545页

作者： Faux, Francis Luthon, Franck Univ Pau & Pays Adour Lab Informat EA3000 IUT Bayonne Pays Basque F-64600 Anglet France

This paper deals with real time face detection and tracking by a video camera. The method is based on a simple and fast initializing stage for learning. The transferable belief model is used to deal with the prior model incompleteness due to the lack of exhaustiveness of the learning stage. The algorithm works in two steps. The detection phase synthesizes an evidential face model by merging basic beliefs elaborated from the Viola and Jones face detector and from colour mass functions. These functions are computed from information sources in a logarithmic colour space. To deal with the colour information dependence in the fusion process, we propose a compromise operator close to the Denoeux cautious rule. As regards the tracking phase, the pignistic probabilities from the face model guarantee the compatibility between the believes and the probability formalism. They are the inputs of a particle filter which ensures face tracking at video rate. The optimal parameter tuning of the evidential model is discussed. © 2011 Lavoisier.

关键词： Cautious rule computer vision Dempster-Shafer Evidence theory Face detection LUX colour space Particle filter pattern recognition Tracking Transferable belief model

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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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International Conference on Image Information Processing

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

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.

关键词： Electrocardiography Feature extraction pattern recognition Information processing Reservoirs Strips

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A Painting Based Technique for Skew Estimation of Scanned Documents

A Painting Based Technique for Skew Estimation of Scanned Do...

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International Conference on Document Analysis and recognition

作者： Alireza Alaei Umapada Pal P. Nagabhushan Fumitaka Kimura Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Japan

In this paper, we propose an efficient skew estimation technique based on Piece-wise Painting Algorithm (PPA) for scanned documents. Here we, at first, employ the PPA on the document image horizontally and vertically. Applying the PPA on both the directions, two painted images (one for horizontally painted and other for vertically painted) are obtained. Next, based on statistical analysis some regions with specific height (width) from horizontally (vertically) painted images are selected and top (left), middle (middle) and bottom (right) points of such selected regions are categorized in 6 separate lists. Utilizing linear regression, a few lines are drawn using the lists of points. A new majority voting approach is also proposed to find the best-fit line amongst all the lines. The skew angle of the document image is estimated from the slope of the best-fit line. The proposed technique was tested extensively on a dataset containing various categories of documents. Experimental results showed that the proposed technique achieved more accurate results than the state-of-the-art methodologies.

关键词： Estimation Painting Fitting Linear regression Text analysis Writing

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A FUZZY IDENTIFICATION METHOD OF CONTOURS BASED ON CHAIN-CODE FEATURES

A FUZZY IDENTIFICATION METHOD OF CONTOURS BASED ON CHAIN-COD...

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第三届全国智能视觉监控学术会议

作者： Qi Dong Guangping Xu Liu Jing Yanbing Xue Hua Zhang Key Laboratory of Intelligence Computing and New Software Technology TianjinChina300384 Key Laboratory of Computer Vision and SystemMinistry of EducationTianjinChina300384 School of Computer and CommunicationTianjin University of TechnologyTianjinChina300384

ISBN: (纸本)9781457718342

The contour analysis and identification are the important aspects in visual surveillance *** paper proposes a fuzzy identification method of ***,according to the description of a contour based on the chain-code method,the proposed method utilizes the statistical features of contours including the chain-code entropy and chain-code space distribution entropies,from which the feature vector of a contour is ***,the method generates the contour pattern from some contour samples and uses the approaching principle to identify a *** our method integrates effectively multiple statistical feathers of its chain-code and employs a fuzzy pattern recognition technique,the experiments show quantitatively that it can achieve good results from various metrics.

关键词： Image Contour Fuzzy pattern Chain Code Object recognition

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Semantic image segmentation using oriented pattern analysis

Semantic image segmentation using oriented pattern analysis

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International Conference on Information, Communications and Signal Processing

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

ISBN: (纸本)9781457700293

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.

关键词： Semantics Image segmentation Coherence Buildings Vectors Image color analysis computer vision

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Edge Saliency Map Detection with Texture Suppression

Edge Saliency Map Detection with Texture Suppression

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International Conference on Image and Graphics (ICIG)

作者： Huanhuan Ao Nenghai Yu

Edge is a basic feature in the field of computing vision. So to find edge saliency map is an indispensable operation for many applications on image processing. In this paper we present a fast algorithm to find edge saliency map for a natural image. The approach integrates three basic edge features: edge gradient value, edge segment length and edge density, and it works well to detect salient region boundaries and to suppress ill edges from texture. An edge saliency map can be used to image segmentation and boundaries detection. Experimental results demonstrate that our algorithm outperforms other edge saliency detection methods. Finally, our algorithm is applied on salient objects segmentation, compared with several state of-the-art salient region detection methods and the results show our work is valuable.

关键词： Image edge detection Image segmentation Visualization Feature extraction computer vision Object segmentation pattern recognition

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