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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8836卷 9-16页

作者： Jin, Qiyu Bai, Li Yang, Jie Grama, Ion Liu, Quansheng Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University No. 800 Dongchuan Road Minhang District Shanghai200240 China School of Computer Science University of Nottingham United Kingdom Laboratoire de Mathmatiques de Bretagne Atlantique Université de Bretagne-Sud UMR 6205 Campus de Tohaninic BP 573 Vannes56017 France

A new algorithm for removing random-valued impulse noise is *** use a standardized version of the Rank Ordered Absolute Differences statistic of Garnett et al. [1] to attribute weights to noisy pixels. These weights are then incorporated into the Optimal Weights Filter approach from [2,3] to construct a new filter. Simulation results show that our method performs significantly better than a number of existing techniques. © Springer International Publishing Switzerland 2014.

关键词： Bandpass filters

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Efficient Texture Classification using Short-time Fourier Transform with Spatial Pyramid Matching

Efficient Texture Classification using Short-time Fourier Tr...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Hassan Dawood Hussain Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781479906505

Texture feature extraction plays an important role in texture image classification. In this paper, we have proposed a texture feature extraction method by utilizing the Short-time Fourier Transform to provide local image information, and for the global geometric correspondence we have proposed to use Spatial Pyramid Matching in frequency domain named as Short-time Fourier Transform with Spatial Pyramid Matching (STFT-SPM). The experiments are conducted on standard benchmark datasets for texture classification like Brodatz and KTH-TIPS2-a, shows that STFT-SPM can achieve significant improvement compared to the Local Phase Quantization, Weber local Descriptor and local Binary pattern methods.

关键词： Spatial Pyramid Matching Texture classification Short-time Fourier Transform STFT Fourier Transform Pyramid texture image information textures standardized benchmark Feature extraction

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Remote sensing image enhancement based on relative entropy and fuzzy algorithm

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Journal of Applied Sciences 2013年第13期13卷 2394-2398页

作者： Yang, Bo Jia, Zhen-Hong Qin, Xi-Zhong Yang, Jie Hu, Ying-Jie College of Information Science and Engineering Xinjiang University Urumqi 830046 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1020 New Zealand

An improved maximum between-cluster variance (OTSU) algorithm was proposed to obtain the threshold adaptively in order to overcome the disadvantages of traditional Pal-King algorithm. The algorithm is able to globally enhance the remote sensing images but, for the relevance of neighboring pixel information is not taken into account in the improved algorithm, the visual effect of low contrast images is also not so good. The algorithm in this study can be used to realize the self-adaptive contrast enhancement when the relative entropy is regarded as a criterion. In order to test the enhancement effect of the proposed algorithm for remote sensing image, we choose 50 remote sensing images for test. Experimental results show that a good visual effect is obtained and the clarity, standard deviation has been improved greatly. Therefore, the algorithm is thought to be an effective ways to get better visual effects and more obvious detailed information. © 2013 Asian Network for Scientific Information.

关键词： image enhancement

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AN ACTIVE CONTOUR MODEL BASED ON MULTIPLE BOUNDARY MEASURES

AN ACTIVE CONTOUR MODEL BASED ON MULTIPLE BOUNDARY MEASURES

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IEEE International Conference on image processing

作者： Yu Qiao Lei Zhou Jie Yang Yonghui Gao The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

ISBN: (纸本)9781479923427

Weak boundary contrast, inhomogeneous background and overlapped intensity distributions of the object and background are main causes that may lead to failure of boundary detection for many traditional active contour methods. In this paper, we propose a region-based active contour model to address these problems in both local and global ways. A localized active contour framework is developed, in which two local boundary measures are introduced for the evolution of the level set function. These measures are used to select the boundary candidates for boundary preservation such that the evolution of the contour is guided in a reasonable way. The object boundary is determined by a global boundary measure which evaluates the boundary completeness during the entire evolution process. The experiments demonstrate that our method works well against weak boundary contrast, inhomogeneous background and overlapped intensity distributions.

关键词： Region-based active contour model Level set method Local boundary measures Boundary preservation Global boundary measure contour Boundary boundary layer set method boundary contrast Comet Nucleus Tour Edge detection evolution evolution evolution intensity distribution

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Graph theory based image segmentation

Graph theory based image segmentation

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Congress on image and Signal processing, CISP

作者： Songhao Zhu Xinshuai Zhu Qingqing Luo Institute of Image Processing and Pattern Recognition Nanjing University of Posts and Telecommunications China

ISBN: (纸本)9781479927654

image segmentation is a fundamental process in many image, video, and computer vision applications. It is very essential and critical to image processing and pattern recognition, and determines the quality of final result of analysis and recognition. This paper presents a semi-supervised strategy to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized cut criterion is utilized to segment images into meaningful units. The experimental results conducted on Berkeley image databases and MSRC image databases demonstrate the effectiveness of the proposed strategy.

关键词： image segmentation pattern recognition image databases Graph theory image edge detection Computer vision Approximation algorithms

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Mountain landslide monitoring based on wireless sensor network

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Information Technology Journal 2013年第15期12卷 3357-3362页

作者： Li, Xiaoling Yuan, Jimin School of Computer Science and Technology Chengdu University 610106 Chengdu China University Key Laboratory of Pattern Recognition Intelligent Information Processing 610106 Chengdu China Department Computer Engineering Chengdu Aeronautic Vocational and Technical College Chengdu 610000 China

The study provides a design scheme for the mountain landslide monitoring System based on wireless sensor networks. Different sensors are mainly used to collect data about the water depth in the soil and the sloping angel of the hillside in real-time. After data analysis and processing by monitoring center, the warning information is provided for related departments to take effective measures rapidly to protect people's lives and properties. © 2013 Asian Network for Scientific Information.

关键词： Landforms

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Unscented Kalman filter based on the decoupling of correlated noise

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Journal of Computational Information Systems 2013年第7期9卷 2941-2948页

作者： Hu, Zhentao Qin, Mian Wang, Juan Liu, Yu Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475004 China School of Physics and Electronics Henan University Kaifeng 475004 China

The unscented Kalman filter is an effective nonlinear estimation method for nonlinear system. As we all know that, one of the basic assumptions of unscented Kalman filter implementation is that the measurement noise and process noise is uncorrected, unfortunately, this assumption may be difficult to satisfy in the practical engineering application. Aiming at this decoupling problem of correlation between measurement noise and process noise at the same time in the non-linear system, the system model is modified by rearrange the state transition equation and measurement equation, and a novel unscented Kalman filter based on correlated noise decoupled is proposed in this paper, From the derivation, it is easy to know that the proposed method is equal to standard unscented Kalman filter. Experimental results show that the proposed method outperforms the standard unscented Kalman filter when noises are correlated. Copyright © 2013 Binary Information Press.

关键词： Nonlinear systems

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Research for detection level and production sales management of raisins based on NN and SAS/GIS

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Advance Journal of Food Science and Technology 2013年第8期5卷 1055-1058页

作者： Xiaoling, Li Jimin, Yuan School of Computer Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent information Processing University Chengdu Chengdu 610106 China School of Computer Science and Technology Panzhihua University Pan Zhihua 610106 China

Raisins grade identification in China still relies on photoelectric sorting and manual separation, also, the function of management system for the production, processing, and sales of raisin is traditional and simple. This study presents a processing method on the basis of the Neural Network (NN) and image manipulation. Calculating the length of the long-short-axis, marking the location of it and calculated the 7 parameters, chroma, length, width and etc, and using boundary tracking algorithm, A BP NN was to build and identify the level of raisins through analysis of the external characteristics of raisins. The result of experiment indicates that average recognition rate is higher than 92%. This study took regional economy statistics of Pan Zhihua as an example, designed an system based on regional economy statistic and achieves the analytic function of regional economic statistics by utilizing distributed SAS /GIS to release the data, provide browsing, searching and analytic function of the space data for the users and accomplish data share. Therefore, the method has a great practical value, which can be applied to other. © Maxwell Scientific Organization, 2013.

关键词： processing

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Contour segmentation based on GVF snake model and contourlet transform 1

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Zhang, Xinhong Cai, Kun Zhang, Fan Li, Rui Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China Software School Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China

ISBN: (数字)9783642394829

ISBN: (纸本)9783642394812

A contour segmentation algorithm is proposed based on GVF Snake model and Contourlet transform. Firstly, object contours of images can be obtained based on Contourlet Transform, and those contours will be identified as the initial contour of GVF Snake model. Secondly, GVF Snake model is used to detect the contour edge of human gait motion. Experimental results show that the proposed method can extract the edge feature accurately and efficiently. © 2013 Springer-Verlag.

关键词： Contourlet transform

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3D shape retrieval using point bidirectional features

3D shape retrieval using point bidirectional features

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Hui Chen Jingqi Yan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479905607

In this paper, we describe a novel 3D shape retrieval method based on new features. The features are extracted for 3D points based on a 2D attribute space which consists of two bidirectional 3D shape attributes, one of which along the shape surface direction and the other along the shape content direction perpendicular to the former. We define this features as Point Bidirectional Features (PBFs), which can reflect not only the global shape but also the local content. For simplicity, we choose the geodesic distance (GD) and the shape diameter function (SDF) to construct PBFs. Given a database of 3D shapes and a query shape, the proposed retrieval method adopts a shape similarity measurement based on 3D points matching with PBFs to decide which is the most similar shape from the database. To reduce cost of computation and feature storage, a shape simplification algorithm is integrated into this method. Additionally, a simple but effective point correspondence mechanism with K-Nearest Neighbor (KNN) assignment is designed for this retrieval method. Experimental results demonstrate the effectiveness of the proposed features and method.

关键词： Shape Three-dimensional displays Histograms Solid modeling Computational modeling Feature extraction Databases

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