Chuanbo Chen

Huazhong University of Science and Technology, Wu-han-shih, Hubei, China

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Publications (33)1.52 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a novel label propagation (LP) method is presented, called the manifold adaptive label propagation (MALP) method, which is to extend original LP by integrating sparse representation constraint into regularization framework of LP method. Similar to most LP, first of all, MALP also finds graph edges from given data and gives weights to the graph edges. Our goal is to find graph weights matrix adaptively. The key advantage of our approach is that MALP simultaneously finds graph weights matrix and predicts the label of unlabeled data. This paper also derives efficient algorithm to solve the proposed problem. Extensions of our MALP in kernel space and robust version are presented. The proposed method has been applied to the problem of semi-supervised face clustering using the well-known ORL, Yale, extended YaleB, and PIE datasets. Our experimental evaluations show the effectiveness of our method.
    IEEE transactions on cybernetics. 09/2014;
  • Computers & Electrical Engineering 08/2014; · 0.99 Impact Factor
  • Chuanbo Chen, Guangwei Wang, Mudar Sarem
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    ABSTRACT: In this paper, a non-symmetry and anti-packing image representation model (NAM) has been proposed. NAM is a hierarchical image representation method and it aims to provide faster operations and less storage requirement. By taking a rectangle sub-pattern, for example, we describe the idea of NAM and its encoding algorithm.In addition, an approach for adaptive area histogram equalization for image contrast enhancement based on a NAM image is presented. The contrast enhancement approach is designed to meet the NAM image representation and it can be duplicated with faster operation. The complexity analysis and the experimental results show that the NAM based algorithm for image contrast enhancement is faster and more effective than that based on matrix image.
    Computers & Electrical Engineering. 01/2011; 37:669-680.
  • Guangwei Wang, Chuanbo Chen
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    ABSTRACT: In this paper, we propose a non-symmetry and anti-packing image representation model (NAM). NAM is a hierarchical image representation method and its aim is less data amount and faster operation. By taking a rectangle sub-pattern for example, we describe the idea of NAM. In addition, an approach for adaptive area histogram equalization image contrast enhancement based on a NAM image is presented. The contrast enhancement approach is designed to meet the NAM image representation and can be fast implemented. In this work, the contrast enhancement method combines dynamic range modification and adaptive area histogram equalization to improve the visualization of images. Complexity analysis and experimental results show that the NAM based algorithm for image contrast enhancement is faster and more effective than that based on matrix image.
    Image and Signal Processing (CISP), 2010 3rd International Congress on; 11/2010
  • Xiaobing Pei, ShaoHong Fang, ChuanBo Chen
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    ABSTRACT: Non-negative matrix factorization (NMF) is useful in finding basis information of non-negative data. It is a new dimension reduction method. In this paper, a Group Locality Preserving Orthogonal Nonnegative Matrix Factorization (GLPONMF) is investigated. The idea is to extend the NMF method in order to extract basis vectors for each sample class and at the same time enforce the locality preserving orthogonal properties. Finally, the experimental evaluation has been given.
    Seventh International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010, 10-12 August 2010, Yantai, Shandong, China; 01/2010
  • Guangwei Wang, Chuanbo Chen
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    ABSTRACT: In this paper, we present a non-symmetry and anti-packing object pattern representation model (NAM) for object detection. A set of distinctive sub-patterns (object parts) is constructed from a set of sample images of the object class; object pattern are then represented using sub-patterns, together with spatial relations observed among the sub-patterns. Many feature descriptors can be used to describe these sub-patterns.The NAM model codes the global geometry of object category, and the local feature descriptor of sub-patterns deal with the local variation of object. By using Edge Direction Histogram (EDH) features to describe local sub-pattern contour shape within an image, we found that richer shape information is helpful in improving recognition performance. Based on this representation, several learning classifiers are used to detect instances of the object class in a new image. The experimental results on a variety of categories demonstrate that our approach provides successful detection of the object within the image.
    01/2010;
  • Guangwei Wang, Chuanbo Chen, Kang Chen
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    ABSTRACT: In this paper, we propose a non-symmetry and anti-packing image representation model (NAM). NAM is a hierarchical image representation method and its aim is less data amount and faster operation. By taking a rectangle sub-pattern for example, we describe the idea of NAM. In this work, based on block-wise LS linear predictor method, a gray-coded bit-plane binary image NAM representation method is presented to compress the error image. The compression performance has been further improved. Experimental results show that our compression scheme is clearly better from data compression point of view than other methods.
    Network Infrastructure and Digital Content, 2010 2nd IEEE International Conference on; 01/2010
  • Wei Huang, Chuanbo Chen, M. Sarem
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    ABSTRACT: Although the quadtree has many merits in image representation and image processing, its compactness is impaired by the excessive emphasis on the symmetry of segmentations. In this paper, a lossless gray level image representation, titled overlapped rectangle image representation (ORIR), is presented. The ORIR has removed the constraint of the symmetric segmentations and is capable of coding some detached pixels by using a single rectangle. These characteristics have made the ORIR a highly compact representation. The theoretical analyses and the experimental results in this paper show that the ORIR is greatly superior to the linear quadtree in the aspect of the memory efficiency.
    Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on; 01/2009
  • Mudar Sarem, Yunping Zheng, Chuanbo Chen
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    ABSTRACT: With the rapid development of mobile communication systems, demands for the transmission of multimedia information are increasing day by day. The effective transmission of images can be increased by getting smaller image file that is obtained by compression. However, image quality is often sacrificed in the compression process. Therefore, there is a need to represent images with less data storage without sacrificing the image quality. In this paper, inspired by the concept of the packing problem, we present a new Non-symmetry and Anti-packing Model with Rectangles (NAMR) for lossy and lossless image representation in order to represent the pattern more effectively and flexiblely. Also, in this paper, we propose an algorithm of NAMR and analyze the data amount of this algorithm. The theoretical analyses and experimental results presented in this paper show that when the representation method of NAMR is compared with that of the popular linear quadtree, not only can the former reduce the data storage much more effectively than the latter in lossless case, but also the former has a better reconstruction quality than the latter in lossy case.
    J. Mobile Multimedia. 01/2009; 5:125-139.
  • Shaohong Fang, Chuanbo Chen, Yunping Zheng
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    ABSTRACT: Image representation is an important issue in computer graphics, computer vision, robotics, image processing and pattern recognition. In this paper, we proposed an improved color image representation method by using the direct non-symmetry and anti-packing model with triangles and rectangles (DNAMTR). Also, we propose an algorithm of the DNAMTR for color images and analyze the total data amount of the algorithm. By comparing the representation algorithm of the DNAMTR with those of the latest direct non-symmetry and anti-packing model (DNAM) and the popular linear quadtree, the experimental results presented in this paper show that the former can greatly reduce the numbers of subpatterns or nodes and simultaneously save the data storage much more effectively than the latter.
    First IITA International Joint Conference on Artificial Intelligence, Hainan Island, China, 25-26 April 2009; 01/2009
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    Yunping Zheng, Chuanbo Chen, Sarem Mudar
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    ABSTRACT: A representation method using the non-symmetry and anti-packing model (NAM) for data compression of binary images is presented. The NAM representation algorithm is compared with the popular linear quadtree and run length encoding algorithms. Theoretical and experimental results show that the algorithm has a higher compression ratio for both lossy and lossless cases of binary images and better reconstructed quality for the lossy case.
    Tsinghua Science & Technology 01/2009; 14(1):139-145.
  • Xueli Wu, Chuanbo Chen, Mudar Sarem, Wei Huang
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    ABSTRACT: The nonsymmetry and antipacking pattern representation model (NAM), inspired by the concept of the packing problem, uses a set of subpatterns to represent an original pattern. The NAM is a promising method for image representation because of its ability to focus on the interesting subsets of an image. In this paper, we develop a new method for gray-scale image representation based on NAM, called NAM-structured plane decomposition (NAMPD), in which each subpattern is associated with a rectangular region in the image. The luminance function of pixels in this region is approximated by an oblique plane model. Then, we propose a new and fast edge detection algorithm based on NAMPD. The theoretical analyses and experimental results presented in this paper show that the edge detection algorithm using NAMPD performs faster than the classical ones because it permits the execution of operations on subpatterns instead of pixels.
    Geo-spatial Information Science 01/2009; 12(4):281-288.
  • Wei Huang, Fan Xiong, Chuanbo Chen, Mudar Sarem
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    ABSTRACT: Zernike moments (ZMs) have been widely used in pattern recognition and image analysis due to their merits of near-zero information redundancy and rotation invariance. However, the discrete sampling error introduced by state-of-the-art algorithms degrades their rotation invariance. In this paper, a novel algorithm for computing the accurate ZMs of binary images is presented. The new algorithm is based on non-symmetry anti-packing image representation (NAIR) and it computes the accurate ZMs of the whole image by summing up the ZMs of all rectangular regions without introducing the discrete sampling error. The experimental results in this paper show that the NAIR-based algorithm for accurate ZMs is faster than the state-of-the-art accurate algorithms.
    01/2009;
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    ABSTRACT: In this paper, we propose a new Non-symmetry and Anti-packing Model (NAM) representation method for gray image. By describing the NAM and Gray-Coded Bit-Plane Decomposition (GC-BPD), a novel NAM-based representation algorithm for gray image is presented. The theoretical analyses and experimental results show that the NAM-based representation method can reduce the data storage much more effectively than the linear quadtree-based representation method and is a better method to represent the gray image. The method is a new research area and it is valuable for the theoretical research and potential practical values such as decreasing the storage room, quickening the process procedure, matching pattern, and so on.
    01/2009;
  • Yunping Zheng, Chuanbo Chen, M. Sarem
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    ABSTRACT: In this paper, inspired by the concepts of the triangle and the rectangle packing problems, we present an improved gray image representation method based on binary-bit plane decomposition by using the non-symmetry and anti-packing pattern representation model with triangles and Rectangles (BPD-based NAMTR). Also, we propose a novel representation algorithm of BPD-based NAMTR for gray images and analyze the total data amount of the algorithm. By comparing the algorithm of BPD-based NAMTR with those of BPD-based NAM and the popular linear quadtree, the theoretical and experimental results presented in this paper show that the former can reduce the data storage much more effectively than the latter, and it is a better method to represent gray images. The gray image representation method of BPD-based NAMTR is valuable for the theoretical research and potential business foregrounds such as reducing storage space, increasing transmission speed, improving pattern match efficiency, and so on.
    Natural Computation, 2008. ICNC '08. Fourth International Conference on; 11/2008
  • Yunping Zheng, Chuanbo Chen, Mudar Sarem
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    ABSTRACT: In this paper, we propose a novel algorithm using the NAMK (Non-symmetry and Anti-packing pattern representation Model with K-lines) for the binary image representation. By comparing the algorithm using the NAMK with that using the popular linear quadtree, the theoretical and experimental results presented in this paper show that the former can reduce the data storage much more effectively than the latter and it is a better method to represent the binary image. The algorithm using the NAMK for the binary image representation presented in this paper is valuable for the theoretical research and potential business foregrounds such as decreasing the storage space, increasing the transmission speed, quickening the process procedure, and so forth.
    Image and Signal Processing, 2008. CISP '08. Congress on; 06/2008
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    ABSTRACT: Linear quadtree is a popular image representation method due to its convenient imaging procedure. However, the excessive emphasis on the symmetry of segmentation, i.e. dividing repeatedly a square into four equal sub-squares, makes linear quadtree not an optimal representation. In this paper, a no-loss image representation, referred to as Overlapped Rectangle Image Representation (ORIR), is presented to support fast image operations such as Legendre moments computation. The ORIR doesn’t importune the symmetry of segmentation, and it is capable of representing, by using an identical rectangle, the information of the pixels which are not even adjacent to each other in the sense of 4-neighbor and 8-neighbor. Hence, compared with the linear quadtree, the ORIR significantly reduces the number of rectangles required to represent an image. Based on the ORIR, an algorithm for exact Legendre moments computation is presented. The theoretical analysis and the experimental results show that the ORIR-based algorithm for exact Legendre moments computation is faster than the conventional exact algorithms.
    Geo-spatial Information Science 01/2008; 11(4):294-301.
  • Yunping Zheng, Chuanbo Chen, Mudar Sarem
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    ABSTRACT: Although the triangle non-symmetry and anti-packing model (TNAM) representation for gray images is an effective image representation method, there is still much space left for optimization. In this paper, inspired by the optimization idea of the packing problem, we proposed an improved algorithm for gray image representation using the non-symmetry and anti-packing model with triangles and rectangles (NAMTR). By comparing the representation algorithm of the NAMTR with those of the TNAM and the popular linear quadtree, theoretical and experimental results presented in this paper show that the former can greatly reduce the number of sub-patterns or nodes and simultaneously save the data storage much more effectively than the latter, and therefore it is a better method to represent gray images. Representation method of the NAMTR, as envisaged in this paper, shows a very strong promise, and it is valuable for further theoretical research and potential business foreground, such as reducing storage space, increasing transmission speed and improving pattern match efficiency.
    Frontiers of Computer Science in China 01/2008; 2:431-437. · 0.27 Impact Factor
  • Wei Huang, Chuanbo Chen, Mudar Sarem
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    ABSTRACT: Geometric moments have been widely used in image processing and pattern recognition. However, there are still no algorithms to compute the exact geometric moments of gray level images. In this paper, a novel image presentation method, named overlapped rectangle image representation (ORIR), is firstly presented, and then, based on ORIR, an effective algorithm for computing the exact geometric moments is presented as well. The new algorithm replaces the double integrals on two-dimensional space with the single summation on ORIR list without introducing the discrete sampling error. The experimental results in this paper show that the moment values computed by the presented algorithm match the theoretical values very well.
    PACIIA 2008, Volume 2, 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 19-20 December 2008, Wuhan, China; 01/2008
  • Chuanbo Chen, Yunping Zheng, Mudar Sarem
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    ABSTRACT: The representation methods of the hierarchical data structures have been widely applied in many important fields, such as computer visualization, robotics, computer graphics, image processing, and pattern recognition. Since these methods put too much emphasis upon the symmetry of segmentation, they are not the optimal representation methods. In this paper, we present a Direct Non-symmetry and Anti-packing Model (DNAM) for color images. Also, we propose a novel algorithm of the DNAM for color images and analyze the data amount of the proposed algorithm. By taking a rectangle subpattern for example, we implement the proposed algorithm and make a comparison with the algorithm of the popular linear quadtree. The theoretical and experimental results presented in this paper show that our proposed algorithm can reduce the data storage much more effectively than that of the linear quadtree and it is a better method to represent color images.
    International Conference on Natural Computation. 01/2008; 5:347-351.