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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Yiren Wang Hassan Dawood Qian Yin Ping Guo the Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China the Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China Computer Science Department Beijing Normal University Beijing China

Automatic image annotation and tagging is necessary for indexing and searching of images using querying a text. It is widely used in search engines like Google, Yahoo, Baidu, etc. Fast image Tagging (FastTag) algorithm is proposed to accelerate image annotation process, while keeping the precision of automatic image annotation results. Feature mapping is used to map image features vectors onto higher dimensional feature space. Feature mapping methods plays an important role in automatic image annotation. In this paper, we have compared 6 kernels, among which four kernels are used in homogeneous feature mapping and two kernels are used in discriminative tree based feature mapping, to investigate which feature mapping performs better for automatic image annotation. The performance of these methods has been analyzed by conducting intensive experiments on three different datasets as used by FastTag algorithm in their experiments. We have found that the homogeneous feature mapping with χ 2 kernel is more suitable when used in FastTag algorithm in terms of precision, recall, FI score and N+ measures, and with a relatively acceptable performance.

关键词： Phase change materials Search engines Kernel Indexing Histograms

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A framework for spatial-variant thresholding of digital subtraction angiography images

A framework for spatial-variant thresholding of digital subt...

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MIPPR 2005: Geospatial Information, Data Mining, and Applications

作者： Sang, Nong Peng, Weixue Li, Heng Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

Vessel segmentation is the base of 3d reconstruction of Digital Subtraction Angiograph (DSA) images. This paper proposes a framework of adaptive local thresholding based on a verification-based approach for vessel segmentation of DSA images. The original DSA image is firstly divided into overlapping subimages according to a priori knowledge of the diameter of vessels. We implement a hypothesis test to determine whether each subimage contains vessels and then choose an optimal threshold respectively for every subimage previously determined to contain vessels, with a secondary verification process to exclude the condition that the subregion only containing the background but misclassified as one containing vessels by the hypothesis test. Finally an overall binarization of the original image is achieved by combining the thresholded subimages. Experiments demonstrate superior performance over global thresholding and some adaptive local thresholding methods.

关键词： Angiography

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Adaptive thresholding of digital subtraction angiography images

Adaptive thresholding of digital subtraction angiography ima...

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MIPPR 2005: image Analysis Techniques

作者： Sang, Nong Li, Heng Peng, Weixue Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in the human body. Blood vessel segmentation is a main problem for 3D vascular reconstruction. In this paper, we propose a new adaptive thresholding method for the segmentation of DSA images. Each pixel of the DSA images is declared to be a vessel/background point with regard to a threshold and a few local characteristic limits depending on some information contained in the pixel neighborhood window. The size of the neighborhood window is set according to a priori knowledge of the diameter of vessels to make sure that each window contains the background definitely. Some experiments on cerebral DSA images are given, which show that our proposed method yields better results than global thresholding methods and some other local thresholding methods do.

关键词： image analysis

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3D reconstruction of the coronary tree from two X-ray angiographic views

3D reconstruction of the coronary tree from two X-ray angiog...

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Medical Imaging 2006: image processing

作者： Sang, Nong Peng, Weixue Li, Heng Zhang, Zhen Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)0819464236

In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is based on the model of generalized cylinders, which are generated by sweeping a two-dimensional cross section along an axis in three-dimensional space. We restrict the cross section to be circular and always perpendicular to the tangent of the axis. Firstly, the vascular centerlines of the X-ray angiography images on both projections are semiautomatically extracted by multiscale vessel tracking using Gabor filters, and the radius of the coronary are also acquired simultaneously. Secondly, the relative geometry of the two projections is determined by the gantry information and 2D matching is realized through the epipolar geometry and the consistency of the vessels. Thirdly, we determine the three-dimensional (3D) coordinates of the identified object points from the image coordinates of the matched points and the calculated imaging system geometry. Finally, we link the consequent cross sections which are processed according to the radius and the direction information to obtain the 3D structure of the artery. The proposed 3D reconstruction method is validated on real data and is shown to perform robustly and accurately in the presence of noise.

关键词： image reconstruction

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Fast recovery of piled deformable objects using superquadrics

Fast recovery of piled deformable objects using superquadric...

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24th German Association for pattern recognition Symposium, DAGM 2002

作者： Katsoulas, Dimitrios Jaklič, Aleš Institute for Pattern Recognition and Image Processing University of Freiburg Georges-Koehler-Allee 52 FreiburgD-79110 Germany Computer Vision Laboratory University of Ljubljana Tržaška cesta 25 LjubljanaSI-1000 Slovenia

ISBN: (纸本)354044209X

Fast robotic unloading of piled deformable box-like objects (e.g. box-like sacks), is undoubtedly of great importance to the industry. Existing systems although fast, can only deal with layered, neatly placed configurations of such objects. In this paper we discuss an approach which deals with both neatly placed and jumbled configurations of objects. We use a time of flight laser sensor mounted on the hand of a robot for data acquisition. Target objects are modeled with globally deformed superquadrics. Object vertices are detected and superquadric seeds are placed at these vertices. Seed refinement via region growing results in accurate object recovery. Our system exhibits a plethora of advantages the most important of which its speed. Experiments demonstrate that our system can be used for object unloading in real time, when a multi-processor computer is employed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Data acquisition

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Shadow detection using regression tree fields with paired regions

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Journal of Computational Information Systems 2013年第11期9卷 4309-4317页

作者： Tao, Wei Zhou, Yue Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

In this paper, we try to deal with the problem of shadow detection from static images and video sequences. In instead to considering individual regions separately, we use relative illumination conditions between segmented regions and perform pair-wise classification based on such information. We use Regression Tree Fields to solve the labeling of shadow and non-shadow regions. And we use continuous value to describe the possibility of the shadow of the region. We evaluate our method on static images and a series of video sequences. © 2013 by Binary Information Press.

关键词： Classification (of information)

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A paddy growth stages classification using MODIS remote sensing images with balanced branches support vector machines

A paddy growth stages classification using MODIS remote sens...

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International Conference on Advanced Computer Science and Information System (ICACSIS)

作者： Sidik Mulyono Mohamad Ivan Fanany T. Basaruddin Laboratory of Pattern Recognition Image Processing and CBIR Faculty of Computer Science Universitas Indonesia Indonesia

This paper presents a paddy growth stages classification using MODIS remote sensing images with support vector machines (SVMs). We collected the paddy growth stages data samples from a series of MODIS mages acquired from March to July 2012 along paddy field area only. The data are collected based on growth stages phenology of paddy using spectral profile which consists of at least 9 classes for growth stages and 2 classes for dominated soil and cloud. We apply SVMs to build a binary classifier for each class with one against all strategy of multiclass approach. One important issue needed to address is unbalanced prior probability that should be solved by each SVM. In this study, we evaluate the effectiveness of balanced branches strategy that is applied to one against all SVMs learning. Our results shows that the balanced branches strategy does improves in average around 10% classification accuracy during training and validation, and in average around 50% during testing.

关键词： MODIS Soil Support vector machines Hyperspectral imaging Training

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An Improved Random Sampling LDA for Face recognition

An Improved Random Sampling LDA for Face Recognition

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Congress on image and Signal processing, CISP

作者： Yunfei Jiang Xinyu Chen Ping Guo Hanqing Lu Laboratory of Image Processing and Pattern Recognition Beijing Normal University Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Linear Discriminant Analysis (LDA) is one of the most used feature extraction techniques for face recognition. However, it often suffers from the small sample size problem with high dimension setting. Random Subspace Method (RSM) is a popular combining technique to improve weak classifier. Nevertheless, it remains a problem how to construct an optimal random subspace for discriminant analysis. In this paper, we propose an improved random sampling LDA for face recognition. Firstly, AdaBoost is adopted to select Gabor feature and remove redundant information. Secondly, in the selected Gabor feature space, we combine principal component analysis and RSM approaches to construct optimal random subspaces for LDA. After that, direct LDA (D-LDA) and R-LDA is applied in each subspace, respectively. Final results are obtained by combining all the LDA classifiers using a fusion rule. Experiments with both the ORL and FERET face databases demonstrate the effectiveness of our proposed method, and it shows promising results compared with previous approaches.

关键词： Sampling methods Linear discriminant analysis Face recognition Principal component analysis pattern recognition Laboratories Feature extraction Scattering Signal processing image sampling

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Terrain Simplification Research in Augmented Scene Modeling

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Journal of China University of Geosciences 2001年第4期12卷 351-355页

作者： Ming Delie You Kefei Tian Jinwen Liu Jian State Key laboratory for image processing and Intelligent Control, Institute for pattern recognition and Artificial Intelligence , Huazhong University of Science and Technology , Wuhan 430074 Wang Guangju State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

关键词： augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy.

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Robust stereo on multiple resolutions

Robust stereo on multiple resolutions

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13th International Conference on pattern recognition, ICPR 1996

作者： Menard, Christian Leonardis, Aleš Department for Pattern Recognition and Image Processing Technical University Vienna Treitlstraße 3/1832 3A-1040 Vienna Austria University of Ljubljana Faculty of Computer and Information Science Computer Vision Laboratory Ljubljana Slovenia

ISBN: (纸本)081867282X

Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent postprocessing stages. In this paper we present a modification of the standard area-based correlation approach so that it can tolerate a significant number of outliers. The approach exhibits a robust behavior not only in the presence of mismatches but also in the case of depth discontinuities. The confidence measure of the correlation and the number of outliers provide two complementary sources of information which, when implemented in a multiresolution framework, result in a robust and efficient method. We present the results of this approach on a number of synthetic and real images. © 1996 IEEE.

关键词： Stereo image processing

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