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Conventional mammographic image generation method with increased calcification sensitivity based on dual-energy

12th International Workshop on Breast Imaging, IWDM 2014

作者： Chen, Xi Mou, Xuanqin Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi China

ISBN: (纸本)9783319078861

The visualization of calcifications could be obscured in mammograms because of overlapping of tissue structures. Dual-energy digital mammography (DEDM) can generate tissue-subtracted image for improving the detectability of breast calcifications, but the mass information is missing. This paper proposes a conventional mammographic image generation method with increased calcification sensitivity based on DEDM. Firstly, a conventional mammographic image is generated with low-energy and high-energy images based on multi-scale decomposition and reconstruction. Secondly, the tissue-subtracted "calcification image" is generated using a nonlinear inverse mapping function with calcification pixels marked. Finally, the density values of the marked calcification pixels in the reconstructed mammographic image are increased for better visualization. Preliminary results show that the proposed DEDM method can generate both calcification and conventional mammogram-like images and the calcification sensitivity is increased. The CNR of calcifications of 50% glandular ratio has been increased from 2.75 to 9.32. © 2014 Springer International Publishing.

关键词： Visualization

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Repetitive shapes detection using affine invariant constraints

Repetitive shapes detection using affine invariant constrain...

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2014 International Conference on Communication Technology and Application, CTA 2014

作者： Yang, Z.H. Dong, P. Institute of Image Processing and Pattern Recognition North China University of Technology Beijing China

ISBN: (纸本)9781845649302

This paper presents a novel approach for finding more accurate feature pairs which is not only invariant to affine transformation, but also deals with images with repetitive shapes. First, the more accurate and robust homographic transformation between different views could be calculated through bi-directional matching and appropriate selection of threshold. Second, an affine geometric property, ratios of areas of corresponding triangles are affine invariant, is used to obtain more feature pairs based on the first step. Experiments demonstrate that the proposed method outperforms the state-of-art ASIFT in the number of correct feature pairs and matching accuracy among images with repetitive patterns. © 2014 WIT Press.

关键词： Affine invariance ASIFT Feature points image matching Repetitive shapes

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Relative ordering learning based on weighted sparse representation for age estimation

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Journal of Information and Computational Science 2014年第14期11卷 4877-4888页

作者： Wang, Shengzheng Yang, Jie Merchant Marine College Shanghai Maritime University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

Age estimation has received extensively interest in computer vision field due to its wide applications, i.e. human behavior analysis, video content recognition, etc. Hence, many classification and regression approaches were widely used to estimate human age, and obtained the basically acceptable results, but the relative relationships of age groups have not been exploited in previous methods. Recently, much work proposed to use various ranking-based learning techniques to exploit the relative ordering information. This paper presents a novel relative ordering learning algorithm based on weighted sparse representation to advance the accuracy of age estimation. The age estimation problem is decomposed into a series of relative age ordering sub-problems, and the relative ordering learning of each sub-problem is performed by using weighted sparse representation. Thus, the human age is inferred by aggregating all relative comparison results. The greatest advantage is that the weighted value can be embedded into the age estimator, and also can be dynamically updated in term of the distributions of the training data. The proposed approach is validated in extensively used aging database FG-NET by comparing it with some existing state-of-the-art methods. The experimental results show that the proposed approach outperforms other methods in all cases, and can effectively solve the imbalance and inconsistency of the training data. 1548-7741/Copyright © 2014 Binary Information Press

关键词： Learning algorithms

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A Robust CPD Approach Based on Shape Context 33

A Robust CPD Approach Based on Shape Context

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第三十三届中国控制会议

作者： YANG Yawen ZHANG Peng Peng QIAO Yu YANG Jie WANG Sheng Zheng The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong University Merchant Marine College Shanghai Maritime University

ISBN: (纸本)9781479947249

Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.

关键词： CPD,Shape context,image registration,Point matching

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EBR analysis of digital image watermarking

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2014年 255卷 11-18页

作者： Zhang, Fan Zhang, Xinhong College of Computer and Information Engineering Henan University Kaifeng475001 China Institute of Image Processing and Pattern Recognition Henan University Kaifeng475001 China Software School Henan University Kaifeng475001 China

ISBN: (纸本)9788132217589

An error bit rate (EBR) analysis of digital image watermarking is proposed based on information theory. This work researches how to embed a large number of watermark information in the same time maintaining a low error probability or researches the relationship between watermark payload capacity and EBR. The EBR of watermarking will drop with the decrease in watermark payload capacity. When payload capacity is less than channel capacity, the EBR will keep in a lower level. © Springer India 2014.

关键词： Bit error rate

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Visual tracking based on weighted subspace reconstruction error

Visual tracking based on weighted subspace reconstruction er...

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作者： Zhou, Tao Zhang, Junhao Xie, Kai Yang, Jie He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Faculty of Engineering and Information Technology University of Technology Sydney Australia

ISBN: (纸本)9781479957514

It is a challenging task to develop an effective and robust visual tracking method due to factors such as pose variation, illumination change, occlusion, and motion blur. In this paper, a novel tracking algorithm based on weighted subspace reconstruction error is proposed. We first compute the discriminative weights by sparse construction error with template dictionary consisted of positive and negative samples, and then confidence map for candidates is computed through subspace reconstruction error. Finally, the location of the target object is estimated by maximizing the decision map which is combined discriminative weights and subspace reconstruction error. Furthermore, we use the new evaluation criterion to verify the robustness of the current tracking result, which can reduce the accumulated error effectively. Experimental results on some challenging video sequences show that the proposed algorithm performs favorably against seven state-of-the-art methods in terms of accuracy and robustness. © 2014 IEEE.

关键词： Errors

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Posterior distribution learning (PDL): A novel supervised learning framework

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8834卷 86-94页

作者： Tu, Enmei Yang, Jie Jia, Zhenghong Kasabov, Nicola Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Information Science and Engineering Xinjiang University Urumqi830046 China The Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

In order to obtain a robust supervised model with good generalization ability, traditional supervised learning method has to be trained with sufficient well labeled and uniformly distributed samples. However, in many real applications, the cost of labeled samples is generally very expensive. How to make use of ample easily available unlabeled samples to remedy the insufficiency of labeled samples to train a supervised model is of great interest and practical significance. In this paper we propose a new supervised learning framework, Posterior Distribution Learning (PDL), which could train a robust supervised model with very a few labeled samples by including those unlabeled samples into training stage. Experimental results on both synthetic and real world data sets are presented to demonstrate the effectiveness of the proposed framework. © Springer International Publishing Switzerland 2014.

关键词： Supervised learning

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Online learning of multi-feature weights for robust object tracking

Online learning of multi-feature weights for robust object t...

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IEEE International Conference on image processing

作者： Tao Zhou Harish Bhaskar Kai Xie Jie Yang Xiangjian He Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Dept. of Elec. & Comp. Engg. Khalifa Univ. of Science Technology and Research Abu Dhabi U.A.E Faculty of Engineering and Information Technology University of Technology Sydney Australia

Sparse Representation based Classification (SRC) and its potential in object tracking have been explored in recent years. However, the trade-off between the discriminative ability of the overly emphasized sparse representation and the lack of insight on correlation of visual information has raised questions over the general applicability of such methods in object tracking. In addition, the need for the optimization of a series of l 1 -regularized least square norm, increases the computational complexity thereby limiting their usage in real-time applications. In this paper, a novel approach to robust object tracking is proposed. First, the variations in the appearance of the tracked target is modelled using PCA basis vectors, and further, a l 2 -regularized least square method is used to solve the proposed representation model. In order to improve the robustness of feature representation in object tracking applications, weights are associated with multiple trackers; each formulated using a different feature, and adapted via an online learning scheme. Finally, a decision fusion criterion is imposed to generate an optimized output through the weighted combination of different tracking results. Experiments on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to thirteen other state-of-the-art baselines.

关键词： Target tracking Robustness Object tracking Lighting Clutter Computed tomography Visualization

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A Robust Method for High-Accuracy Microbe Identification Based on image processing

A Robust Method for High-Accuracy Microbe Identification Bas...

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2014 IEEE International Conference on Progress in Informatics and Computing

作者： Mingqi Cao Yuncai Liu Shanghai JiaoTong University Institute of Image Processing and Pattern Recognition

We present a novel fast method based on computer vision toidentify microbe. The proposed method is simple but absolutely effective. It combines approximate parallel light source and industrial camera, toautomatically accomplish the bacteria identification and monitor the growing states of bacteria during the progress of a drug sensitive test. Based on this method, the color information and turbidity information, which reflect the primary information of drug sensitive tests, can be obtained fast, while processing efficiency can be as high as hundreds of milliseconds per frame. The performance of our method is significantly accurate and robust.

关键词： microbe identification drug sensitive test localization color feature turbidity feature

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Accurate Computation of Fingerprint Intrinsic images with PDE-Based Regularization

Accurate Computation of Fingerprint Intrinsic Images with PD...

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7th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2012

作者： Li, Mingyan Chen, Xiaoguang College of Sciences Beijing Forestry University 100083 Beijing China Institute of Image Processing and Pattern Recognition College of Sciences North China University of Technology 100083 Beijing China

The intrinsic images of fingerprint, such as orientation field and frequency map, represent the particular and basic characteristics of fingerprint ridge/valley patterns, and play a key role in feature extraction and matching of the fingerprint recognition system. In this paper, a novel algorithm is presented for accurate computation of fingerprint intrinsic images with PDE-based regularization technique. First, the coarse orientation field is estimated using general gradient-based method, and the frequency map is estimated by Fourier spectrum analysis of the projected curve of local window. Then, to measure the reliability of the intrinsic images, the quality map is computed based on the gray-scale intensity and local structural information. Finally, accurate orientation field and frequency map are reconstructed with PDE-based regularization of nonlinear diffusion filtering which is controlled by the quality-based diffusivity. Experimental results illustrated the efficiency of the proposed approach. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Spectrum analysis

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