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Shadow detection using regression tree fields with paired regions

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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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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Incremental tensor principal component analysis for image recognition

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Advanced Materials Research 2013年 710卷 584-588页

作者： Zhao, Wei Dong Liu, Chang Yan, Tao College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province Chengdu 610106 China

ISBN: (纸本)9783037857205

Aiming at the disadvantages of the traditional off-line vector-based learning algorithm, this paper proposes a kind of Incremental Tensor Principal Component Analysis (ITPCA) algorithm. It represents an image as a tensor data and processes incremental principal component analysis learning based on update-SVD technique. On the one hand, the proposed algorithm is helpful to preserve the structure information of the image. On the other hand, it solves the training problem for new samples. The experiments on handwritten numeral recognition have demonstrated that the algorithm has achieved better performance than traditional vector-based Incremental Principal Component Analysis (IPCA) and Multi-linear Principal Component Analysis (MPCA) algorithms. © (2013) Trans Tech Publications, Switzerland.

关键词： Principal component analysis

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DNA sequence recognition based on the Markov model

DNA sequence recognition based on the Markov model

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Junyan Zhang Chenhui Yang Information Science and Technology College Chengdu University Chengdu China Key Laboratory of Pattern Recognition and Intelligent Chengdu University Chengdu China

ISBN: (纸本)9781479927623

DNA sequences recognition is a key problem in bioinformatics and biomedical informatics. In this paper, we solve this problem by use of the probability method and metric instead of traditional frequency metric because the characters in DNA alphabet set meet the Markov properties. For this purpose, transition probabilities, transition matrixes, and log odds ratios are defined. And then, we put forward our sequence recognition algorithm based on the Markov model (SRM), which has better performance on time complexity than some sequence alignment algorithms in the same field. The results of the contrast experiments show that our SRM algorithm can recognize DNA sequences correctly and effectively without any ambiguities.

关键词： DNA Markov processes Mathematical model Time complexity Algorithm design and analysis Probability

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Incremental tensor discriminant analysis for image detection

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Advanced Materials Research 2013年 710卷 579-583页

作者： Yan, Tao Liu, Chang Zhao, Wei Dong College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province Chengdu 610106 China

ISBN: (纸本)9783037857205

In order to settle incremental learning and preserve the space information of images, this paper proposes an incremental tensor discriminant analysis for facial image detection. The proposed algorithm employs tensor representation to preserve the structure information and introduces the incremental learning to solve the on-line learning for new added samples. The experiments have shown that our method achieves better classification performance and reduces the computational cost effectively compared with other algorithms. © (2013) Trans Tech Publications, Switzerland.

关键词： Discriminant analysis

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pattern Matching with Wildcard Gaps Based on Cross List

Pattern Matching with Wildcard Gaps Based on Cross List

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International Symposium on Computational Intelligence and Design, ISCID

作者： Junyan Zhang Chenhui Yang Information Science and Technology College Chengdu University Chengdu China Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University Chengdu China

pattern matching is a fundamental application text retrieval, string query, biological sequence analysis, etc. Therefore, the effective algorithm performing this kind of matching is in great need. In this paper, the wildcard is defines to match any one character in a sequence. Multiple wildcards form a gap. The length of a flexible gap is arbitrary. We design CLPM algorithm by use of cross list index structure to realize pattern matching with flexible wildcard gaps. The preprocessing algorithm is designed to initialize cross list so as to reduce searching space. In CLPM algorithm, the effective intervals is defined and computed based on the start positions of each sub pattern in each string, which help to obtain matching result set. Moreover, the approximate pattern matching is converted to short extract pattern matching. The contrast experiments are done based on DBLP tile data set. The results show that CLMP algorithm has better performance in the same fields.

关键词： pattern matching Indexes Silicon Algorithm design and analysis Approximation algorithms Presses Educational institutions

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Audio Fingerprinting Based on N-grams

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第10期6卷 361-368页

作者： Wang, Qiang Guo, Zhiyuan Liu, Gang Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

In this paper, we present a novel audio fingerprinting method based on N-grams, which can quickly identify a segment of audio even when the audio signals are seriously distorted. We make use of N peaks in spectrum to form the audio fingerprint, which accelerates the retrieval speed greatly. We take advantage of the initial robust peaks to calculate the similarity between candidates and the input audio, which improves the retrieval accuracy significantly. The effectiveness of the N-gram method was evaluated on a music database of 10,000 songs. Experimental results show that the proposed approach outperforms two state-of-the-art algorithms (Shazam and Philips Robust Hash) in both effectiveness (in terms of retrieval accuracy) and efficiency (in terms of average retrieval time).

关键词： Music

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Mining top-K Frequent and Flexible pattern from sequences

Mining top-K Frequent and Flexible Pattern from sequences

引用

IEEE Conference Anthology

作者： Zhang Junyan Min Fan University Key Laboratory of Pattern Recognition and Intelligent information Processing Chengdu Sichuan Province China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequency, under which the Apriori property holds. We define a pattern mining problem called Ming top-K Frequent patterns (MFP), where gaps are mined instead of specified. Compared with existing problems, MFP does not require any domain knowledge of the user. However, theoretical analysis and experimental results show that MFP favors inflexible patterns. We then define another problem where the flexibility threshold of each gap is specified by the user. The problem is called Mining top-K Frequent and Flexible patterns (MF 2 P). We develop algorithm with polynomial complexities for both problems. patterns can grow from both sides. Some interesting biological patterns mined by our algorithms are discussed.

关键词： constraints pattern mining sequence wildcard gap

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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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ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODING FOR ABNORMALITY DETECTION

ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODI...

引用

IEEE International Conference on Image Processing

作者： Sheng Han Ruiqing Fu Suzhen Wang Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong

ISBN: (纸本)9781479923427

This paper focuses mainly on adaptive dictionary updating and abnormality detection via weighted space coding in video surveillance. Generally, abnormality analysis conducted on a large amount of video data is very complicated, time-consuming and time-variant. However, our dictionary is very efficient at following up on shifted contents in video and abandoning old inactive information in time. The adaptability characteristic also helps reduce the dictionary's size to a small scale, since it only needs to keep recent or active information. We also introduce a simple, but effective, judgement criterion for abnormal detection based on sparse coding over weighted bases. Because of the condensed dictionary and the simplified judgment criterion, our algorithm performs online learning and online detection with a high speed and a high accuracy in various scenes.

关键词： Dictionary Learning Adaptive Learning Sparse Coding Abnormality Detection Sparse coding anomaly detection video data Dictionaries as Topic video monitoring

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