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IEEE Signal processing and Communications Applications (SIU)

作者： Erdal Yenialp Habil Kalkan Vision Image Processing and Pattern Recognition Laboratory (VIPLAB) Bilgisayar Mühendisliği Bölümü Süleyman Demirel Üniversitesi Isparta Turkey

Segmentation algorithms are widely used in image processing. These methods have different complexity values and the choice of reasonable methods decreases on large images. Especially on the medical images with large size, it may take days to perform segmentation in some methods. However, parallel implementation may eliminate the drawback of these algorithms to some extent. In this study, we propose to implement segmentation algorithms in parallel using Graphical processing Unit. Using the proposed implementation, the computation time of the K-centers, K-means and DBSCAN algorithms were decreases 87, 642 and 2 times, respectively.

关键词： Graphics processing units Clustering algorithms image segmentation Art Software algorithms Computer science

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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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Detection of wide linear structures by fusion of width and gray

Detection of wide linear structures by fusion of width and g...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Anna Zhu Guoyou Wang Ran Wang State Key Laboratory for Multispectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)9781479900145

Lines provide important information in images and line detection is crucial in many applications. Many line features can be used to detect line position while line width (i.e., thickness) is a more structured, higher-level feature compared to edge or other line features. Every point of the wide line structure has its own width in spite of the structure's asymmetry. In this paper, we use the parallel edges to get the line orientation and width. We do not need to know the actual width of the line, but rather recover it to get the region of interest (ROI). Then use a modified OTSU obtaining proper region threshold T to segment the wide line structures. By fusing feature of width and gray, a sequence of tests has been conducted on a variety of image samples obtained from simple natural scene and our experimental results demonstrate the practical and robust of the proposed method.

关键词： image edge detection Estimation Detectors Feature extraction image segmentation Transforms Roads

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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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CROSS-VIEW ACTION recognition VIA TRANSDUCTIVE TRANSFER LEARNING

CROSS-VIEW ACTION RECOGNITION VIA TRANSDUCTIVE TRANSFER LEAR...

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IEEE International Conference on image processing

作者： Jie Qin Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781479923427

Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions. However, the recognition performance deteriorates rapidly when the viewpoint changes. Traditional approaches aim to address the problem by inductive transfer learning, in which target-view samples are manually labeled. In this paper, we present a novel approach for cross-view action recognition based on transduc-tive transfer learning. We address the problem by transferring instances across views. In our settings, both labels of examples from the target view and the corresponding relation between examples from pairwise views are dispensable. Experimental results on the IXMAS multi-view data set demonstrate the effectiveness of our approach, and are comparable to the state of the art.

关键词： action recognition transfer learning transductive SVM Transfer (Psychology) state of the art target view recognition (Psychology) Learning

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SEMI-SUPERVISED LEARNING IN TRAFFIC SCENE SURVEILLANCE BASED ON LABEL-PROPAGATION

SEMI-SUPERVISED LEARNING IN TRAFFIC SCENE SURVEILLANCE BASED...

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IEEE International Conference on image processing

作者： Meng Liang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781479923427

Object classification in traffic scene surveillance has attracted much attention recent years. Traditional classification methods need lots of labeled samples to build a satisfying classifier. However, the acquisition of the labeled samples may cost lots of time and human labor. In this paper, we propose an label-propagation based semi-supervised learning method which uses the information of both labeled and unlabeled samples. Experiment results show that our method outperforms the traditional methods both in accuracy and robustness.

关键词： traffic scene surveillance object classification label propagation semi-supervised learning Semi-supervised Learning Traffic traffic monitoring Classification Methods

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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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Mining top-K Frequent and Flexible pattern from sequences

Mining top-K Frequent and Flexible Pattern from sequences

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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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image segmentation based on visual perception model

Image segmentation based on visual perception model

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2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012

作者： Shao, Shuai Duan, Fuqing Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9789491216008

image segmentation is the basis of image processing and image analysis. However, there are no common method that can be used in natural images, and present methods fail to explain understandings of human's visual system. In this paper, we propose to apply Karklin's visual perception model to extract feature vectors of images, and the features are clustered with K-means method. The results obtained in feature space are projected back to the image space to finish segmentation. A comparison with the Normalized Cuts (Ncut) method is done, and it turns out that proposed method outperform Ncut in texture rich images. © the authors.

关键词： image segmentation

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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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