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International Conference on Electronics, Computer and Computation (ICECCO)

作者： Ali Güneş Habil Kalkan Efkan Durmuş Mehmet Burak Bütükcan Vision Image Processing and Pattern Recognition Laboratory (VIPLAB) S üleyman Demirel University Isparta Turkey Canakkale Onsekiz Mart Universitesi Canakkale Canakkale TR

Figs like other agricultural products may include cancerogenic aflatoxin which is caused by Aspergillus type molds. Under the UV illumination, a large portion of the aflatoxin contaminated figs expose Bright Greenish Yellow Fluorescence (BGYF) in visible light spectrum. Using the fluorescence properties, the contaminated figs are visually detected and manually removed by workers. However, this procedure could not eliminate all the aflatoxin contaminated figs and the UV exposure may cause skin cancer on workers under UV illumination. Besides, the reflectance outside the visible spectrum may include significant information for aflatoxin contamination. In this study, we investigate the NIR reflectance spectroscopy for the detection of aflatoxin contaminated figs and correctly classified the figs with 90% mean accuracy.

关键词： Spectroscopy Reflectivity Fluorescence Lighting Inspection Sugar Contamination

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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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Parallel implementation of segmentation algorithms on graphics processing unit

Parallel implementation of segmentation algorithms on graphi...

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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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AFFINE SOFTASSIGN WITH BIDIRECTIONAL DISTANCE FOR POINT MATCHING

AFFINE SOFTASSIGN WITH BIDIRECTIONAL DISTANCE FOR POINT MATC...

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IEEE International Conference on Image processing

作者： Peng-peng Zhang Sheng-zheng Wang Yu Qiao Jie Yang Yong-hui 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 China 200240 Merchant Marine College Shanghai Maritime University China 200235

ISBN: (纸本)9781479923427

This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.

关键词： affine soft assignment bidirectional distance point matching In-law Affine transformation Bidirectional Affine Registration observational data iterative methods

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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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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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Mountain landslide monitoring based on wireless sensor network

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Information Technology Journal 2013年第15期12卷 3357-3362页

作者： Li, Xiaoling Yuan, Jimin School of Computer Science and Technology Chengdu University 610106 Chengdu China University Key Laboratory of Pattern Recognition Intelligent Information Processing 610106 Chengdu China Department Computer Engineering Chengdu Aeronautic Vocational and Technical College Chengdu 610000 China

The study provides a design scheme for the mountain landslide monitoring System based on wireless sensor networks. Different sensors are mainly used to collect data about the water depth in the soil and the sloping angel of the hillside in real-time. After data analysis and processing by monitoring center, the warning information is provided for related departments to take effective measures rapidly to protect people's lives and properties. © 2013 Asian Network for Scientific Information.

关键词： Landforms

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Photorealistic 3D Mapping of Indoors by RGB-D Scanning Process

Photorealistic 3D Mapping of Indoors by RGB-D Scanning Proce...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Tommi Tykkala Andrew I. Comport Joni-Kristian Kamarainen Machine Vision and Pattern Recognition Laboratory Lappeenranta University of Technology Kouvola Unit Finland CNRS-I3S/University of Nice Sophia-Antipolis France Department of Signal Processing Tampere University of Technology Finland

ISBN: (纸本)9781467363563

In this work, a RGB-D input stream is utilized for GPU-boosted 3D reconstruction of textured indoor environments. The goal is to develop a process which produces standard 3D models from indoors to explore them virtually. Camera motion is tracked in 3D space by registering the current view with a reference view. Depending on the trajectory shape, the reference is either fetched from a concurrently built keyframe model or from a previous RGB-D measurement. Real-time tracking (30Hz) is executed on a low-end GPU, which is possible because structural data is not fused concurrently. After camera poses have been estimated, both trajectory and structure are refined in post-processing. The global point cloud is compressed into a watertight polygon mesh by using Poisson reconstruction method. The Poisson method is well-suited, because it compressed the raw data without introducing multiple geometries and also fills holes efficiently. Holes are typically introduced at occluded regions. Texturing is generated by backprojecting the nearest RGB image onto the mesh. The final model is stored in a standard 3D model format to allow easy user exploration and navigation in virtual 3D environment.

关键词： trajectory three-dimensional displays Photorealistic Three Dimensions INDOORS navigation Sim'eon Denis Poisson

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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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Multi-feature bio-inspired model for scene classification

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Applied Mechanics and Materials 2013年 303-306卷 1569-1572页

作者： Hu, De-Kun Lin, Jie College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province 610106 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9783037856529

A multi-feature bio-inspired model for scene image classification (MFBIM) is presented in this work;it extends the hierarchical feedforward model of the visual cortex. Firstly, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. Then, BPNN assigns the category of an image based on the previous outputs. Experiments show that the model boosts the classification accuracy over the shape based model. Meanwhile, the proposed approach achieves a high accuracy comparable to other reported methods on publicly available color image dataset. © (2013) Trans Tech Publications, Switzerland.

关键词： Computer vision

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