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

作者： Hisyam Fahmi Ary Noviyanto Aniati Murni Arymurthy Image Processing and Pattern Recognition Laboratory Faculty of Computer Science Universitas Indonesia

Segmentation becomes a difficult task if the objects are not homogeneous and have overlapping characteristics. The Graph Cuts methods combined with Gaussian Mixture Model (GMM) for initialization label has been adopted to detect cattle object in an image with complex background. The RGB colors and Gray Level Co-occurrence Matrix (GLCM) textures are used as the features set. This method can robustly segment the cattle beef image from its background. This segmentation method produces the average of accuracy value up to 90%.

关键词： Image segmentation Cows Accuracy Image color analysis Equations Mathematical model Gaussian mixture model

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Efficient Texture Classification using Short-time Fourier Transform with Spatial Pyramid Matching

Efficient Texture Classification using Short-time Fourier Tr...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Hassan Dawood Hussain Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781479906505

Texture feature extraction plays an important role in texture image classification. In this paper, we have proposed a texture feature extraction method by utilizing the Short-time Fourier Transform to provide local image information, and for the global geometric correspondence we have proposed to use Spatial Pyramid Matching in frequency domain named as Short-time Fourier Transform with Spatial Pyramid Matching (STFT-SPM). The experiments are conducted on standard benchmark datasets for texture classification like Brodatz and KTH-TIPS2-a, shows that STFT-SPM can achieve significant improvement compared to the Local Phase Quantization, Weber local Descriptor and local Binary pattern methods.

关键词： Spatial Pyramid Matching Texture classification Short-time Fourier Transform STFT Fourier Transform Pyramid texture image information textures standardized benchmark Feature extraction

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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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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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Mining top-K Frequent and Flexible pattern from sequences

Mining top-K Frequent and Flexible Pattern from sequences

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2013 IEEE Conference Anthology, ANTHOLOGY 2013

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

ISBN: (纸本)9781479916603

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 (MF2P). 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. © 2013 IEEE.

关键词： Bioinformatics

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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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An image compression-encryption algorithm based on 2-D compressive sensing

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Journal of Computational Information Systems 2013年第24期9卷 10057-10064页

作者： Mo, Yan Zhang, Aidi Zheng, Fen Zhou, Nanrun Jiangxi Province Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang 330063 China Department of Electronic Information Engineering Nanchang University Nanchang 330031 China

An image compression-encryption algorithm based on 2-D compressive sensing is proposed, which can accomplish encryption and compression simultaneously. The measurements are performed in two directi-ons and the measurement matrices are constructed as partial Hadamard matrices, which are controlled by chaos map. The proposed algorithm is sensitive to the keys and it can resist various attacks. Simulation results verify the validity and reliability of the proposed algorithm. Copyright © 2013 Binary Information Press.

关键词： Compressed sensing

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Detection of aflatoxin contaminated figs using Near-Infrared (NIR) reflectance spectroscopy

Detection of aflatoxin contaminated figs using Near-Infrared...

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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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