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2012 IEEE International Conference on Computer Science and Automation Engineering（CSAE 2012）

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

A considerable amount of research work has been done for texture classification using local or global feature extraction methods. Inspired by Weber's Law, a simple and robust Weber Local Descriptor (WLD) is a recently developed for local feature extraction. This WLD method did not consider the contrast information. In order to improve texture classification accuracy, we propose a hybrid approach that combines the WLD with contrast information in this paper. It utilizes the histogram of two complementary features WLD and the image variance calculated with the Probability Weighted Moments. Support vector machine is used for classification. The comparison of the proposed method with state of art methods like local binary pattern and WLD is experimental investigated on two publically available dataset, named as Brodatz and KTH-TIPS2-a. Results show that our proposed method outperforms over the state of art methods for texture classification.

关键词： Texture classification Weber Local Descriptor Probability Weighted Moments Support vector machine Contrast information

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Performance comparison analysis features extraction methods for Batik recognition

Performance comparison analysis features extraction methods ...

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

作者： Ida Nurhaida Ruli Manurung Aniati Murni Arymurthy Laboratory of Pattern Recognition and Image Processing Faculty of Computer Science University of Indonesia Indonesia

Batik, as a cultural heritage from Indonesia, has a lot of motifs based on certain patterns. This paper discusses feature extraction methods for the recognition of batik motifs in digital images. In this study, the use of several feature extraction methods have been compared in terms of their performance with several scenarios for testing level accuracy. The methods include Gray Level Co-occurrence Matrices (GLCM), Canny Edge Detection, and Gabor filters. The experimental results show that the use of GLCM features has performed the best with a classification accuracy reaching 80%.

关键词： Gabor filters Image edge detection Accuracy Noise Filter banks Testing

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A paddy growth stages classification using MODIS remote sensing images with balanced branches support vector machines

A paddy growth stages classification using MODIS remote sens...

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

作者： Sidik Mulyono Mohamad Ivan Fanany T. Basaruddin Laboratory of Pattern Recognition Image Processing and CBIR Faculty of Computer Science Universitas Indonesia Indonesia

This paper presents a paddy growth stages classification using MODIS remote sensing images with support vector machines (SVMs). We collected the paddy growth stages data samples from a series of MODIS mages acquired from March to July 2012 along paddy field area only. The data are collected based on growth stages phenology of paddy using spectral profile which consists of at least 9 classes for growth stages and 2 classes for dominated soil and cloud. We apply SVMs to build a binary classifier for each class with one against all strategy of multiclass approach. One important issue needed to address is unbalanced prior probability that should be solved by each SVM. In this study, we evaluate the effectiveness of balanced branches strategy that is applied to one against all SVMs learning. Our results shows that the balanced branches strategy does improves in average around 10% classification accuracy during training and validation, and in average around 50% during testing.

关键词： MODIS Soil Support vector machines Hyperspectral imaging Training

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An improved method of identification based on thermal palm vein image 1

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Wang, Ran Wang, Guoyou Chen, Zhong Liu, Jianguo Shi, Yu National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Hongshan District 430074 Wuhan Hubei Province China

ISBN: (数字)9783642344817

ISBN: (纸本)9783642344800

Biological characteristics based on face, fingerprint and iris images have been extensively studied and used for the identification in the past few decades. As a new-born method, thermal palm vein pattern is gathering more and more attention all over the world. An improved method of identification based on thermal palm vein image is presented in the paper. Five steps are needed to have a person verified: 1) acquisition of infrared palm vein image;2) detection of ROI (region of interest);3) enhancement of the palm vein image;4) features extraction of the palm vein patterns;5) matching the features between the real palm vein and sample data. Experiments have been carried out on 178 different images and 176 images of them are correctly recognized with two in failure. Experiments show the detection rate is satisfied. © 2012 Springer-Verlag.

关键词： Image enhancement

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Statistical Image Upsampling Method Based on CUDA

Statistical Image Upsampling Method Based on CUDA

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International Conference on Computational Intelligence and Security

作者： Xin Zheng Qingqing Xu Peipei Pan Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing P.R. China

In many application fields, an appropriate high-quality fast image upsampling method is required. Although many interpolation-based upsampling methods have been proposed, the quality of result images is not satisfactory. Some of them are very fast, but produce poor quality images, the others can produce high quality images, but the methods in them are slow. In our paper, we proposed a fast statistical image upsampling method based on CUDA, it can obtain high quality images based on reducing the input resolution-grids dependency artifacts. Thus, we can rebuild low resolution images' sharp edges fast and get high-quality upsampled images in real time. We have applied this method in the multi-resolution texture generation of large scale terrain rendering. Experiments prove that our method can receive ideal effects in real time.

关键词： Graphics processing units Mathematical model Image edge detection Image resolution Markov processes Standards Computational modeling

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Image Completion with Automatic Structure Propagation

Image Completion with Automatic Structure Propagation

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International Conference on Computational Intelligence and Security

作者： Peipei Pan Xin Zheng Qingqing Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing P.R. China

In this paper, we propose a novel approach for image completion with automatic structure propagation. This method integrates two stages: Firstly, it extends the salient structure lines from the known regions to the unknown by following a local self-similarity assumption on natural images. Then guided by the structure information, it restores the missing region by patch-based texture synthesis. Experiment results demonstrate a better effect of our method than that of the previous patch-based texture synthesis image completion algorithm.

关键词： Image edge detection Image segmentation Image reconstruction Image resolution Filling Image restoration Sun

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Research on scene infrared image simulation

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第4期6卷 77-86页

作者： Zou, Lamei Zhang, Tianxu Yang, Weidong Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan China

Vega has been widely used in the Virtual Reality field. Its infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to the complex scene. This article deeps into the scene's IR simulation method based on Vega. We design and realize a real time scene IR image simulation system in this article. We quantitatively define the scene as a simple and complex scene according to the scene range and whether it includes Digital Elevation Model (DEM)/Digital Surface Model (DSM) data. For the simple scene, we directly process IR image simulation according to the Vega general IR simulation process. While for the complex scene, we propose an IR image simulation method based on image classification and automatic texture material mapping technique. At the aspect of image classification, we develop a coarse to fine K-means clustering method based on the consistency of image color for color image classification and an additional Support Vector Machine (SVM) classification method based on texture features for gray level image classification. The method was tested on different scene's IR simulation. Experimental results show that the proposed approach can achieve better applicability and greater efficiency than the popular Vega IR simulation method.

关键词： Image classification

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Perceptually weighted Non-negative Matrix Factorization for blind single-channel music source separation

Perceptually weighted Non-negative Matrix Factorization for ...

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International Conference on pattern recognition

作者： S. Kırbız B. Gunsel Multimedia Signal Processing and Pattern Recognition Laboratory Department of Electronics and Communications Engineering Technical University Maslak Istanbul Turkey

We propose a blind single-channel musical source separation method that improves perceptual quality of the separated sources. It uses the advantages of subspace learning based on Non-negative Matrix Factor 2-D Deconvolution (NMF2D). To improve the perceptual quality of separation, we propose a weighted divergence type cost function for the optimization that adopts the auditory model defined in ITU-R BS.1387 into the source separation. It is shown that the proposed perceptually weighted NMF2D scheme efficiently clusters the bases of subspace representation corresponding to notes generated by single instruments. Source separation performance has been reported on musical mixtures resulting an improvement in perceptual quality measures.

关键词： Source separation Spectrogram Time frequency analysis Instruments Humans Time domain analysis Computational complexity

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Multi-sensor measurement adaptive filtering algorithm in measurement uncertainty

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Journal of Information and Computational Science 2012年第4期9卷 843-851页

作者： Hu, Zhentao Fu, Chunling Liu, Xianxing Laboratory of Image Processing and Pattern Recognition Henan University Kaifeng 475004 China Basic Experiment Teaching Center Henan University Kaifeng 475004 China

The reliable estimation of system state in multi-sensor uncertainty is always the hot and knotty issue of nonlinear filtering theory. Aiming to the reasonable utilization of measurement information, a novel multi-sensor measurement adaptive filtering algorithm is proposed in this paper. Firstly, Combining with the construction of measurement likelihood and maximize principle, the equivalent measurement are affirmed. Next, the selection and fusion of measurement without disturbance influence are accomplished by the introduction of statistic distance among the measurements, which can realize the optimization of equivalent measurement to some extend. The new method improves the adverse influence of disturbance in multi-sensor information fusion process, and retains the litter computational complexity relative to the distributed fusion structure. The theoretical analysis and experimental results show the efficiency of the proposed algorithm. Copyright © 2012 Binary Information Press.

关键词： Extended Kalman filters

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Optimal stopping condition for iterative deconvolution method by the measurement of image texture

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第15期6卷 109-119页

作者： Wang, Ze Yan, Luxin Jin, Mingzhi State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The non-regularized iterative image restoration algorithms have been widely investigated in the literature. In this work, we focus on a common issue of non-regularized iterative methods, the stopping condition. A no-reference criterion of optimal stopping condition for non-regularized iterative deconvolution called Total Local Binary patterns (TLBP), which is based on the measurement of varying image texture during the deblurring procedure, is proposed. The metric utilizes the minimum of TLBP that is computed according to the LBP map of the blurred image to obtain the optimal restored image. We applied the Richardson-Lucy (RL) method to test the blurred version of the synthetic images and real images in experiments. Deconvolution experiments for Gaussian and out-offocus blur validate the effectiveness of the proposed method.

关键词： Image reconstruction

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