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检索条件"机构=Image Processing and Pattern Recognition Laboratory"

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Combining the contrast information with LPQ for texture classification

Combining the contrast information with LPQ for texture clas...

引用

International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

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

Texture classification is an important problem in image analysis. A considerable amount of research work has been done for local or global rotation invariant feature extraction for texture classification. Local invariant features contain the spatial information, but usually do not have the contrast information. A new hybrid approach is proposed which considers the contrast information in spatial domain and the phase information in frequency domain of the image. It uses the joint histogram of the two complementary features, local phase quantization (LPQ) and the contrast of the image. Support vector machine is used for classification. The experimental results on standard benchmark datasets for texture classification Brodatz and KTH-TIPS2-a show that the proposed method can achieve significant improvement compared to the LPQ, Gabor filer or local Binary pattern methods.

关键词： Histograms Quantization (signal) Support vector machines Transforms Feature extraction Standards Gabor filters

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Fast Multiple Scattering in Participating Media with Beamlet Decomposition

Fast Multiple Scattering in Participating Media with Beamlet...

引用

International Conference on Computational Intelligence and Security

作者： Yuanlong Wang Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

We propose a fast algorithm which is based on the beam let decomposition for real-time rendering of scenes in participating media with multiple scattering. Firstly, the light source radiation is considered as composed by all particles in the media and each particle radiation is decomposed along different forward directions using the plane decomposition method. Then the multiple scattering radiation of one particle is calculated by the decomposition radiations from its adjacent particles and the light source. Finally, according to the multiple scattering radiation value of each particle, the radiation of the ray which is from viewpoint is calculated using ray marching method, which can be implemented on the graphics processing unit (GPU), and rendering process is highly parallel. The experimental results show that the algorithm can achieve real-time rendering efficiency and enhance the practicality of multiple scattering.

关键词： Scattering Media Rendering (computer graphics) Light sources Absorption Algorithm design and analysis Graphics processing units

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Scene recognition via Combining Information of Neighbors

Scene Recognition via Combining Information of Neighbors

引用

International Conference on Computational Intelligence and Security

作者： Minguang Song Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Recently, spatial principal component analysis of census transform histograms (PACT) was proposed to recognize instance and categories of places or scenes in an image. When combining PACT with Local difference Magnitude Binary pattern (LMBP), a new representation called Local Difference Binary pattern (LDBP) was proposed and performed better. LDBP is based on the comparisons between center pixel and its neighboring pixels. However, the relationship among neighbor pixels is not considered. In this paper we proposed Local Neighbor Binary pattern (LNBP) to utilize the relationship among neighboring pixels. LNBP provides complementary information regarding neighboring pixels for LDBP. We propose to combine LDBP with LNBP, and used a spatial representation for scene recognition. Experiments on two widely used dataset demonstrate the proposed method can improve the performance of recognition.

关键词： Histograms pattern recognition Transforms Computer vision Principal component analysis Conferences image recognition

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Text-independent Speaker Identification Using Fisher Discrimination Dictionary Learning Method

Text-independent Speaker Identification Using Fisher Discrim...

引用

International Conference on Computational Intelligence and Security

作者： Xia Wang Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

In last decades, text-independent speaker recognition is a hot research topic attracted many researchers. In this paper, we proposed to apply the Fisher discrimination dictionary learning method to identify the text-independent speaker recognition. The feature used in classification is the Gaussian Mixture Model super vector. The proposed method is evaluated with public ally available dataset TIMIT. Experimental results show that the proposed method outperforms the Sparse Representation Classifier used for text-independent speaker recognition in both clean and noisy condition.

关键词： Dictionaries Mathematical model Equations Speaker recognition Noise measurement Learning systems pattern recognition

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Combining the contrast information with WLD for texture classification

Combining the contrast information with WLD for texture clas...

引用

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

作者： Hussain Dawood Hassan Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 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： Histograms Feature extraction Pulse width modulation Maximum likelihood estimation Standards pattern recognition Robustness

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Cattle's fur detection based on Gaussian mixture model in complex background: Application of automatic race classification of beef cattle

Cattle's fur detection based on Gaussian mixture model in co...

引用

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

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

Segmentation becomes a difficult task if the objects and background are not homogeneous and having overlapping characteristics. Cattle segmentation from its background is required in several typical applications, such as: the automatic cattle race classification. The cattle's fur detection which is inspired from the human skin detection is investigated in this paper for cattle and background segmentation in automatic beef cattle race classification. The Gaussian mixture model that was used in skin detection has been adopted to model Bali cow and Hybrid Ongole cow in this beef cattle race classification. The RGB color space and two texture descriptors are used as the features set. The addition of texture descriptor has increased the performance of the fur detection and automatic race classification. The GMM performs well but the noise and the complexity of the background lead to misclassification.

关键词： image color analysis Cows Accuracy Skin Feature extraction image segmentation Entropy

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Performance comparison analysis features extraction methods for Batik recognition

Performance comparison analysis features extraction methods ...

引用

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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Combining the Contrast Information with WLD for Texture Classification

Combining the Contrast Information with WLD for Texture Clas...

引用

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

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

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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...

引用

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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Statistical image Upsampling Method Based on CUDA

Statistical Image Upsampling Method Based on CUDA

引用

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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