检索结果-内蒙古大学图书馆

Graph-based semi-supervised learning with local binary patterns for holistic object categorization

EXPERT SYSTEMS WITH APPLICATIONS 2014年第17期41卷 7744-7753页

作者： Dornaika, F. Bosaghzadeh, A. Salmane, H. Ruichek, Y. Univ Basque Country UPV EHU San Sebastian 20018 Spain Basque Fdn Sci Ikerbasque Bilbao Spain UTBM IRTES SET F-90010 Belfort France

In this paper, we develop a new efficient graph construction algorithm that is useful for many learning tasks. Unlike the main stream for graph construction, our proposed data self-representativeness approach simultaneously estimates the graph structure and its edge weights through sample coding. Compared with the recent e, graph based on sparse coding, our proposed objective function has an analytical solution (based on self-representativeness of data) and thus is more efficient. This paper has two main contributions. Firstly, we introduce a principled Two Phase Weighted Regularized Least Square graph construction method. Secondly, the obtained data graph is used, in a semi-supervised context, in order to categorize detected objects in outdoor and indoor scenes using local binary patterns as image descriptors. In many previous works, LBP descriptors (histograms) were used as feature vectors for object detection and recognition. However, our work exploits them in order to construct adaptive graphs using a self-representativeness coding. The experiments show that the proposed method can outperform competing methods. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Graph-based semi-supervised learning Graph-based label propagation local binary patterns Holistic object classification Outdoor scenes Indoor scenes

来源：评论

学校读者我要写书评

暂无评论

General rotation-invariant local binary patterns operator with application to blood vessel detection in retinal images

引用

PATTERN ANALYSIS AND APPLICATIONS 2014年第1期17卷 69-81页

作者： Fathi, Abdolhossein Naghsh-Nilchi, Ahmad Reza Univ Isfahan Dept Comp Engn Esfahan Iran

The local binary patterns (LBP) operator is a powerful multi-resolution micro-texture descriptor, which can be applied to many image-processing applications. However, existing LBP operators cannot use the information of non-uniform patterns efficiently. This paper presents a general extension of LBP operator to extract all uniform and non-uniform pattern types by using suitable rotation-invariant labeling scheme. Since the proposed LBP operator can extract all micro-texture structures, we combined it with artificial neural networks (ANN) to present a new supervised technique for automatic blood vessel enhancement and detection. The thin and thick blood vessels are detected by applying proper top-hat transform and length filtering on the enhanced blood vessels. The performance of the proposed method is evaluated on manually labeled images of the publicly available DRIVE and STARE databases and compared with several state-of-the-art approaches. The obtained results show the high accuracy of the proposed method on detecting thin and thick blood vessels.

关键词： local binary patterns Texture descriptor Retinal image segmentation Blood vessel detection

来源：评论

学校读者我要写书评

暂无评论

Study on local Gabor binary patterns for face representation and recognition 9

Study on local Gabor binary patterns for face representation...

引用

9th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Pattern Recognition and Computer Vision

作者： Ge, Wei Han, Chunling Quan, Wei Changchun Univ Sci & Technol Inst Elect & Informat Engn Weixing Rd 7089 Changchun Peoples R China

ISBN: (纸本)9781510600546

More recently, local binary patterns(LBP) has received much attention in face representation and recognition. The original LBP operator could describe the spatial structure information, which are the variety edge or variety angle features of local facial images essentially, they are important factors of classify different faces. But the scale and orientation of the edge features include more detail information which could be used to classify different persons efficiently, while original LBP operator could not to extract the information. In this paper, based on the introduction of original LBP-based facial representation and recognition, the histogram sequences of local Gabor binary patterns are used to representation facial image. Principal Component Analysis (PCA) method is used to classification the histogram sequences, which have been converted to vectors. Recognition experimental results show that the method we used in this paper increases nearly 6% than the classification performance of original LBP operator.

关键词： local binary patterns face representation face recognition Gabor filter histogram sequence principal component analysis classification local Gabor binary pattern

来源：评论

学校读者我要写书评

暂无评论

Eye Blink Detection Using local binary patterns

Eye Blink Detection Using Local Binary Patterns

引用

International Conference on Multimedia Computing and Systems (ICMCS)

作者： Malik, Krystyna Smolka, Bogdan Silesian Tech Univ Dept Automat Control Akad 16 Str PL-44100 Gliwice Poland

ISBN: (纸本)9781479938247

In the paper a novel approach to the problem of eye blink detection in video sequences is proposed. The introduced method is utilizing the technique of local binary patterns (LBP), which enables to build a descriptor capturing the features of the current eye state. In the initial step, the histogram of LBP describing the open eye is constructed and afterwards it serves as a template, which is compared with the histogram of the LBP of subsequent frames. The eye blinks are detected as sharp peaks of the dissimilarity between the template and the histogram of the current frame. The efficiency of the proposed eye blink detector has been compared with the state-of-the-art approaches using two video databases. The analysis of the results shows that the proposed technique effectiveness is superior to the existing methods of eye blink detection.

关键词： eye blink detection local binary patterns video analysis

来源：评论

学校读者我要写书评

暂无评论

Glaucoma Detection based on local binary patterns in Fundus Photographs

Glaucoma Detection based on Local Binary Patterns in Fundus ...

引用

Conference on Medical Imaging - Computer-Aided Diagnosis

作者： Ali, Maya Alsheh Hurtut, Thomas Faucon, Timothee Cheriet, Farida Univ Paris 05 LIPADE Paris France Ecole Polytechn Montral Montreal PQ Canada CDIAGNOS inc Montreal PQ Canada

ISBN: (纸本)9780819498281

Glaucoma, a group of diseases that lead to optic neuropathy, is one of the most common reasons for blindness worldwide. Glaucoma rarely causes symptoms until the later stages of the disease. Early detection of glaucoma is very important to prevent visual loss since optic nerve damages cannot be reversed. To detect glaucoma, purely data-driven techniques have advantages, especially when the disease characteristics are complex and when precise image-based measurements are difficult to obtain. In this paper, we present our preliminary study for glaucoma detection using an automatic method based on local texture features extracted from fundus photographs. It implements the completed modeling of local binary patterns to capture representative texture features from the whole image. A local region is represented by three operators: its central pixel (LBPC) and its local differences as two complementary components, the sign (which is the classical LBP) and the magnitude (LBPM). An image texture is finally described by both the distribution of LBP and the joint-distribution of LBPM and LBPC. Our images are then classified using a nearest-neighbor method with a leave-one-out validation strategy. On a sample set of 41 fundus images (13 glaucomatous, 28 non-glaucomatous), our method achieves 95.1 % success rate with a specificity of 92.3 % and a sensitivity of 96.4 %. This study proposes a reproducible glaucoma detection process that could be used in a low-priced medical screening, thus avoiding the inter-experts variability issue.

关键词： Glaucoma texture features computer aided diagnosis local binary patterns Fundus photographs

来源：评论

学校读者我要写书评

暂无评论

GENDER CLASSIFICATION WITH local ZERNIKE MOMENTS AND local binary patterns

GENDER CLASSIFICATION WITH LOCAL ZERNIKE MOMENTS AND LOCAL B...

引用

22nd IEEE Signal Processing and Communications Applications Conference (SIU)

作者： Coban, Bahtiyar Samet Gokmen, Muhittin Istanbul Tech Univ Bilgisayar Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781479948741

This study provides a new feature extraction method to gender classification. local Zernike Moments is a method used for face recognition and proved that it is more successful than Gabor or LBP representations. In this study, LZM method is used for gender classification on FERET and LFW databases and demonstrated that it is more successful than LBP method on both databases. In the light of analysis done on the test results of these two methods, a new hybrid feature method built by combining LZM and LBP features is created and the performance rates are achieved as 99.57% for FERET and 97.71% for LFW databases by using Support Vector Machines (SVM) classifier. This indicates the superiority of the proposed method over suggested methods for gender classification on both controlled environment and real-world images.

关键词： local Zernike Moments local binary patterns Gender Classification Support Vector Machines FERET LFW

来源：评论

学校读者我要写书评

暂无评论

One Dimensional Multi-Resolution local binary patterns Features (1DMRLBP) for Regular Electrocardiogram (ECG) Waveform Detection 19

One Dimensional Multi-Resolution Local Binary Patterns Featu...

引用

19th International Conference on Digital Signal Processing (DSP)

作者： Louis, Wael Hatzinakos, Dimitrios Venetsanopoulos, Anastasios Univ Toronto Edward S Rogers Sr Dept Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)9781479946129

Feeding a noisy signal to a biometric system degrades its performance. Hence, signal quality measure is used to avoid passing irregular signals to subsequent systems such as biometric systems. To tackle this issue, 1DMRLBP features, which are 1 dimensional signal feature extraction (inspired by the 2 dimensional image local binary patterns) is proposed. 1DMRLBP with its multi-resolution capability captures local and global signal characteristics;and with its histogram extraction avoids segments misalignment and reduces the number of features. Also with some modifications, 1DMRLBP accommodates the problem of unknown amplitude of a signal. 1DMRLBP achieves 91% performance rate in distinguishing between regular and irregular ECG waveforms. MATLAB code and more information are available at ***/similar to wlouis/1DMRLBP.

关键词： Biomedical signal detection ECG detection local binary patterns Signal quality measure

来源：评论

学校读者我要写书评

暂无评论

Features Representation by Multiple local binary patterns for Facial Expression Recognition 11

Features Representation by Multiple Local Binary Patterns fo...

引用

11th World Congress on Intelligent Control and Automation

作者： Wang, Li Li, Ruifeng Wang, Ke Harbin Inst Technol Dept State Key Lab Robot & Syst Harbin Heilongjiang Pr Peoples R China

ISBN: (纸本)9781479958252

To recognize expressions conveniently and effectively, an enhanced feature representation method is proposed for facial expression recognition. local binary pattern histogram Fourier (HF-LBP) features is used to represent facial expression features. Multiple HF-LBP features are extracted to form recognition vectors for facial expression recognition in the approach, which include sign and magnitude LBP in the completed LBP scheme with multiple radii and different size neighborhoods to achieve enough features. It represents images from different scales and directions in the local neighborhood by overall considerations from the aspect. K-nearest neighborhoods classifier is applied for expression recognition after representing facial features using HF-MLBP. Comparisons are made with other extension LBP operators to evaluate the approach. The experimental results show that our method has good performance in facial expression recognition.

关键词： local binary patterns feature Fourier transform multiple features facial expression recognition

来源：评论

学校读者我要写书评

暂无评论

Edge-based Foreground Detection with Higher Order Derivative local binary patterns for Low-resolution Video Processing

Edge-based Foreground Detection with Higher Order Derivative...

引用

9th International Conference on Computer Vision Theory and Applications (VISAPP)

作者： Deboeverie, Francis Allebosch, Gianni Van Haerenborgh, Dirk Veelaert, Peter Philips, Wilfried UGent iMinds Dept Telecommun & Informat Proc Image Proc & Interpretat St Pietersnieuwstr 41 B-9000 Ghent Belgium

ISBN: (纸本)9789897581335

Foreground segmentation is an important task in many computer vision applications and a commonly used approach to separate foreground objects from the background. Extremely low-resolution foreground segmentation, e.g. on video with resolution of 30x30 pixels, requires modifications of traditional high-resolution methods. In this paper, we adapt a texture-based foreground segmentation algorithm based on local binary patterns (LBPs) into an edge-based method for low-resolution video processing. The edge information in the background model is introduced by a novel LBP strategy with higher order derivatives. Therefore, we propose two new LBP operators. Similar to the gradient operator and the Laplacian operator, the edge information is obtained by the magnitudes of First Order Derivative LBPs (FOD-LBPs) and the signs of Second Order Derivative LBPs (SOD-LBPs). Posterior to background subtraction, foreground corresponds to edges on moving objects. The method is implemented and tested on low-resolution images produced by monochromatic smart sensors. In the presence of illumination changes, the edge-based method outperforms texture-based foreground segmentation at low resolutions. In this work, we demonstrate that edge information becomes more relevant than texture information when the image resolution scales down.

关键词： Foreground Segmentation Edge Detection local binary patterns Low-resolution Video Processing

来源：评论

学校读者我要写书评

暂无评论

Facial Image Clustering in Stereo Videos Using local binary patterns and Double Spectral Analysis 5

Facial Image Clustering in Stereo Videos Using Local Binary ...

引用

IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Orfanidis, Georgios Tefas, Anastasios Nikolaidis, Nikos Pitas, Ioannis Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

ISBN: (纸本)9781479945184

In this work we propose the use of local binary patterns in combination with double spectral analysis for facial image clustering applied to 3D (stereoscopic) videos. Double spectral clustering involves the fusion of two well known algorithms: Normalized cuts and spectral clustering in order to improve the clustering performance. The use of local binary patterns upon selected fiducial points on the facial images proved to be a good choice for describing images. The framework is applied on 3D videos and makes use of the additional information deriving from the existence of two channels, left and right for further improving the clustering results.

关键词： face recognition pattern clustering stereo image processing video signal processing 3D videos double spectral analysis facial image clustering local binary patterns stereo videos stereoscopic videos Clustering algorithms Face Feature extraction Laplace equations Three-dimensional displays Trajectory Videos Videotapes Stereo image processing three-dimensional displays Cluster Analysis Laplace's equation Video signal processing Face Face Clustering algorithms binary pattern Feature extraction Facial Recognition trajectory

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：