检索结果-内蒙古大学图书馆

2013 International Conference on Advances in Information Technology(ICAIT 2013)

作者： Hua Lu Mingqiang Yang Xianye Ben Jianzhong Miao School of Information Science and Engineering Shandong University

As the local binary pattern operator discards a lot of important texture features, a new texture operator is proposed in this paper, the merge local binary patterns(MLBP)By using the absolute differences between P neighbors of the LBP operator and the central pixel, an subtraction operator(SLBP) like LBP is proposed for the robust of the featureBy combining original LBP operator and SLBP operator into joint distribution, texture classification will improve significantlyExtensive experiments in CMU-PIE and AR face database present the advantages of the MLBP method over other methods.

关键词： local binary patterns Average Merge local binary patterns

来源：评论

学校读者我要写书评

暂无评论

FACE DETECTION IN MOBILE PHONES USING CO-OCCURRENCE OF ADJACENT local binary patterns

FACE DETECTION IN MOBILE PHONES USING CO-OCCURRENCE OF ADJAC...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Jeaff Wang Dohyoung Lee K.N. Plataniotis Multimedia Lab The Edward S. Rogers Department of Electrical and Computer Engineering University of Toronto

ISBN: (纸本)9781479903573

This paper investigates a novel combination of Co-occurrence of adjacent local binary patterns histogram and local binary patterns feature extraction methods for face detection in mobile phone applications. In particular, Co-occurrence of adjacent local binary patterns histogram feature extraction provides exceptionally high discriminative power in face/non-face classification and hence is used to ensure the high accuracy of the proposed face detector. local binary patterns feature extraction has low computation complexity and is thus used to reduce the overall processing speed. In the conducted face detection experiments, the proposed face detector yields comparable or better performance as well as faster computation speed than the existing best methods.

关键词： Frontal face detection Feature extraction local binary patterns Mobile Phone Mobile phones Feature extraction Facial Recognition binary binary pattern PROCESSING SPEED

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Geometry,Gabor Wavelets Representation and local binary patterns for Facial Expression Recognition

A Comparative Study of Geometry,Gabor Wavelets Representatio...

引用

2012 International Conference on Electrical and Computer Engineering(ICECE2012)

作者： Qiang Zhou 1,Shiqing Zhang 1 1 School of Physics and Electronic Engineering,Taizhou University,Taizhou,China

Facial expression recognition is an interesting and challenging problem and impacts important applications in many areas such as intelligent environments and multimodal human computer ***,Gabor wavelets representation and local binary patterns(LBP) are three types of successful facial features for facial expression *** this paper,the recognition performance of geometry,Gabor wavelets representation and LBP,was compared on facial expression recognition *** results on the popular JAFFE facial expression database demonstrate Gabor wavelets representation obtains the best performance,outperforming geometry and LBP.

关键词： Facial expression recognition Geometry Garbor wavelets representation local binary patterns

来源：评论

学校读者我要写书评

暂无评论

1-D local binary patterns BASED VAD USED INHMM-BASED IMPROVED SPEECH RECOGNITION

1-D LOCAL BINARY PATTERNS BASED VAD USED INHMM-BASED IMPROVE...

引用

European Signal Processing Conference

作者： Qiming Zhu Navin Chatlani John J. Soraghan Centre for Excellence in Signal and Image Processing (CeSIP) University of Strathclyde Royal College Building

ISBN: (纸本)9781467310680

In this paper, 1-D local binary patterns (LBP) are proposed to be used in speech signal segmentation and voice activation detection (VAD)and combined with hidden Markov model (HMM) for advanced speech recognition. Speech is firstly de-noised by Adaptive Empirical Model Decomposition (AEMD), and then processed using LBP based VAD. The short-time energy of the speech activity detected from the VAD is finally smoothed and used as the input of the HMM recognition process. The enhanced performance of the proposed system for speech recognition is compared with other VAD techniques at different SNRs ranging from 15 dB to a robust noisy condition at -5 dB.

关键词： Speech Enhancement using Adaptive Empirical Model Decomposition (AEMD) local binary patterns Voice Activity Detection Noise Reduction Hidden Markov Model Speech recognition Hidden Markov models binary LBP gene LBP short-time energy dubnium decibel

来源：评论

学校读者我要写书评

暂无评论

DETECTION OF DIABETIC RETINOPATHY AND AGE-RELATED MACULAR DEGENERATION FROM FUNDUS IMAGES THROUGH local binary patterns AND RANDOM FORESTS

DETECTION OF DIABETIC RETINOPATHY AND AGE-RELATED MACULAR DE...

引用

IEEE International Conference on Image Processing

作者： Sandra Morales Kjersti Engan Valery Naranjo Adrian Colomer Instituto Interuniversitario de Investigacion en Bioingenieria y Tecnologia Orientada al Ser Humano Universitat Politecnica de Valencia I3BH/LabHuman Department of Electrical Engineering and Computer Science University of Stavanger

ISBN: (纸本)9781479983407

This work focuses on differentiating between pathological and healthy fundus images. The goal is to distinguish between diabetic retinopathy (DR), age-related macular degeneration (AMD) and normal images by analysing the texture of the retina background. local binary patterns (LBP) are used as texture descriptors. The two class problems DR vs. normal and AMD vs. normal, as well as the three class problem of DR, AMD, and normal, have been tested and have obtained promising results. An average sensitivity and specificity higher than 0.86 in all the cases and almost of 0.96 for AMD detection were achieved with a random forest classifier. These results suggest that LBP is a robust texture descriptor for retinal images and the method proposed in this paper, analysing the retina background directly and avoiding difficult lesion segmentation, can be useful for diagnostic aid.

关键词： local binary patterns Diabetic Retinopathy Age-related Macular Degeneration Fundus Image Retina Texture Macular Degeneration Diabetic Retinopathy texture descriptor binary pattern images Normal binary LBP gene LBP Forest DR Diagnostic agents degeneration THROUGH

来源：评论

学校读者我要写书评

暂无评论

A FPGA-based Hardware Architecture for Real-time Texture Classification Using local binary patterns

A FPGA-based Hardware Architecture for Real-time Texture Cla...

引用

2016 3rd International Conference on Engineering Technology and Application（ICETA 2016）

作者： Long Zhang Wanxia Qu Yang Guo Sikun Li College of Computer National University of Defense Technology

local binary Pattern(LBP) is a simple yet efficient texture operator which has become a popular approach in texture *** this paper,we propose a novel hardware architecture for texture classification algorithms based on local binary patterns that can be executed efficiently on a field-programmable gate arrays(FPGAs).A new memory structure and window operations have been used in this hardware design to accelerate images *** new architecture is implemented on Xilinx Virtex-6 *** experiments show that this new method exhibits more efficient execution compared with standard implementations based on central processing units and graphics processing units.

关键词： local binary patterns texture classification window operations FPGA

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

Change Detection in Feature Space using local binary Similarity patterns

Change Detection in Feature Space using Local Binary Similar...

引用

10th International Conference on Computer and Robot Vision (CRV)

作者： Bilodeau, Guillaume-Alexandre Jodoin, Jean-Philippe Saunier, Nicolas Ecole Polytech Dept Comp & Software Engn LITIV lab Montreal PQ H3C 3A7 Canada Ecole Polytech Dept civil geol & mining engn Montreal PQ H3C 3A7 Canada

ISBN: (纸本)9780769549835

In general, the problem of change detection is studied in color space. Most proposed methods aim at dynamically finding the best color thresholds to detect moving objects against a background model. Background models are often complex to handle noise affecting pixels. Because the pixels are considered individually, some changes cannot be detected because it involves groups of pixels and some individual pixels may have the same appearance as the background. To solve this problem, we propose to formulate the problem of background subtraction in feature space. Instead of comparing the color of pixels in the current image with colors in a background model, features in the current image are compared with features in the background model. The use of a feature at each pixel position allows accounting for change affecting groups of pixels, and at the same time adds robustness to local perturbations. With the advent of binary feature descriptors such as BRISK or FREAK, it is now possible to use features in various applications at low computational cost. We thus propose to perform background subtraction with a small binary descriptor that we named local binary Similarity patterns (LBSP). We show that this descriptor outperforms color, and that a simple background subtractor using LBSP outperforms many sophisticated state of the art methods in baseline scenarios.

关键词： Change detection local binary patterns local binary descriptor Background subtraction

来源：评论

学校读者我要写书评

暂无评论

local polynomial contrast binary patterns for face recognition

引用

NEUROCOMPUTING 2019年 355卷 1-12页

作者： Xu, Zhen Jiang, Yinyan Wang, Yichuan Zhou, Yicong Li, Weifeng Liao, Qingmin Tsinghua Univ Grad Sch Shenzhen Dept Elect Engn Shenzhen Peoples R China Shenzhen Key Lab Informat Sci & Technol Shenzhen Peoples R China Univ Macau Dept Comp & Informat Sci Macau Peoples R China

We propose a novel face representation model, called the polynomial contrast binary patterns (PCBP), based on the polynomial filters, for robust face recognition. It is assumed that the discrete array of pixel values comes about by sampling an underlying smooth surface in an image. The proposed method efficiently estimates the underlying local surface information, which is approximately represented as linear projection coefficients of the pixels in a local patch. The decomposition using polynomial filters can capture rich image information at multiple orientations and frequency bands. This guarantees its robustness to illumination and expression variations. The weighting scheme embeds different discriminative powers of each filter response image. We also propose to carry out a subsequent Fisher linear Discriminant (FLD) on each decomposed image for dimension reduction of features. Our extensive experiments on the public FERET and LFW databases demonstrate that the non-weighted Polynomial contrast binary patterns performs better than most of methods and the weighting scheme further improves the recognition rates. WPCBP+FLD(CD) and WPCBP+FLD(HI) can achieve much competitive or even better recognition performance compared with the state-of-the-art face recognition methods. (C) 2018 Published by Elsevier B.V.

关键词： Face recognition Polynomial filters local binary patterns Surface fitting

来源：评论

学校读者我要写书评

暂无评论

local fractal dimension and binary patterns in texture recognition

引用

PATTERN RECOGNITION LETTERS 2016年 78卷 22-27页

作者： Florindo, Joao B. Bruno, Odemir M. Univ Sao Paulo Sao Carlos Inst Phys POB 369 BR-13560970 Sao Carlos SP Brazil

The present work proposes a new texture image descriptor, combining the local binary patterns extracted from the grey-level image (classic approach) with those extracted from the local fractal dimension at each point of the image. In this way, these descriptors express two important measurements from the image, i. e., the variation among pixel intensities in each local neighbourhood and the local complexity (pixel arrangement) at each point. Such combination provides a rich and robust descriptor even for the most complex textures. The effectiveness of the proposed solution is evaluated in the classification of two well-known benchmark databases: UIUC and USPTex, showing that the combined features outperform all the other compared approaches in terms of correctness rates in the classification of grey-scale texture images. (C) 2016 Elsevier B.V. All rights reserved.

关键词： local fractal dimension local binary patterns Texture recognition Image analysis

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：