中国科学院光电技术研究所机构知识库
Advanced  
IOE OpenIR  > 光电工程总体研究室(一室)  > 会议论文
题名:
A novel description based on skeleton and contour for shape matching
作者: Hu, Jinlong1,2; Peng, Xianrong1; Fu, Chengyu1
出版日期: 2015
会议名称: Proceedings of SPIE - The International Society for Optical Engineering
会议日期: 2015
学科分类: Binary images - Computer vision - Edge detection - Extraction - Feature extraction - Geometry - Graphic methods - High power lasers - Musculoskeletal system - Object detection - Object recognition - Statistical methods
DOI: 10.1117/12.2065209
通讯作者: Hu, Jinlong
中文摘要: In computer vision field, feature extraction plays a critical role in shape matching, image alignment, object recognition and tracking etc. Generally speaking, feature extraction consists of three steps: feature detection, feature description and feature matching. In the second step, the detected features (e.g. gray value, SIFT, Harris corners) are converted to vectors or the form that can be described mathematically such that feature can be matched correctly. How to construct an efficient descriptor to realize accurate shape matching under a variety of transformations is still a challenge. To this end, a novel shape descriptor based on skeleton for shape matching is proposed in this paper. Firstly, the image is smoothed with Gaussian filter to remove the influence of the noise. Secondly, the smoothed image is segmented with Fuzzy C-means Cluster (FCM) to obtain a binary image. Thirdly, the binary image"™s skeleton is extracted with Medial Axis Transform (MAT), thus the skeleton"™s endpoints and joint-points locations are acquired. Furthermore, the object"™s contour is extracted with contour coding. In the construction of skeletal descriptor, the relative location vectors of the skeletal endpoints to each contour point are computed. Being similar to shape context, statistical histogram is constructed in log-polar coordinate. Consequently, shape matching is performed via two histograms"™ similarity measurement. Experiments on standard MPEG7 dataset show that the proposed shape description method allows translation, scale and rotation invariance. © 2015 SPIE.
英文摘要: In computer vision field, feature extraction plays a critical role in shape matching, image alignment, object recognition and tracking etc. Generally speaking, feature extraction consists of three steps: feature detection, feature description and feature matching. In the second step, the detected features (e.g. gray value, SIFT, Harris corners) are converted to vectors or the form that can be described mathematically such that feature can be matched correctly. How to construct an efficient descriptor to realize accurate shape matching under a variety of transformations is still a challenge. To this end, a novel shape descriptor based on skeleton for shape matching is proposed in this paper. Firstly, the image is smoothed with Gaussian filter to remove the influence of the noise. Secondly, the smoothed image is segmented with Fuzzy C-means Cluster (FCM) to obtain a binary image. Thirdly, the binary image"™s skeleton is extracted with Medial Axis Transform (MAT), thus the skeleton"™s endpoints and joint-points locations are acquired. Furthermore, the object"™s contour is extracted with contour coding. In the construction of skeletal descriptor, the relative location vectors of the skeletal endpoints to each contour point are computed. Being similar to shape context, statistical histogram is constructed in log-polar coordinate. Consequently, shape matching is performed via two histograms"™ similarity measurement. Experiments on standard MPEG7 dataset show that the proposed shape description method allows translation, scale and rotation invariance. © 2015 SPIE.
收录类别: Ei
语种: 英语
卷号: 9255
ISSN号: 0277-786X
文章类型: 会议论文
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7418
Appears in Collections:光电工程总体研究室(一室)_会议论文

Files in This Item:
File Name/ File Size Content Type Version Access License
2015-2153.pdf(271KB)会议论文--限制开放View 联系获取全文

作者单位: 1. Institute of Optics and Electronics, Key Laboratory of Beam Control, Chinese Academy of Sciences, Chengdu, Sichuan, China
2. University of Chinese Academy of Sciences, Beijing, China

Recommended Citation:
Hu, Jinlong,Peng, Xianrong,Fu, Chengyu. A novel description based on skeleton and contour for shape matching[C]. 见:Proceedings of SPIE - The International Society for Optical Engineering. 2015.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Hu, Jinlong]'s Articles
[Peng, Xianrong]'s Articles
[Fu, Chengyu]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Hu, Jinlong]‘s Articles
[Peng, Xianrong]‘s Articles
[Fu, Chengyu]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: 2015-2153.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院光电技术研究所 - Feedback
Powered by CSpace