中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 机器人学研究室  > 期刊论文
题名: New spectrum ratio properties and features for shadow detection
作者: Tian JD(田建东); Qi XJ(齐虓隽); Qu JQ(屈靓琼); Tang YD(唐延东)
作者部门: 机器人学研究室
关键词: Spectrum ratio properties ; Shadow features ; Skylight SPD ; Daylight SPD ; Shadow detection
刊名: Pattern Recognition
ISSN号: 0031-3203
出版日期: 2016
卷号: 51, 期号:3, 页码:85–96
收录类别: SCI ; EI
产权排序: 1
项目资助者: Natural Science Foundation of China under Grants 61102116 and 61473280.
摘要: Successfully detecting shadows in still images is challenging yet has wide applications. Shadow properties and features are very important for shadow detection and processing. The aim of this work is to find some new physical properties of shadows and use them as shadow features to design an effective shadow detection method for outdoor color images. We observe that although the spectral power distribution (SPD) of daylight and that of skylight are quite different, in each channel, the spectrum ratio of the point-wise product of daylight SPD with sRGB color matching functions (CMFs) to the point-wise product of skylight SPD with sRGB CMFs roughly approximates a constant. This further leads to that the ratios of linear sRGB pixel values of surfaces illuminated by daylight (in non-shadow regions) to those illuminated by skylight (in shadow regions) equal to a constant in each channel. Following this observation, we calculated the spectrum ratios under various Sun angles and further found out four new shadow properties. With these properties as shadow features, we developed a simple shadow detection method to quickly locate shadows in single still images. In our method, we classify an edge as a shadow or non-shadow edge by verifying whether the pixel values on both sides of the Canny edges satisfy the three shadow verification criteria derived from the shadow properties. Extensive experiments and comparison show that our method outperforms state-of-the-art shadow detection methods.
语种: 英语
WOS记录号: WOS:000367633400007
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
关键词[WOS]: CAST SHADOWS ; MODEL ; REMOVAL ; CALIBRATION ; SURFACE ; IMAGES
研究领域[WOS]: Computer Science ; Engineering
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/17439
Appears in Collections:机器人学研究室_期刊论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
New spectrum ratio properties and features for shadow detection.pdf(7205KB)期刊论文作者接受稿开放获取View Download

Recommended Citation:
Tian JD,Qi XJ,Qu JQ,et al. New spectrum ratio properties and features for shadow detection[J]. Pattern Recognition,2016,51(3):85–96.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Tian JD(田建东)]'s Articles
[Qi XJ(齐虓隽)]'s Articles
[Qu JQ(屈靓琼)]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Tian JD(田建东)]‘s Articles
[Qi XJ(齐虓隽)]‘s Articles
[Qu JQ(屈靓琼)]‘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: New spectrum ratio properties and features for shadow detection.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  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace