DocumentCode
74273
Title
Adaptive shadow detection using global texture and sampling deduction
Author
Ke Jiang ; Ai-hua Li ; Zhi-gao Cui ; Tao Wang ; Yan-zhao Su
Author_Institution
502 Fac., Xi´an Inst. of High Technol., Xi´an, China
Volume
7
Issue
2
fYear
2013
fDate
Apr-13
Firstpage
115
Lastpage
122
Abstract
An adaptive shadow detection algorithm is proposed to eliminate interference on object detection from the shadow. The algorithm uses three components in YUV colour space to identify shadow pixels from the candidate foreground. An adaptive threshold estimator is designed to improve shadow detection accuracy and adaptive capacity in various lighting conditions. This estimator uses edge detection method to obtain global texture, as well statistical calculations to obtain the thresholds. Algorithm has the characteristic of low complexity and little restraint; hence it is suitable for real time-moving shadow detection in various lighting conditions. Experiment results show that this algorithm can obtain a high detection accuracy and the time-assume is greatly shortened compared with other algorithms with similar accuracy.
Keywords
edge detection; image colour analysis; image matching; image sampling; image texture; interference suppression; lighting; object detection; real-time systems; statistical analysis; YUV colour space; adaptive capacity; adaptive shadow detection algorithm; adaptive threshold estimator; edge detection method; global texture; high detection accuracy; interference elimination; lighting conditions; object detection; real time-moving shadow detection; sampling deduction; statistical calculations;
fLanguage
English
Journal_Title
Computer Vision, IET
Publisher
iet
ISSN
1751-9632
Type
jour
DOI
10.1049/iet-cvi.2012.0106
Filename
6519167
Link To Document