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 :
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