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1887

access icon free Adaptive shadow detection using global texture and sampling deduction

© The Institution of Engineering and Technology
Received 04/06/2012, Accepted 05/02/2013, Revised 07/01/2013, Published

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.

Inspec keywords: lighting; image texture; image matching; object detection; image colour analysis; real-time systems; statistical analysis; edge detection; image sampling; interference suppression

Other keywords: statistical calculations; sampling deduction; interference elimination; YUV colour space; high detection accuracy; adaptive capacity; real time-moving shadow detection; edge detection method; adaptive shadow detection algorithm; global texture; object detection; adaptive threshold estimator; lighting conditions

Subjects: Computer vision and image processing techniques; Other topics in statistics; Other topics in statistics; Image recognition

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