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| Shadow elimination method integrated edge features and local texture characteristic |
| 1.School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China; 2.Key Laboratory of Automotive Electronics and Intelligent Transportation, Southeast University, Suzhou, Jiangsu 215123, China |
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Abstract To achieve shadow elimination in video target segmentation, according to confidence, characters of foreground edge projection and local texture features were merged to propose a novel shadow extraction strategy. By adaptive Gaussian method， the foreground containing shadow was obtained to extract dynamic background. The edge difference between foreground and background in minimum enclosing rectangle area of foreground was calculated to achieve edges and shadow of vehicle. Otsu algorithm was used for video segmentation. The area with high confidence was labeled as shadow, and that with low confidence was labeled as vehicle. According to the jumping level of local texture between current frame and background frame, the remaining shadow concerning with vehicle was found out in the area with middle confidence by further processing. Experimental results demonstrate that the proposed method can effectively remove huge shadows which may lead to heavy deformation with over 90％ elimination rate. The algorithm can be applied in object detecting and tacking in intelligent video surveillance system with good real-time performance.
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2012, Vol. 33 
