Shadow detection for moving objects based on texture analysis

Year: 2007

Authors: Leone A., Distante C.

Autors Affiliation: CNR, IMM, I-73100 Lecce, Italy

Abstract: This paper presents a new approach for shadow detection of moving objects in visual surveillance environment, improving localization, segmentation, tracking and classification of detected objects. An automatic segmentation procedure based on adaptive background difference is performed in order to detect potential shadow points so that, for all moving pixels, the approach evaluates the compatibility of photometric properties with shadow characteristics. The shadow detection approach is improved by evaluating the similarity between little textured patches, since shadow regions present same textural characteristics in each frame and in the corresponding adaptive background model. In this work we suggest a new approach to describe textural information in terms of redundant systems of functions. The algorithm is designed to be unaffected by scene type, background type or light conditions. Experimental results validate the algorithm

Journal/Review: PATTERN RECOGNITION

Volume: 40 (4)      Pages from: 1222  to: 1233

KeyWords: videosurveillance; shadow detection; texture analysis; frame theory; Gabor dictionaries
DOI: 10.1016/j.patcog.2006.09.017

ImpactFactor: 2.019
Citations: 138
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-09-29
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