Abstract
A novel algorithm is developed to detect moving objects and remove cast shadows by exploiting textural and spatial-temporal features. Multi-scale wavelet transformation is used to segment moving objects based on spatial property. Textural and spectral features color ratio differences between two adjacent pixels in four different directions are used to remove cast shadows. RGB color space is selected instead of introducing complex color models to segment moving objects and eliminate shadows. The proposal requires much less efforts compared with currently available methods. It does not require any complex supervised training phase, and does not require manual calibration or makes any hypothesis. Experiments have highlighted that the proposal is robust and efficient to segment moving objects and suppress shadow by comparisons.
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Guan, YP. (2012). Texture and Space-Time Based Moving Objects Segmentation and Shadow Removing. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_29
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DOI: https://doi.org/10.1007/978-3-642-31020-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31019-5
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