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Shadow detection and removal in real scene images is always a challenging but yet intriguing problem. In contrast with the rapidly expanding and continuous interests on this area, it is always hard to provide a robust system to eliminate shadows in static images. This paper aimed to give a comprehensive method to remove shadows based on a two stage approach: vague shadow estimation and hard shadow estimation. First, classification is applied to the derivatives of the input image to separate the vague shadows. Then, color invariant is exploited to distinguish the hard shadow edges from the material edges. Next, a robust shadow edge mask was obtained based on the combination of the vague and hard shadow mask. By using image reintegrating approaches, we derived the shadow estimation form the mask and obtained the shadow-free reflectance image by subtracting shadows from the original image. Experimental results showed that our method can robustly remove both vague and hard shadows appearing in the real scene images.
Wydawca
Czasopismo
Rocznik
Tom
Strony
37--49
Opis fizyczny
Bibliogr. 17 poz., fot.
Twórcy
autor
autor
- Department of Computer Science and Engineering, Shanghai Jiaotong University, P.R. China, nathan.xu@sjtu.edu.cn
Bibliografia
- [1] J.M. Wang, Y.C. Chung, C.L. Chang, S.W. Chen, Shadow Detection and Removal for Traffic Images, Proc. IEEE International Conference on Networking, Sensing and Control, vol. 1, pp. 649 - 654, 2004.
- [2] T. Chen, W. Yin, X.S. Zhou, D. Comaniciu, and T.S. Huang, Illumination Normalization for Face Recognition and Uneven Background Correction Using Total Variation Based Image Models, Proc. CVPR, vol. 2, pp. 532-539, 2005.
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- [4] A. Prati, I. Mikic, M. Trivedi, and R. Cucchiara, Detecting moving shadows: Algorithms and evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, pp. 918-923, 2003.
- [5] S. Nadimi and B. Bhanu, Physical models for moving, shadow and object detection in video, IEEE Trans. Pattern Anal. Machine Intell, vol. 26, no. 8,. pp. 1079-1087,2004.
- [6] E.H. Land, The Retinex Theory of Color Vision, Scientific American, vol. 237, pp. 108-128, 1977.
- [7] J. McCann, Lessons Learned from Mondrians Applied to Real Images and Color Gamuts, Proc. IS&T/SID Seventh Color Imaging Conference, pp. 1-8, 1999.
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- [11] Y. Matsushita, K. Nishino, K. Ikeuchi, M. Sakauchi, Illumination Normalization with Time-Dependent Intrinsic Images for Video Surveillance, IEEE Trans. Pattern Anal. Machine Intell., 26(10):1336-1347, 2004
- [12] M. Tappen, W.T. Freeman, and E.H. Adelson, Recovering intrinsic images from a single image, IEEE Trans. Pattern Anal. Machine Intell., vol. 27, no. 9, pp. 1459-1472, 2005
- [13] E. Salvador, P. Green, and T. Ebrahimi, Shadow identification and classification using invariant color models, Proc. of ICASSP 01, volume 3, pages 1545-1548. IEEE, 2001
- [14] M. Baba N. Asada, Shadow Removal from a Real Picture, Proceedings of the SIGGRAPH conference on Sketches & applications, 2003
- [15] M. Baba, M. Mukunoki, N. Asada, Shadow Removal from a Real Image Based on Shadow Density, SIGGRAPH, 2004.
- [16] G.D. Finlayson, S.D. Hordley C. Lu and M.S. Drew, On the Removal of Shadows from Images, IEEE Trans. Pattern Anal. Machine Intell., Jan, 2006
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0017-0078