A Shackle Process for Shadow Detection
V Suriya, Sona Poulose and S Anila. Article: A Shackle Process for Shadow Detection. IJCA Proceedings on International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences ICIIIOES(3):8-15, December 2013. Full text available. BibTeX
@article{key:article,
author = {V. Suriya and Sona Poulose and S. Anila},
title = {Article: A Shackle Process for Shadow Detection},
journal = {IJCA Proceedings on International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences},
year = {2013},
volume = {ICIIIOES},
number = {3},
pages = {8-15},
month = {December},
note = {Full text available}
}
Abstract
The presence of shadows in images can represent a serious obstacle for their full exploitation. Shadows are a decrease in the amount of light that reaches a surface. They are a local change in the amount of light rejected by a surface towards the observer. Coping with shadows is a crucial challenge in object detection, scene understanding, recognition and tracking applications. In the proposed technique, detection of shadow region is performed by using morphological operations. Borders are identified by finding the difference between dilation and erosion processes. The classification process is implemented by means of the KNN (K-Nearest Neighbourhood) classifier. Colour segmentation is performed to compare with the results of the border image created. The comparison results of the colour segmented and border image are considered in terms of classification. Thus, using the proposed technique the classification of shadows and non-shadows is better than the segmentation technique.
References
- Ar´evalo. V, Gonz´alez. J and Ambrosio. G (2008), 'Shadow detection in colour high-resolution satellite images'. Int. J. Remote Sens. , 29(7):1945–1963.
- Bell. M and Freeman. W. T (2001), 'Learning local evidence for shading and reflectance'. In ICCV01, pages I: 670--677.
- Cai. D, Li. M, Bao. Z, Chen. Z, Wei. W, and Zhang. H (2010), 'Study on shadow detection method on high resolution remote sensing image based on HIS space transformation and NDVI index', in Proc. 18th Int. Conf. Geoinf. , pp. 1–4.
- Cucchiara. R, Grana. C, Neri. G, Piccardi. M, and Prati. A (2001), 'The Sakbot System for Moving Object Detection and Tracking', Video-Based Surveillance Systems—Computer Vision and Distributed Processing, pp. 145-157.
- Finlayson. G and Süsstrunk. S (2002), 'Optimization for hue constant RGB sensors', in Proc. IS&T/SID 10th Colour Image. Conf. , vol. 10, pp. 343–348.
- Horprasert. T, Harwood. D, and Davis. L. S (1999), 'A Statistical Approach for Real-Time Robust Background Subtraction and Shadow Detection', Proc. IEEE Int'l Conf. Computer Vision '99 FRAME-RATE Workshop.
- Kasetkasem. T and Varshney. P. K (2011), 'An optimum land cover mapping algorithm in the presence of shadow', IEEE J. Select. Topics Signal Process, vol. 5, no. 3, pp. 592–605.
- Koller. D, Danilidis. K, Nagel. H (1993), 'Model-based object tracking in monocular image sequences of road traffic scenes', Int. J. Compute. Vis. 10 (3) 257–281.
- Land. E. H and McCann. J. J (1971), 'Lightness and the Retinex Theory', J. Opt. Soc. Am. , Vol. 61, pp. 1-11.
- Land. E. H (1983), 'Recent Advances in the Retinex Theory and Some Implications for Cortical Computations: Colour Vision and the natural Image', Proc. Nat. Acad. Sci. USA, Vol. 80, pp. 6163-5169
- Mikic. I, Cosman. P, Kogut. G, and Trivedi. M (2000), 'Moving Shadow and Object Detection in Traffic Scenes', Proc. Int'l Conf. Pattern Recognition, vol. 1, pp. 321-324.
- Nadimi. S and Bhanu. B (2004), 'Physical models for moving shadow and object detection in video', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 8,. pp. 1079–1087, August.
- Prati. A, Mikic. I, Grana. C, and Trivedi. M (2001), 'Shadow Detection Algorithms for Traffic Flow Analysis: A Comparative Study', Proc. IEEE Intelligent Transportation Systems Conf. , Oakland, CA.
- Prati. A, Mikic. I, Trivedi. M, and Cucchiara. R (2003), 'Detecting Moving Shadows: Algorithms and Evaluation', IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, pp. 918--923.
- Salvador. E, Cavallaro. A, and Ebrahimi. T (2001), 'Shadow identification and classification using invariant colour models', in Proc. IEEE Int. Conf. Acoust. , Speech, Signal Process. , vol. 3, pp. 1545–1548.
- Salvador. E, Green. P, and Ebrahimi. T (2001), 'Shadow identification and classification using invariant colour models'. In Proceedings of ICASSP 01, volume 3, pages 1545--1548. IEEE.
- Stauder. J, Mech. R, and Ostermann. J (1999), 'Detection of Moving Cast Shadows for Object Segmentation', IEEE Trans. Multimedia, vol. 1, no. 1, pp. 65-76.
- Su. J, Lin. X, and Liu. D (2006), 'An automatic shadow detection and compensation method for remote sensed colour images', in Proc. 8th Int. Conf. Signal Process. , vol. 2, pp. 1–4.
- Wang. J. M, Chung, Chang. C. L, Chen. S. W (2004), 'Shadow detection and removal for traffic images, Networking, Sensing and Control', IEEE International Conference on Volume 1, 21-23 March 2004 Page(s):649 - 654 Vol. 1.