A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image
|
10.5120/7306-0520 |
Kamaljit Kaur and Heena Chawla. Article: A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image. International Journal of Computer Applications 47(20):33-37, June 2012. Full text available. BibTeX
@article{key:article,
author = {Kamaljit Kaur and Heena Chawla},
title = {Article: A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {47},
number = {20},
pages = {33-37},
month = {June},
note = {Full text available}
}
Abstract
Many image analysis tasks require a classification procedure to identify the shadowed and non-shadowed areas of an image, so that once the shadowed areas are known, the clarity of the image can be improved. The main aim is to detect the anomalous regions of an image. There are numerous techniques of doing so. One of the best ways is to find hyper plane that can be identified to find the difference between the shadow and non shadow areas in the image by using classification algorithm. Thus this research will be to compare various classifiers on the basis of various parameters that which one proves the best in terms of identifying the boundary of shadow and non shadow areas in images. The classification algorithms used in this case would be Support Vector machine (SVM), K- Nearest neighbour (KNN) and Bayesian networks.
References
- Airton M. Polidorio, F. C. Flores, Nilton n. Imai, Antonio M. , G. Tommaselli and Clélia Franco (2003) - "Automatic shadow segmentation in Aerial color images", XVI-Brazilian Symposium on Computer Graphics and Image Processing ,pp. 270-277.
- Andrea Prati, Ivana Mikc, Costantino Grana and Mohan M. Trivedi (2001) –"Shadow Detection Algorithms for Traffic Flow Analysis: a Comparative Study", IEEE Intelligent Transportation Systems Conference, pp. 340-345.
- Elena Salvador, Andrea Cavallaro, Touradj Ebrahimi(2001)- 'Shadow identification and Classification using invariant color models", ICASSP01, pp. 1545-1548.
- Li Xu, Feihu Qi and Renjie Jiang (2006)-"Shadow removal from a single Image", Intelligent System Design and application, pp. 1049-1054.
- Mei Xiao, Chong-Zhao Han and Lei Zhang (2007)-"Moving Shadow Detection and Removal for Traffic Sequences" International Journal of Automation and Computing, pp. 38-46.
- M. A. Egan -'Locating Clusters in Noisy Data: A Genetic Fuzzy c-means Clustering Algorithm", Fuzzy Information processing Society – NAFIPS, conference of the North American, pp. 178- 182.
- Tai-Pang Wu and Chi-Keung Tang (2005)-"A Bayesian Approach For Shadow Extraction From a Single Image", Tenth IEEE International Conference on Computer, vol. 1, pp. 480-487.
- Yan Li, Tadashi Sasagawa, Peng Gong -A system of the shadow detection and shadow Removal for high resolution city aerial photo.
- Yan Li, Tadashi Sasagawa, Peng Gong -A system of the shadow detection and shadow Removal for high resolution city aerial photo.
- Yu-jiao XiaHou,Sheng-rong Gong "Adaptive Shadows Detection Algorithm Based on Gaussian Mixture Model",International Symposium on Information Science and Engineering, 2008,pp. 116-120.
- Gonzalez, Woods, and Eddins(2009), Digital Image Processing Using MATLAB 2nd Ed.