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Image Segmentation for Uneven Lighting Images using Adaptive Thresholding and Dynamic Window based on Incremental Window Growing Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 56 - Number 13 |
| Year of Publication: 2012 |
| Authors: Rashmi Saini, Maitreyee Dutta |
10.5120/8954-3140
|
Rashmi Saini, Maitreyee Dutta . Image Segmentation for Uneven Lighting Images using Adaptive Thresholding and Dynamic Window based on Incremental Window Growing Approach. International Journal of Computer Applications. 56, 13 ( October 2012), 31-36. DOI=10.5120/8954-3140
Abstract
This paper proposes a novel method to address the problem of segmentation, for uneven lighting images. Though there are many segmentation methods, but most of them are based on either the fixed window method or window merging technique. Limitation of such methods is that, initial size of window is selected manually and segmentation accuracy greatly depends upon the proper choice of initial window size. In the proposed work, problem of uneven illumination condition has been addressed using dynamic window growing approach. The proposed algorithm is based on an incremental window growing approach using entropy based selection criteria. The window thus fixed by the selection criteria are considered as sub-images and each sub-images has been segmented by using minimum standard deviation difference based thresholding to improve the segmentation result. The result of the experiments show that the proposed method can deal with higher number of segmentation problem and improve the overall performance for uneven lighting image segmentation.
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