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http://hdl.handle.net/2080/355
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| Title: | Parallel Genetic Algorithm Based Thresholding for Image Segmentation |
| Authors: | Kanungo, P
Nanda, P K |
| Keywords: | Thresholding
Segmentation
Object Background Classification
Genetic Algorithm |
| Issue Date: | 2006 |
| Publisher: | IMT, Nagpur, India |
| Citation: | Proceedings of the National Seminar on IT and Softcomputing ITSC06, Nov 17-18 IMT, Nagpur, India |
| Abstract: | Threshold plays a vital role in classification of
objects and background in a given scene and hence
segmentation. Determination of optimal threshold is
hard for images exhibiting overlapping histogram
distributions. In this paper, we propose a novel
strategy of determining the threshold from histogram
distributions. A feature image is generated from the
given image and the optimal threshold is determined
using the histogram of the featured pixels. The
featured pixels are generated by considering a fixed
window around a pixel. The histogram distributions
are discrete in nature and hence Genetic Algorithm
(GA) and Parallel Genetic Algorithm (PGA) based
clustering algorithms are proposed to determine the
optimal thresholds for two and three class problems.
The optimal thresholds, thus determined could
segment the noisy image. The efficacy of the proposed
scheme is compared with that of the Otsu’s approach.
Results obtained by the proposed scheme was
comparable to that O... |
| Description: | Copyright for this article belongs to the publisher of the proceedings |
| URI: | http://hdl.handle.net/2080/355 |
| Appears in Collections: | Conference Papers
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