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A Multilevel Automatic Thresholding Method Based on a Genetic Algorithm for a Fast Image Segmentation by Kamal Hammouche; Moussa Diaf; Patrick Siarry is a Computer Science article available to read on EtoBox.

What is A Multilevel Automatic Thresholding Method Based on a Genetic Algorithm for a Fast Image Segmentation about?

In this paper, a multilevel thresholding method which allows the determination of the appropriate number of thresholds as well as the adequate threshold values is proposed. This method combines a genetic algorithm with a wavelet transform. First, the length of the original histogram is reduced by using the wavelet transform. Based on this lower resolution version of the histogram, the number of thresholds and the threshold values are determined by using a genetic algorithm. The thresholds are then projected onto the original space. In this step, a refinement procedure may be added to detect accurate threshold values. Experiments and comparative results with multilevel thresholding methods over a synthetic histogram and real images show the efficiency of the proposed method.

Who reads A Multilevel Automatic Thresholding Method Based on a Genetic Algorithm for a Fast Image Segmentation?

Author

Kamal Hammouche; Moussa Diaf; Patrick Siarry

Publisher

Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 1077-3142)

Published

2008

Language

EN

Field

Computer Science (Physical Sciences)