Application of Genetic Algorithm & Morphological Operations for Image Segmentation

Image segmentation is an important part of the digital image processing. It is a low level, but difficult task that segments the image into regions of similar attributes. Segmentation simply changes the illustration of the image by dividing the image into similar components something that is more significant and easier to study. Till now there is no fundamental theory or algorithm on the subject of image segmentation. Although, in this paper genetic algorithm and mathematical morphological operations are used for optimizing or detecting homogenous regions of an image. The operation is performed on 16 x 16 subimages and the resultant subimages are then combined and the segmented images is produced.

[1]  Jin-Jang Leou,et al.  A genetic algorithm approach to color image enhancement , 1998, Pattern Recognit..

[2]  Theodosios Pavlidis,et al.  Picture Segmentation by a Tree Traversal Algorithm , 1976, JACM.

[3]  Binapani Sethi,et al.  A Review of Genetic Algorithm application for Image Segmentation , 2012 .

[4]  C. Tao.  Mobile Mapping Technology for Road Network Data Acquisition , 2001 .

[5]  Kannan,et al.  ON IMAGE SEGMENTATION TECHNIQUES , 2022 .

[6]  A. Rosenfeld,et al.  Edge and Curve Detection for Visual Scene Analysis , 1971, IEEE Transactions on Computers.

[7]  Bir Bhanu,et al.  Adaptive image segmentation using a genetic algorithm , 1989, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  S. N. Sivanandam,et al.  Introduction to genetic algorithms , 2007 .