Image Segmentation with Improved Distance Measure in Som and K Means Algorithms

Volume 8, Issue 4, pp 367 - 376 http://dx.doi.org/10.22436/jmcs.08.04.05

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Authors

Khosro Jalali - Department of Electronic Engineering, Technical and Vocational Schools Mahmoud Abad. Mostafa Heydari - Department of Computer Science and Engineering, Shomal University, Amol, Iran. Asma Tanavar - Department of Computer Engineering ,Islamic Azad University ,Sari branch, Sari, Iran.

Abstract

This paper explains the task of segmenting image by improved distance measure in SOM and K means algorithms. Image segmentation, divides the image into its constituent regions. It can be said the most prominent features in segmenting is the image brightness for monochrome images and the color components of color images. Over all pixels of image analysis is difficult, Pixels with similar brightness, with the use of image segmentation are grouped together. To achieve higher accuracy of segmentation, we are used fit the soft computing techniques namely Fuzzy algorithms. Image segmentation in many cases (For example, the tumor area to help doctors detect tumor) only be used to assist human visual system. This paper compares segmentation-based methods, visual system and scoring is on him.

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Keywords

• Segmentation
• Distance measure
• K means algorithm
• P-norm weigthed SOM

MSC

•  68U10

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