Analysis of Cluster based Self Organization Map (SOM) Algorithm in Various Color Spaces Models

Nwe Ni Than, Myat Thu Zar

Abstract


Image segmentation means separation process that can divide the original image into smaller area with similar attributes. In this proposed system, input images are taken from the Berkley Image Segmentation Database (BSD) for color image segmentation.  Various color space of images such as RGB, HSV and L*A*B* are used for the segmentation process. Due to effect of the color conversion function reduce the input images size is not flexible, Image J software is used to get the same size of images for different color space. The subjective and objective measured is applied to analyze the color images. Then the cluster based self-organization map (SOM) is applied to produce a low-dimensional input space of the training samples. SOM method develops the ratio of color images similarity and spatial relationship of objects within an image. In this system, the features of color similarity in the image is first segmented into cluster regions and  the resulting regions are treated by computing the spatial distance between any two cluster regions and then the labeling process is made by SOM.


Keywords


Color Image Segmentation, SOM Algorithm, Image Processing, Color Space Model, ANN

Full Text:

PDF

References


Amrita Mohanty, S Rajkumar, Zameer Muzaffar Mir, Puja Bardhan “Analysis of Color Images using Cluster based Segmentation Techniques “, International Journal of Computer Applications (0975 – 8887),Volume 79 – No.2, October 2013 .

D.Khattab, “ Color Image Segmentation Based on Different Color Space Model Using Automatic Grabcut”, Research and Development of Advanced Computing Technologies, 2014.

Preeti , “Color Image Segmentation Using K-Means, Fuzzy C-Means and Density Based Clustering”, international journal for research i n applied science and engineering technology ( IJRASET), Vol. 2 Issue VI, June 2014.

R.Hassan, R.R.Ema, “Color Image Segmentation using Automated K-Means Clustering with RGB and HSV Color Spaces”, Global Journal of Computer Science and Technology: Graphic and Vision Volume 17Issue 2Version 1.0 2017.

S.Sengupta, S.Verma, S.M.S.Paul, “Comparative Study of Image Segmentation using Variants of Self Organizing Maps (SOM)”, international journal for research in emerging science and technology, volume-2, issue-5, may-2015.

Q. Ye , W. Gao AND W. Zeng, “Color Image Segmentation Using Density-Based Clustering”, ICASSP, 2003


Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Nwe Ni Than, Myat Thu Zar

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.