Volume 9, Issue 2, September 2014, Pages 511–517
V. Manju1, T. Gomathi2, and S. Poonguzhali3
1 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
2 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
3 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In image processing an essential step is image segmentation. The aim of segmentation is to simplify and to change the representation of an image into a form easier to analyse. Many image segmentation methods are available but most of these methods are not suitable for thermal image and they need prior knowledge. In order to overcome these obstacles, a new thermal image segmentation methodis developed using an unsupervised artificial neural network method called Kohonen's self-organizing map and a threshold technique. Kohonen's self-organizing map is used to organize the pixels according to Gary level values of multiple bands into groups then a threshold technique is used to cluster the image into dislocate zone, this mode is TSOM.
Author Keywords: Image segmentation, Kohonen's self-organizing map, Neural Networks, Unsupervised.
V. Manju1, T. Gomathi2, and S. Poonguzhali3
1 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
2 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
3 Department of ETCE, Sathyabama University, Chennai, Tamilnadu, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In image processing an essential step is image segmentation. The aim of segmentation is to simplify and to change the representation of an image into a form easier to analyse. Many image segmentation methods are available but most of these methods are not suitable for thermal image and they need prior knowledge. In order to overcome these obstacles, a new thermal image segmentation methodis developed using an unsupervised artificial neural network method called Kohonen's self-organizing map and a threshold technique. Kohonen's self-organizing map is used to organize the pixels according to Gary level values of multiple bands into groups then a threshold technique is used to cluster the image into dislocate zone, this mode is TSOM.
Author Keywords: Image segmentation, Kohonen's self-organizing map, Neural Networks, Unsupervised.
How to Cite this Article
V. Manju, T. Gomathi, and S. Poonguzhali, “Enhancing Thermal Image Segmentation By The Application Of The Concepts Used In Unsupervised Artificial Neural Network,” International Journal of Innovation and Scientific Research, vol. 9, no. 2, pp. 511–517, September 2014.
