Contact: +91-9711224068
International Journal of Applied Research
  • Multidisciplinary Journal
  • Printed Journal
  • Indexed Journal
  • Refereed Journal
  • Peer Reviewed Journal

ISSN Print: 2394-7500, ISSN Online: 2394-5869, CODEN: IJARPF

Impact Factor: RJIF 5.2

International Journal of Applied Research

Vol. 2, Issue 8, Part E (2016)

Image segmentation with optimization techniques

Author(s)
SP Priyadharshini and S John Grasias
Abstract
Image segmentation is an essential technique and plays vital role in image analysis system and computer vision. Image segmentation is to partitions an input image into its constituent parts and extracting useful information from complex images. Ant colony optimization (ACO) is a cooperative search algorithm inspired by the behaviour of real ants. In order to achieve an approving performance of ACO is global optimization algorithm to solve image segmentation problems. Consequently, the image segmentation can be performed more effectively by finding disease in medical images by using conventional optimization algorithms. The proposed method has been successfully applied to detect the tumour from brain images by using image segmentation techniques. Experimental results show that the proposed segmentation methods produce satisfactory outcome.
Pages: 284-287  |  623 Views  16 Downloads
How to cite this article:
SP Priyadharshini and S John Grasias. Image segmentation with optimization techniques. International Journal of Applied Research. 2016; 2(8): 284-287.
Call for book chapter
International Journal of Applied Research