S. H. Jawale, Priyadarshini, Indira Gandhi College of Engineering, Nagpur, India.
A. B. Bavaskar, Indira Gandhi College of Engineering, Nagpur, India.
DOI : 01.0401/ijaict.2014.07.16
International Journal of Advanced Information and Communication Technology
Received On : September 12, 2016
Revised On : October 20, 2016
Accepted On : November 12, 2016
Published On : December 05, 2016
Volume 03, Issue 12
Pages : 601-604
Abstract
Image Fusion is a process of combining the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Also the choice of a color space is of great importance form any computer vision algorithms (e.g. edge detection and object recognition). This paper presents efficient segmentation, edge detection approach, based on a fusion procedure which aims at combining several segmentation images associated to simpler partition models in order to finally get a more reliable and accurate segmentation. Image fusion techniques can improve the quality and increase the application of these data. The objective of Image fusion is to combine the information of the number of images of the same scene from different sensors or the images with focus on different objects. In this paper an introductory approach to some of the image fusion methods has been taken. Edge detection is one of the most commonly used operations in image analysis. In this paper, we present methods for edge segmentation of natural images, we used several techniques for this category.
Keywords
Berkeley image database , color spaces , fusion of segmentations, image processing, edge detection.
Cite this article
S. H. Jawale, Priyadarshini, A. B. Bavaskar, “Fusion based Edge Detection and Segmentation of Color Spaces” INTERNATIONAL JOURNAL OF ADVANCED INFORMATION AND COMMUNICATION TECHNOLOGY, pp.601-604, December 05, 2016.
Copyright
© 2016 S. H. Jawale, Priyadarshini, A. B. Bavaskar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.