Research Article | OPEN ACCESS
Edge Detection Algorithms VS-active Contour for Sketch Matching: Comparative Study
1Ghazali Sulong, 1, 2Huda Abdulaali and 3Soukaena Hassan
1UTM-IRDA Digital Media Center (MaGIC-X), Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor Takzim, Malaysia
2Department of Computer, College of Science, University of Al-Mustansiriyah, Baghdad,
3Department of Computer Science, University of Technology, Iraq
Research Journal of Applied Sciences, Engineering and Technology 2015 7:759-764
Received: April 14, 2015 | Accepted: May 10, 2015 | Published: November 05, 2015
Abstract
Sketch based image retrieval method is still a new filed under development process in the research area. The main idea of image retrieval by sketch is to detect or bound the object in images which stored in the database and match it with a query which inserted as a sketch. This study displays the edge detection algorithms like (Sobel, Canny) and compare the results with contour active (Snakes) boundary methods. The results of those methods prepared to match with the query sketch. The experimental results show that Snakes algorithms registered as the best in matching process which fabricate a differentiated boundary detection of image objects. For more validity of this method used, the annotation of each matched image has been checked and approved that the contour (Snakes) boundary method is more precise in image retrieval.
Keywords:
Boundary object, edge detection, image annotation, object detected, sketch matching, snakes active contour,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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