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Object Detection Based on Template Matching through Use of Best-So-Far ABC
Joint Authors
Tanathong, Supannee
Banharnsakun, Anan
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-09
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks.
This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm.
In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function.
Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution.
American Psychological Association (APA)
Banharnsakun, Anan& Tanathong, Supannee. 2014. Object Detection Based on Template Matching through Use of Best-So-Far ABC. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-508145
Modern Language Association (MLA)
Banharnsakun, Anan& Tanathong, Supannee. Object Detection Based on Template Matching through Use of Best-So-Far ABC. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-508145
American Medical Association (AMA)
Banharnsakun, Anan& Tanathong, Supannee. Object Detection Based on Template Matching through Use of Best-So-Far ABC. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-508145
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-508145