New ACO algorithm for image edge detection

Ant Colony Optimization (ACO) is a metaheuristic based on real behavior of ants to solve optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images which allows to extract information from them. An ACO algorithm to edge det...

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Detalles Bibliográficos
Publicado:	2014
Materias:	Algorithms Ant colony optimization Artificial intelligence Image processing Optimization Pattern recognition ACO algorithms Ant Colony Optimization (ACO) Computational time Extract informations Image edge detection Knowledge information Metaheuristic Optimization problems Edge detection
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS23923_v2014_n4_p_Martinez http://hdl.handle.net/20.500.12110/paper_NIS23923_v2014_n4_p_Martinez
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_NIS23923_v2014_n4_p_Martinez
record_format	dspace
spelling	paper:paper_NIS23923_v2014_n4_p_Martinez2023-06-08T16:40:04Z New ACO algorithm for image edge detection Algorithms Ant colony optimization Artificial intelligence Image processing Optimization Pattern recognition ACO algorithms Ant Colony Optimization (ACO) Computational time Extract informations Image edge detection Knowledge information Metaheuristic Optimization problems Edge detection Ant Colony Optimization (ACO) is a metaheuristic based on real behavior of ants to solve optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images which allows to extract information from them. An ACO algorithm to edge detection is proposed. Using heuristic and knowledge information and applying an improvement operator, binary images including edges detected are obtained. The algorithm was tested with several images (real and synthetic, with and without presence of noise). The results reached were competitive in terms of quality of images and required computational time. © The Institution of Engineering and Technology 2014. 2014 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS23923_v2014_n4_p_Martinez http://hdl.handle.net/20.500.12110/paper_NIS23923_v2014_n4_p_Martinez
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Algorithms Ant colony optimization Artificial intelligence Image processing Optimization Pattern recognition ACO algorithms Ant Colony Optimization (ACO) Computational time Extract informations Image edge detection Knowledge information Metaheuristic Optimization problems Edge detection
spellingShingle	Algorithms Ant colony optimization Artificial intelligence Image processing Optimization Pattern recognition ACO algorithms Ant Colony Optimization (ACO) Computational time Extract informations Image edge detection Knowledge information Metaheuristic Optimization problems Edge detection New ACO algorithm for image edge detection
topic_facet	Algorithms Ant colony optimization Artificial intelligence Image processing Optimization Pattern recognition ACO algorithms Ant Colony Optimization (ACO) Computational time Extract informations Image edge detection Knowledge information Metaheuristic Optimization problems Edge detection
description	Ant Colony Optimization (ACO) is a metaheuristic based on real behavior of ants to solve optimization problems. Edge detection plays an important role in image processing. It consists in detecting edges or contours in images which allows to extract information from them. An ACO algorithm to edge detection is proposed. Using heuristic and knowledge information and applying an improvement operator, binary images including edges detected are obtained. The algorithm was tested with several images (real and synthetic, with and without presence of noise). The results reached were competitive in terms of quality of images and required computational time. © The Institution of Engineering and Technology 2014.
title	New ACO algorithm for image edge detection
title_short	New ACO algorithm for image edge detection
title_full	New ACO algorithm for image edge detection
title_fullStr	New ACO algorithm for image edge detection
title_full_unstemmed	New ACO algorithm for image edge detection
title_sort	new aco algorithm for image edge detection
publishDate	2014
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS23923_v2014_n4_p_Martinez http://hdl.handle.net/20.500.12110/paper_NIS23923_v2014_n4_p_Martinez
_version_	1769175852987187200

New ACO algorithm for image edge detection

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