Fast Parabola Detection Using Estimation of Distribution Algorithms
This paper presents a new method based on Estimation of Distribution Algorithms (EDAs) to detect parabolic shapes in synthetic and medical images. The method computes a virtual parabola using three random boundary pixels to calculate the constant values of the generic parabola equation. The resultin...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2017-01-01
|
Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2017/6494390 |
id |
doaj-b03022a904934f708a3e2442f1a4c3e7 |
---|---|
record_format |
Article |
spelling |
doaj-b03022a904934f708a3e2442f1a4c3e72020-11-24T22:43:56ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182017-01-01201710.1155/2017/64943906494390Fast Parabola Detection Using Estimation of Distribution AlgorithmsJose de Jesus Guerrero-Turrubiates0Ivan Cruz-Aceves1Sergio Ledesma2Juan Manuel Sierra-Hernandez3Jonas Velasco4Juan Gabriel Avina-Cervantes5Maria Susana Avila-Garcia6Horacio Rostro-Gonzalez7Roberto Rojas-Laguna8Division de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoCONACYT, Centro de Investigacion en Matematicas (CIMAT), A.C., Jalisco S/N, Col. Valenciana, 36000 Guanajuato, GTO, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoCONACYT, Centro de Investigacion en Matematicas (CIMAT), A.C., Fray Bartolome de las Casas 314, Barrio La Estacion, 20259 Aguascalientes, AGS, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoDivision de Ingenierias, Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, Carr. Salamanca-Valle Km 3.5+1.8, Palo Blanco, 36885 Salamanca, GTO, MexicoThis paper presents a new method based on Estimation of Distribution Algorithms (EDAs) to detect parabolic shapes in synthetic and medical images. The method computes a virtual parabola using three random boundary pixels to calculate the constant values of the generic parabola equation. The resulting parabola is evaluated by matching it with the parabolic shape in the input image by using the Hadamard product as fitness function. This proposed method is evaluated in terms of computational time and compared with two implementations of the generalized Hough transform and RANSAC method for parabola detection. Experimental results show that the proposed method outperforms the comparative methods in terms of execution time about 93.61% on synthetic images and 89% on retinal fundus and human plantar arch images. In addition, experimental results have also shown that the proposed method can be highly suitable for different medical applications.http://dx.doi.org/10.1155/2017/6494390 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jose de Jesus Guerrero-Turrubiates Ivan Cruz-Aceves Sergio Ledesma Juan Manuel Sierra-Hernandez Jonas Velasco Juan Gabriel Avina-Cervantes Maria Susana Avila-Garcia Horacio Rostro-Gonzalez Roberto Rojas-Laguna |
spellingShingle |
Jose de Jesus Guerrero-Turrubiates Ivan Cruz-Aceves Sergio Ledesma Juan Manuel Sierra-Hernandez Jonas Velasco Juan Gabriel Avina-Cervantes Maria Susana Avila-Garcia Horacio Rostro-Gonzalez Roberto Rojas-Laguna Fast Parabola Detection Using Estimation of Distribution Algorithms Computational and Mathematical Methods in Medicine |
author_facet |
Jose de Jesus Guerrero-Turrubiates Ivan Cruz-Aceves Sergio Ledesma Juan Manuel Sierra-Hernandez Jonas Velasco Juan Gabriel Avina-Cervantes Maria Susana Avila-Garcia Horacio Rostro-Gonzalez Roberto Rojas-Laguna |
author_sort |
Jose de Jesus Guerrero-Turrubiates |
title |
Fast Parabola Detection Using Estimation of Distribution Algorithms |
title_short |
Fast Parabola Detection Using Estimation of Distribution Algorithms |
title_full |
Fast Parabola Detection Using Estimation of Distribution Algorithms |
title_fullStr |
Fast Parabola Detection Using Estimation of Distribution Algorithms |
title_full_unstemmed |
Fast Parabola Detection Using Estimation of Distribution Algorithms |
title_sort |
fast parabola detection using estimation of distribution algorithms |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2017-01-01 |
description |
This paper presents a new method based on Estimation of Distribution Algorithms (EDAs) to detect parabolic shapes in synthetic and medical images. The method computes a virtual parabola using three random boundary pixels to calculate the constant values of the generic parabola equation. The resulting parabola is evaluated by matching it with the parabolic shape in the input image by using the Hadamard product as fitness function. This proposed method is evaluated in terms of computational time and compared with two implementations of the generalized Hough transform and RANSAC method for parabola detection. Experimental results show that the proposed method outperforms the comparative methods in terms of execution time about 93.61% on synthetic images and 89% on retinal fundus and human plantar arch images. In addition, experimental results have also shown that the proposed method can be highly suitable for different medical applications. |
url |
http://dx.doi.org/10.1155/2017/6494390 |
work_keys_str_mv |
AT josedejesusguerreroturrubiates fastparaboladetectionusingestimationofdistributionalgorithms AT ivancruzaceves fastparaboladetectionusingestimationofdistributionalgorithms AT sergioledesma fastparaboladetectionusingestimationofdistributionalgorithms AT juanmanuelsierrahernandez fastparaboladetectionusingestimationofdistributionalgorithms AT jonasvelasco fastparaboladetectionusingestimationofdistributionalgorithms AT juangabrielavinacervantes fastparaboladetectionusingestimationofdistributionalgorithms AT mariasusanaavilagarcia fastparaboladetectionusingestimationofdistributionalgorithms AT horaciorostrogonzalez fastparaboladetectionusingestimationofdistributionalgorithms AT robertorojaslaguna fastparaboladetectionusingestimationofdistributionalgorithms |
_version_ |
1725693849096945664 |