3 citations · 13 across the 17 of their papers we have counts for
11 papers · 1 filter
An improved computer vision method for detecting white blood cells
Erik Cuevas, Margarita Diaz, Miguel Manzanares +2
The automatic detection of White Blood Cells (WBC) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine…
Multi Circle Detection on Images Using Artificial Bee Colony (ABC) Optimization
Erik Cuevas, Felipe Sencion-Echauri, Daniel Zaldivar +1
Hough transform (HT) has been the most common method for circle detection, exhibiting robustness, but adversely demanding considerable computational effort and large memory require…
A multilevel thresholding algorithm using Electromagnetism Optimization
Diego Oliva, Erik Cuevas, Gonzalo Pajares +2
Segmentation is one of the most important tasks in image processing. It consist in classify the pixels into two or more groups depending on their intensity levels and a threshold v…
Circle detection using electro-magnetism optimization
Erik Cuevas, Diego Oliva, Daniel Zaldivar +2
This paper describes a circle detection method based on Electromagnetism-Like Optimization (EMO). Circle detection has received considerable attention over the last years thanks to…
Circle detection using Discrete Differential Evolution Optimization
Erik Cuevas, Daniel Zaldivar, Marco Perez +1
This paper introduces a circle detection method based on Differential Evolution (DE) optimization. Just as circle detection has been lately considered as a fundamental component fo…
Seeking multi-thresholds for image segmentation with Learning Automata
Erik Cuevas, Daniel Zaldivar, Marco Perez
This paper explores the use of the Learning Automata (LA) algorithm to compute threshold selection for image segmentation as it is a critical preprocessing step for image analysis,…
Circle detection by Harmony Search Optimization
Erik Cuevas, Noe Ortega, Daniel Zaldivar +1
Automatic circle detection in digital images has received considerable attention over the last years in computer vision as several efforts have aimed for an optimal circle detector…
A Multi-threshold Segmentation Approach Based on Artificial Bee Colony Optimization
Erik Cuevas, Felipe Sencion, Daniel Zaldivar +2
This paper explores the use of the Artificial Bee Colony (ABC) algorithm to compute threshold selection for image segmentation. ABC is a heuristic algorithm motivated by the intell…
Fast algorithm for Multiple-Circle detection on images using Learning Automata
Erik Cuevas, Fernando Wario, Valentin Osuna +2
Hough transform (HT) has been the most common method for circle detection exhibiting robustness but adversely demanding a considerable computational load and large storage. Alterna…
Circle detection on images using Learning Automata
Erik Cuevas, Fernando Wario, Daniel Zaldivar +1
Circle detection over digital images has received considerable attention from the computer vision community over the last few years devoting a tremendous amount of research seeking…
Multi-ellipses detection on images inspired by collective animal behavior
Erik Cuevas, Maurici Gonzalez, Daniel Zaldivar +1
This paper presents a novel and effective technique for extracting multiple ellipses from an image. The approach employs an evolutionary algorithm to mimic the way animals behave c…