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Multithreshold Segmentation Based on Artificial Immune Systems
Joint Authors
Zaldivar, Daniel
Cuevas, Erik
Osuna-Enciso, Valentin
Sossa, Humberto
Pérez-Cisneros, Marco
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-07-05
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
Bio-inspired computing has lately demonstrated its usefulness with remarkable contributions to shape detection, optimization, and classification in pattern recognition.
Similarly, multithreshold selection has become a critical step for image analysis and computer vision sparking considerable efforts to design an optimal multi-threshold estimator.
This paper presents an algorithm for multi-threshold segmentation which is based on the artificial immune systems(AIS) technique, also known as theclonal selection algorithm (CSA).
It follows the clonal selection principle (CSP) from the human immune system which basically generates a response according to the relationship between antigens (Ag), that is, patterns to be recognized and antibodies (Ab), that is, possible solutions.
In our approach, the 1D histogram of one image is approximated through a Gaussian mixture model whose parameters are calculated through CSA.
Each Gaussian function represents a pixel class and therefore a thresholding point.
Unlike the expectation-maximization (EM) algorithm, the CSA-based method shows a fast convergence and a low sensitivity to initial conditions.
Remarkably, it also improves complex time-consuming computations commonly required by gradient-based methods.
Experimental evidence demonstrates a successful automatic multi-threshold selection based on CSA, comparing its performance to the aforementioned well-known algorithms.
American Psychological Association (APA)
Cuevas, Erik& Osuna-Enciso, Valentin& Zaldivar, Daniel& Pérez-Cisneros, Marco& Sossa, Humberto. 2012. Multithreshold Segmentation Based on Artificial Immune Systems. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-1029814
Modern Language Association (MLA)
Cuevas, Erik…[et al.]. Multithreshold Segmentation Based on Artificial Immune Systems. Mathematical Problems in Engineering No. 2012 (2012), pp.1-20.
https://search.emarefa.net/detail/BIM-1029814
American Medical Association (AMA)
Cuevas, Erik& Osuna-Enciso, Valentin& Zaldivar, Daniel& Pérez-Cisneros, Marco& Sossa, Humberto. Multithreshold Segmentation Based on Artificial Immune Systems. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-1029814
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029814