Improved Unsupervised Color Segmentation Using a Modified HSV Color Model and a Bagging Procedure in K-Means++ Algorithm
Joint Authors
Zaldivar, Daniel
Cuevas, Erik
Chavolla, Edgar
Valdivia, Arturo
Diaz, Primitivo
Pérez-Cisneros, Marco
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-14
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
Accurate color image segmentation has stayed as a relevant topic between the researches/scientific community due to the wide range of application areas such as medicine and agriculture.
A major issue is the presence of illumination variations that obstruct precise segmentation.
On the other hand, the machine learning unsupervised techniques have become attractive principally for the easy implementations.
However, there is not an easy way to verify or ensure the accuracy of the unsupervised techniques; so these techniques could lead to an unknown result.
This paper proposes an algorithm and a modification to the HSV color model in order to improve the accuracy of the results obtained from the color segmentation using the K-means++ algorithm.
The proposal gives better segmentation and less erroneous color detections due to illumination conditions.
This is achieved shifting the hue and rearranging the H equation in order to avoid undefined conditions and increase robustness in the color model.
American Psychological Association (APA)
Chavolla, Edgar& Valdivia, Arturo& Diaz, Primitivo& Zaldivar, Daniel& Cuevas, Erik& Pérez-Cisneros, Marco. 2018. Improved Unsupervised Color Segmentation Using a Modified HSV Color Model and a Bagging Procedure in K-Means++ Algorithm. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-23.
https://search.emarefa.net/detail/BIM-1206453
Modern Language Association (MLA)
Chavolla, Edgar…[et al.]. Improved Unsupervised Color Segmentation Using a Modified HSV Color Model and a Bagging Procedure in K-Means++ Algorithm. Mathematical Problems in Engineering No. 2018 (2018), pp.1-23.
https://search.emarefa.net/detail/BIM-1206453
American Medical Association (AMA)
Chavolla, Edgar& Valdivia, Arturo& Diaz, Primitivo& Zaldivar, Daniel& Cuevas, Erik& Pérez-Cisneros, Marco. Improved Unsupervised Color Segmentation Using a Modified HSV Color Model and a Bagging Procedure in K-Means++ Algorithm. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-23.
https://search.emarefa.net/detail/BIM-1206453
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206453