International Journal of Computational Intelligence Systems

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Volume 9, Issue Supplement 1, April 2016, Pages 43 - 68

Classifying image analysis techniques from their output

Authors
C Guada1, *, cguada@ucm.es, D Gómez2, dagomez@estad.ucm.es, JT. Rodríguez1, jtrodriguez@mat.ucm.es, J Yáñez1, jayage@ucm.es, J Montero1, 3, monty@mat.ucm.es
1Facultad de Ciencias Matemáticas, Complutense University, Plaza de las Ciencias 3, Madrid, 28040, Spain†
2Facultad de Estudios Estadísticos, Complutense University, Av. Puerta de Hierro s/n, Madrid, 28040, Spain‡
3Instituto de Geociencias IGEO (CSIC, UCM), Plaza de las Ciencias 3, Madrid, 28040, Spain§
*

Facultad de Ciencias Matemáticas, Complutense University, Plaza de las Ciencias 3, Madrid, 28040, Spain.

†

Facultad de Ciencias Matemáticas, Complutense University, Plaza de las Ciencias 3, Madrid, 28040, Spain.

‡

Facultad de Estudios Estadísticos, Complutense University, Av. Puerta de Hierro s/n, Madrid, 28040, Spain.

§

Instituto de Geociencias IGEO (CSIC-UCM), Plaza de las Ciencias 3, Madrid, 28040, Spain.

Received 5 November 2015, Accepted 12 March 2016, Available Online 1 April 2016.
DOI
10.1080/18756891.2016.1180819How to use a DOI?
Keywords
Image segmentation; image classification; edge detection; fuzzy sets; machine learning; graphs
Abstract

In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some stage, each technique has been usually designed to focus on a specific objective, and their outputs are in fact different according to each objective. Thus, they are in fact different methods. But due to the essential relationship between them they are quite often confused. In particular, this paper pursues a clarification of the differences between image segmentation and edge detection, among other image processing techniques.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - Supplement 1
Pages
43 - 68
Publication Date
2016/04/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1180819How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - C Guada
AU  - D Gómez
AU  - JT. Rodríguez
AU  - J Yáñez
AU  - J Montero
PY  - 2016
DA  - 2016/04/01
TI  - Classifying image analysis techniques from their output
JO  - International Journal of Computational Intelligence Systems
SP  - 43
EP  - 68
VL  - 9
IS  - Supplement 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1180819
DO  - 10.1080/18756891.2016.1180819
ID  - Guada2016
ER  -