Vitiligo Detection Using Cepstral Coefficients

Christian Salamea; Juan Fernando Chica

doi:10.1007/978-3-030-32022-5_36

Vitiligo Detection Using Cepstral Coefficients

Christian Salamea, Juan Fernando Chica

Research Group on Interaction, Robotics and Automatics (GIIRA)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Vitiligo is a pathology that causes the appearance of macules achromic (white spots) in the skin. Besides, generates a negative emotional burden in the people that have it, what make necessary to develop suitable methods to identify and treat it properly. In this paper we propose a novel system formed by two stages: The Front End where the principal characteristics of the image are extracted using the Mel Frequency Cepstral Coefficients (MFCC) and i-Vectors (techniques widely used in speech processing) and the Back End, where these characteristics are received and through a classifier is define whether and image contains or not vitiligo. Artificial Neural Networks and Support Vector Machines were selected as classifiers. Results shows that both MFCC and i-Vectors could be used in the field of image processing. Although, the i-Vectors allows us to decrease more the dimensionality of a feature vector and without losing the characteristics of the high dimensionality, this was reflected in their performance with an accuracy of 95.28% to recognize correctly images.

Original language	English
Title of host publication	Advances in Emerging Trends and Technologies Volume 1
Editors	Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz
Publisher	Springer Verlag
Pages	389-398
Number of pages	10
ISBN (Print)	9783030320218
DOIs	https://doi.org/10.1007/978-3-030-32022-5_36
State	Published - 1 Jan 2020
Event	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - quito, Ecuador Duration: 29 May 2019 → 31 May 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1066
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019
Country/Territory	Ecuador
City	quito
Period	29/05/19 → 31/05/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Dimensionality reduction
Feature extraction
i-Vectors
Medical image processing
MFCC

Access to Document

10.1007/978-3-030-32022-5_36

Cite this

@inproceedings{7340a790a7174d66acd9b3baa35b778c,

title = "Vitiligo Detection Using Cepstral Coefficients",

abstract = "Vitiligo is a pathology that causes the appearance of macules achromic (white spots) in the skin. Besides, generates a negative emotional burden in the people that have it, what make necessary to develop suitable methods to identify and treat it properly. In this paper we propose a novel system formed by two stages: The Front End where the principal characteristics of the image are extracted using the Mel Frequency Cepstral Coefficients (MFCC) and i-Vectors (techniques widely used in speech processing) and the Back End, where these characteristics are received and through a classifier is define whether and image contains or not vitiligo. Artificial Neural Networks and Support Vector Machines were selected as classifiers. Results shows that both MFCC and i-Vectors could be used in the field of image processing. Although, the i-Vectors allows us to decrease more the dimensionality of a feature vector and without losing the characteristics of the high dimensionality, this was reflected in their performance with an accuracy of 95.28% to recognize correctly images.",

keywords = "Dimensionality reduction, Feature extraction, i-Vectors, Medical image processing, MFCC",

author = "Christian Salamea and Chica, {Juan Fernando}",

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year = "2020",

month = jan,

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doi = "10.1007/978-3-030-32022-5_36",

language = "English",

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series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "389--398",

editor = "Miguel Botto-Tobar and Joffre Le{\'o}n-Acurio and {D{\'i}az Cadena}, Angela and {Montiel D{\'i}az}, Pr{\'a}xedes",

booktitle = "Advances in Emerging Trends and Technologies Volume 1",

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Salamea, C & Chica, JF 2020, Vitiligo Detection Using Cepstral Coefficients. in M Botto-Tobar, J León-Acurio, A Díaz Cadena & P Montiel Díaz (eds), Advances in Emerging Trends and Technologies Volume 1. Advances in Intelligent Systems and Computing, vol. 1066, Springer Verlag, pp. 389-398, 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019, quito, Ecuador, 29/05/19. https://doi.org/10.1007/978-3-030-32022-5_36

Vitiligo Detection Using Cepstral Coefficients. / Salamea, Christian; Chica, Juan Fernando.
Advances in Emerging Trends and Technologies Volume 1. ed. / Miguel Botto-Tobar; Joffre León-Acurio; Angela Díaz Cadena; Práxedes Montiel Díaz. Springer Verlag, 2020. p. 389-398 (Advances in Intelligent Systems and Computing; Vol. 1066).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Vitiligo Detection Using Cepstral Coefficients

AU - Salamea, Christian

AU - Chica, Juan Fernando

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Vitiligo is a pathology that causes the appearance of macules achromic (white spots) in the skin. Besides, generates a negative emotional burden in the people that have it, what make necessary to develop suitable methods to identify and treat it properly. In this paper we propose a novel system formed by two stages: The Front End where the principal characteristics of the image are extracted using the Mel Frequency Cepstral Coefficients (MFCC) and i-Vectors (techniques widely used in speech processing) and the Back End, where these characteristics are received and through a classifier is define whether and image contains or not vitiligo. Artificial Neural Networks and Support Vector Machines were selected as classifiers. Results shows that both MFCC and i-Vectors could be used in the field of image processing. Although, the i-Vectors allows us to decrease more the dimensionality of a feature vector and without losing the characteristics of the high dimensionality, this was reflected in their performance with an accuracy of 95.28% to recognize correctly images.

AB - Vitiligo is a pathology that causes the appearance of macules achromic (white spots) in the skin. Besides, generates a negative emotional burden in the people that have it, what make necessary to develop suitable methods to identify and treat it properly. In this paper we propose a novel system formed by two stages: The Front End where the principal characteristics of the image are extracted using the Mel Frequency Cepstral Coefficients (MFCC) and i-Vectors (techniques widely used in speech processing) and the Back End, where these characteristics are received and through a classifier is define whether and image contains or not vitiligo. Artificial Neural Networks and Support Vector Machines were selected as classifiers. Results shows that both MFCC and i-Vectors could be used in the field of image processing. Although, the i-Vectors allows us to decrease more the dimensionality of a feature vector and without losing the characteristics of the high dimensionality, this was reflected in their performance with an accuracy of 95.28% to recognize correctly images.

KW - Dimensionality reduction

KW - Feature extraction

KW - i-Vectors

KW - Medical image processing

KW - MFCC

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DO - 10.1007/978-3-030-32022-5_36

M3 - Conference contribution

AN - SCOPUS:85075695155

SN - 9783030320218

T3 - Advances in Intelligent Systems and Computing

SP - 389

EP - 398

BT - Advances in Emerging Trends and Technologies Volume 1

A2 - Botto-Tobar, Miguel

A2 - León-Acurio, Joffre

A2 - Díaz Cadena, Angela

A2 - Montiel Díaz, Práxedes

PB - Springer Verlag

T2 - 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019

Y2 - 29 May 2019 through 31 May 2019

ER -

Vitiligo Detection Using Cepstral Coefficients

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Publication series

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Keywords

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