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.
|Title of host publication
|Advances in Emerging Trends and Technologies Volume 1
|Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz
|Number of pages
|Published - 1 Jan 2020
|1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - quito, Ecuador
Duration: 29 May 2019 → 31 May 2019
|Advances in Intelligent Systems and Computing
|1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019
|29/05/19 → 31/05/19
Bibliographical notePublisher Copyright:
© 2020, Springer Nature Switzerland AG.
- Dimensionality reduction
- Feature extraction
- Medical image processing