Quaternion support vector classifier

Issue title: Intelligent Computing for Pattern Recognition, Image Processing and Computer Vision Papers from CIARP 2014, November 2-5, 2014, Puerto Vallarta, Jalisco, Mexico

Guest editors: Eduardo Bayro-Corrochano

Article type: Research Article

Authors: López-González, G.^* | Arana-Daniel, N. | Bayro-Corrochano, E.

Affiliations: CINVESTAV-Unidad Guadalajara, Colonia el Bajío, Zapopan, Jalisco, México

Correspondence: [*] Corresponding author: G. López-González, CINVESTAV-Unidad Guadalajara, Av. del Bosque 1145, Colonia el Bajío, Zapopan, Jalisco, México. E-mail:gelopez@gdl.cinvestav.mx

Abstract: This paper is concerned with the Quaternion Support Vector Machines for classification as a generalization of the real- and complex-valued Support Vector Machines. In this framework we handle the design of kernels involving the Clifford or quaternion product. The application section shows experiments in pattern recognition and colour image processing. We also present a way to expand the amount of classes without the need to increase the number of classifiers as in standar approaches.

Keywords: Support vector machines, classification, complex SVM, quaternion SVM

DOI: 10.3233/IDA-160849

Journal: Intelligent Data Analysis, vol. 20, no. s1, pp. S109-S119, 2016