title: Automatic classification of the interferential tear film lipid layer using colour texture analysis.
abstract: The tear film lipid layer is heterogeneous among the population. Its classification depends on its thickness and can be done using the interference pattern categories proposed by Guillon. This papers presents an exhaustive study about the characterisation of the interference phenomena as a texture pattern, using different feature extraction methods in different colour spaces. These methods are first analysed individually and then combined to achieve the best results possible. The principal component analysis (PCA) technique has also been tested to reduce the dimensionality of the feature vectors. The proposed methodologies have been tested on a dataset composed of 105 images from healthy subjects, with a classification rate of over 95% in some cases.
authors.affiliation: Departamento de Computación, Universidade da Coruña, Campus de Elviña S/N, 15071 A Coruña, Spain. bremeseiro@udc.es
authors.forename: B
authors.initials: B
authors.lastname: Remeseiro
authors.forename: M
authors.initials: M
authors.lastname: Penas
authors.forename: N
authors.initials: N
authors.lastname: Barreira
authors.forename: A
authors.initials: A
authors.lastname: Mosquera
authors.forename: J
authors.initials: J
authors.lastname: Novo
authors.forename: C
authors.initials: C
authors.lastname: García-Resúa
mesh_terms: D000328:Adult; D003116:Color; D016208:Databases, Factual; D006801:Humans; D008055:Lipids / Q000737:chemistry* / Q000145:classification*; D008390:Markov Chains; D008857:Microscopy, Interference / Q000706:statistics & numerical data; D055620:Optical Phenomena; D025341:Principal Component Analysis; D060388:Support Vector Machine; D013666:Tears / Q000737:chemistry*; D058067:Wavelet Analysis; D055815:Young Adult
chemical_list: D008055:Lipids