Colour Texture Analysis for Classifying the Tear Film Lipid Layer: A Comparative Study

Author

Remeseiro, B. ; Ramos, L. ; Penas, M. ; Martínez, E. ; Penedo, M.G. ; Mosquera, A.

Author_Institution

Dept. de Comput., Univ. da Coruna, A Coruna, Spain

fYear

2011

fDate

6-8 Dec. 2011

Firstpage

268

Lastpage

273

Abstract

This paper presents a comparative study of different texture extraction methods for the automatic classification of the tear film lipid layer based on the categories enumerated by Guillon. From a photography of the eye, a region of interest is detected and its low-level features are extracted, generating a feature vector that describes it, to be finally classified in one of the target categories. This paper discusses several texture analysis methods and colour spaces to generate the feature vectors. The proposed methods have been tested on a dataset composed of 105 images, with a classification rate of over 95% in some cases.

Keywords

biomedical optical imaging; eye; feature extraction; image classification; image colour analysis; medical image processing; molecular biophysics; colour texture analysis; eye photography; feature vector; low level feature extraction; tear film lipid layer automatic classification; texture extraction methods; Accuracy; Color; Discrete wavelet transforms; Feature extraction; Gray-scale; Image color analysis; Lipidomics; Butterworth filters; Eye lipid layer; Gabor filters; Guillon categories; Markov random fields; co-occurrence features; machine learning; the discrete wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on

Conference_Location

Noosa, QLD

Print_ISBN

978-1-4577-2006-2

Type

conf

DOI

10.1109/DICTA.2011.51

Filename

6128693