Abstract
This paper describes a methodology for the automatic classification of the eye lipid layer based on the categories enumerated by Guillon [1]. From a photography of the eye, the system detects the region of interest where the analysis will take place, extracts its low-level features, generates a feature vector that describes it and classifies the feature vector in one of the target categories. We have tested our methodology on a dataset composed of 105 images, with a classification rate of over 90%.
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Ramos, L., Penas, M., Remeseiro, B., Mosquera, A., Barreira, N., Yebra-Pimentel, E. (2011). Texture and Color Analysis for the Automatic Classification of the Eye Lipid Layer. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_9
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DOI: https://doi.org/10.1007/978-3-642-21498-1_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21497-4
Online ISBN: 978-3-642-21498-1
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