Image Analysis of Fundus Using Filter Bank and Subspace Classifier
Nobuo Matsuda, Hideaki Satō, Fumiaki Tajima · 2016
This paper describes filtering effects on classification performance with applying of filter bank of multi scale and orientation to an image of distinct types in the image analysis using Subspace classifier method. In our proposed method, the feature extraction was firstly conducted, and examinations on the feature vector and subspace dimensions were conducted based on three kinds of intensity distributions. Afterwards, a series of the analysis concerning the accuracy were conducted in the cases of single filter and filter bank. The effects on the performances for filter bank were compared with the performances for a single filter. Our results showed that the preprocessing using filter bank provided a higher classification performance than the results using a single filter preprocessing, and that boosted the improvement of classification performance.