Low-pass Filter’s Effects on Image Analysis Using Subspace Classifier
This paper shows an effect for applying a low-pass filter on the performance of image analysis using the Subspace classifier. The feature extraction was firstly based on three kinds of intensity distributions, and the feature vector and subspace dimension for recognition were examined. Afterwards, a series of the analysis on the accuracies were conducted in the cases of filtered images and without filtered. The analyzed accuracies by using the Subspace classifier were also compared with the results by the technique of another: Learning vector quantization (LVQ).
KeywordsSubspace Classifier Feature Space Low-pass Filter Learning Vector Quantization Fundus Image
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