Filtering Effects for Image Data Types in Image Analysis Using Subspace Classifier

This paper describes an effect on performance of classification with applying of a low-pass filter to an image of a few of distinct image types in the image analysis using Subspace classifier method. The feature extraction was firstly examined based on three kinds of intensity images, and for classification, the feature vector and Subspace dimension were determined. Afterwards, the images with a few of distinct image types were analyzed for classification performance, and filtered images were also analyzed. The analyzed accuracies of filtered images were compared with the accuracy without filtering. Our results showed that the features of true-color channel were suitable for classification, and that an application of filter to an image of a few of distinct image types had an influence on a classification accuracy.