A multi-window approach to classify histological features
Medical images are usually composed of different kinds of texture components which are always so much varied that a conventional single window approach cannot capture enough salient information for comparison. This paper applies the widely used multi-channel Gabor filters to demonstrate how a multi-window approach can improve the classification accuracy rate of histological labels. In addition, a most confident window method is proposed to further increase the accuracy rate of the multi-window approach.