An efficient meta-heuristic based codebook construction using key point selection over histopathological images

For analyzing various kinds of diseases in the present era classification of Histopathological images is considered to be an essential process, which is performed by extracting the features from selected images in dataset. in this paper we have proposed a new keypoint selection method, Gray Scaling Relational Analysis (GSRA) which are essential for constructing the code book. Then in the next phase we proposed methodology to reduce the dense regions in histopathological images with distinct dimension of pixels by classifying dense and non-dense histopathological images and selection of candidates using CNN. And finally, we have proposed a methodology for constructing meta-heuristic- based code book construction on the Histopathological images on LC25000 lung and colon histopathological image dataset.