Pattern Classification of Melanoma by Local Features Using BoF Based Spatial Encoding

Felsia Thompson, Jeyakumar M.K
2017 International Journal of Engineering and Technology  
Melanoma is the direst form of skin cancer. Early detection of cancer is a very critical issue in today's dematologic practice. Feature extraction allows representing the content of the image as perfectly as possible. In this paper, Bag of Features based Supervised Spatial Encoding of Feature extraction is proposed. Low Level Images and their Latent Features induce codebook of features. Scale invariant Speeded up Robust Features (SURF) technique is used for feature point detection in Low Level
more » ... mage representation. Since the system considers the entire image as lesion, it also recognizes clustered or patched lesion. It uses l*a*b color space for describing color intensities. The patterns so detected are classified using multi-SVM classifier. The proposed cluster based system provides the classification accuracy of 95.075% and sensitivity, specificity rates as 94.07% and 95.5 respectively.
doi:10.21817/ijet/2017/v9i6/170906115 fatcat:3rmbtgw5yvbczl3xg2gg3u63w4