Segmentation of Skin Lesion Using Harris Corner Detection and Region Growing

Nowadays skin diseases are considered as one of the common cause of human illness, and if not detected or diagnosed at early stage, it can be more harmful. With advancement in computer vision and image processing various techniques have been developed for diagnoses of skin diseases. This work mainly focused on simple yet effective technique for segmentation of skin lesions. It is also robust for extracting the region of interest whose background and foreground color is bit similar. It automatically segments skin lesion of arbitrary shapes and sizes. The proposed technique is mainly based on three major modules namely preprocessing, segmentation and post-processing. In pre-processing different color models are used for extraction of single channel followed by filtering to remove noise. In the second module, segmentation is preformed using Harris corner detector, seed selection and region growing segmentation. Finally morphological operation is performed as post-processing comprising of region filling and dilation. The experimentation results shows the performance of proposed model by achieving accuracy of 95%.