Image Content Based Retrieval System using Cosine Similarity for Skin Disease Images

Abstract

A content based image retrieval system (CBIR) is proposed to assist the dermatologist for diagnosis of skin diseases. First, after collecting the various skin disease images and their text information (disease name, symptoms and cure etc), a test database (for query image) and a train database of 460 images approximately (for image matching) are prepared. Second, features are extracted by calculating the descriptive statistics. Third, similarity matching using cosine similarity and Euclidian distance based on the extracted features is discussed. Fourth, for better results first four images are selected during indexing and their related text information is shown in the text file. Last, the results shown are compared according to doctor’s description and according to image content in terms of precision and recall and also in terms of a self developed scoring system.