CBMIR: SHAPE-BASED IMAGE RETRIEVAL USING CANNY EDGE DETECTION AND K-MEANS CLUSTERING ALGORITHMS FOR MEDICAL IMAGES

摘要

The accumulation of large collections of digital images has created the need for efficient and intelligent schemes for classifying and retrieval of images. In this work, CBMIR: Shape-Based Image Retrieval Using Canny Edge Detection and K-Means Clustering Algorithms for Medical Images, has been developed to retrieve the medical images from huge volume of medical databases. This requires the preprocessing, feature extraction, classification, retrieval and indexing steps in order to develop an efficient medical image retrieval system. In this work, for preprocessing step, the image segmentation method has been carried out, for feature extraction, basic shape feature has been extracted using canny edge detection algorithm, and for classification, K-means classification algorithm has been used. For retrieval of images, Euclidian distance method values are calculated between query image and database images. The goal of this work is to provide a medical image retrieval system for further use of medical diagnosis purpose in the field of medical domain.