A Survey on Local and Global Feature Extraction Techniques in Content Based Medical Image Retrieval - Samraj, Jasmine; Dhivya, R (International Journal of Computer Sciences and Engineering, 2025)
Content-Based Image Retrieval (CBIR), also known as Query by Image Content and Content-Based Visual Information Retrieval is the application of Computer Vision Techniques and Image Processing Algorithms to the image retrieval problem which is the problem of searching for digital images in large databases. "Content-based" means that the search analyses the contents of the image rather than the metadata such as keywords, tags, or descriptions associated with the image. The term "Content" refers the low – level features of the image such as colour, shape, texture, or any other information that can be derived from the image itself. Content based image retrieval uses these extracted features to retrieve the relevant images from the database. The Local and Global features extracted from these image also plays an important role in the Content Based Medical Image Retrieval (CBMIR). The global features are extracted from the whole image whereas the zone based local features are computed from individual regions of the image to form the local features. Recent studies show that content based image retrieval is an important area of research in the multimedia databases in retrieving similar images based on user defined specification or pattern. In this paper we analyse the different state-of-art local and global feature extraction techniques used by the content based image retrieval system for medical images.