Open AccessCOMPREHENSIVE STUDY ON CONTENT BASED IMAGE RETRIEVAL WITH THEIR FEATURES
Author(s) -
Pritpal kaur,
K. Sandeep
Publication year - 2017
Publication title -
international journal of computer and technology
Language(s) - English
Resource type - Journals
ISSN - 2277-3061
DOI - 10.24297/ijct.v16i6.6348
Subject(s) - computer science , search engine indexing , image retrieval , content based image retrieval , terabyte , information retrieval , visual word , process (computing) , feature (linguistics) , scope (computer science) , digital image , database , image processing , artificial intelligence , image (mathematics) , linguistics , philosophy , programming language , operating system
In current years, very huge collections of images and videos have grown swiftly. In parallel with this boom, content-based image retrieval and querying the indexed collections of images from the large database are required to access visible facts and visual information. Three of the principle additives of the visual images are texture, shape and color. Content based image retrieval from big sources has a wide scope in many application areas and software’s. To accelerate retrieval and similarity computation, the database images are analyzed and the extracted regions are clustered or grouped together with their characteristic feature vectors. As a result of latest improvements in digital storage technology, it's easy and possible to create and store the large quantity of images inside the image database. These collections may additionally comprise thousands and thousands of images and terabytes of visual information like their shape, texture and color. For users to make the most from those image databases, efficient techniques and mechanisms of searching should be devised. Having a computer to do the indexing primarily based on a CBIR scheme attempts to deal with the shortcomings of human-based indexing. Since an automated process on a computer can analyze and process the images at a very quick and efficient rate that human can never do alone. In this paper, we will discuss the structure of CBIR with their feature vectors.