Open AccessCBIR Using Slant Transform Using DC & AC Coefficients
Author(s) -
N. Sravani,
K. Veera Swamy
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.6.15042
Subject(s) - pattern recognition (psychology) , image retrieval , artificial intelligence , feature (linguistics) , computer science , content based image retrieval , block (permutation group theory) , image (mathematics) , feature vector , image texture , brightness , computer vision , mathematics , image processing , philosophy , linguistics , physics , geometry , optics
In the CBIR- (Content Based Image Retrieval) technique requires low-level or primitive features- color, texture, or other data that can be taken from its image Extracting feature vectors of database images as well as query image can be calculated with the help of slant transform by considering DC & 3 AC coefficients obtained in each block of an image. Slant transform represents the gradual brightness changes in an image line effectively. By calculating the difference between feature vector data base and feature vector for a query by using the distance measuring techniques. The vector of the smaller distance is the closest to query image. The experiment is performed in the Corel 500 Image Database. Finally, CBIR results are evaluated by the recall, precision, and F-Score.