The aim concerning this chapter search out propose an efficient recovery method that can save appropriate information from the gigantic accumulations of images employed in heterogeneous uses which has a pronounced affect retrieval act when compared to standard and established Gabor filter methods. In recent times, skilled is a magnificent mechanics progression in the research area had connection with image recovery, in specific the Query By Image Content (QBIC) structure. Retrieval of information has become a very disputing area of research in miscellaneous applications like databases related to combined use of several media, Google retrieval and mathematical libraries. The study grown a hybrid QBIC retrieval whole that depicts the impact of PSO on recovery performance in QBIC arrangement by retrieving color features, feeling features and shape appearance of the images in three consecutive stages. In the submitted technique, color facial characteristics are initially derived using a color histogram. In the following step, Log Gabor filters are brought into harmony using Particle Swarm Optimization (PSO), saving the texture characteristics. The origin of shape features is achieved by using a polygonal fitting method. When compared to the current standard systems, the submitted method shows a superior recovery rate in terms of mean recall and mean accuracy. The novelty is that it can exploit global minima countenance that result in extreme accuracy without moving the computation.
Author(s) Details:
D. Madhavi,
Department of EECE, GITAM Deemed to be
University, Visakhapatnam, Andhra Pradesh, India.
N.
Jyothi,
Department
of EECE, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India.
Please see the link here: https://stm.bookpi.org/RHST-V3/article/view/10755
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