Journal of Mathematical Sciences: Advances and ApplicationsAuthor's: Uday Pratap Singh and Sanjeev Jain
Pages: [217] - [226]
Received Date: December 09, 2009
Submitted by:
Searching test image from image databases using features extraction
from the content is currently an active research area. In this work,
we present novel feature extraction approaches for content-based
image retrieval, when the query image is color image. To facilitate
robust man-machine interfaces, we accept query images with color
attributes. Special attention is given to the similarity measure with
different distance matrices properties since the test image and object
image from database finding the distance measuring. Several applicable
techniques within the literature are studied for these conditions.
The goal of this paper is to present the user with a subset of images
that are more similar to the object image. One of the most important
aspects of the proposed methods is the accuracy measurement of the
query image with different database images. The method significantly
improves the feature extraction process and enables it, to be used
for other computer vision applications.
color image, image retrieval, Euclidean metrics, Manhattan metrics, correlation.
