Recently, as web and various databases contain a large number of images, CBIR (content-based image retrieval) are greatly
used. This paper proposes an image retrieval system using color-spatial information from the applications. First, we suggest two kinds of
the indexing keys to prune away the irrelevant images to given query images using MCS (Major Color Set) and DBS (Distribution Block
Signature). MCS’s are related to color information while, DBS’s are related to spatial information respectively. After successively
applying these filters to a large database, we get only a small amount of high potential candidates that is somewhat similar to that of
query images. We propose to use QM (quad modeling) method to set the initial weight of 2-dimensional cell in the query image
according to each major color and retrieve more similar images through similarity association function associated with the weights.
Finally, we evaluated the system’s efficiency by statistically how many images were expected to be filtered out during the first and
second filtering processes.
Published In:IJCSN Journal Volume 6, Issue 3
Date of Publication : June 2017
Pages : 351-355
Tables : --
V.Subha : is currently working as an Assistant professor in RGCET in
department of computer science, puducherry, India. Her research interests
include image, video processing, computer vision, big data and
Content-Based Image Retrieval, Major Color Set, Global Color Signature, Distribution Block Signatures, Quad Modeling,
Hue Saturation Value
In this work, we used signature based on the color, spatial
approach for addressing the content based image retrieval
problem. The chosen MCS, GCS and DBS color signature
in the approach is used for efficient retrieval of an image.
Further, in this work, we used an HSV color model to
represent an image. We have studied and implemented the
system up to the first step of QM modeling in VB.Net
Environment. In future, similarity measure for QM matrix
can be calculated to better capture the amount of overlap
between query and database images. Further for accurate
retrieval, the relevance feedback approach can be
incorporated and performance of the system using
precision and recall measures can be used for evaluation.
1. Swain .M & Ballard “Color indexing”, International
journal of computer vision, 7(1), 11-32, (1991).
2. Anil k. Jain “Image retrieval using color and shape”,
Pattern recognition society, 1233-1244, (1995).
3. Liu.Picard “Periodicity, Directionality, and Randomness:
World Features For Image Modeling And Retrieval”. IEEE
Transaction On Pattern Analysis And Machine
Intelligence, 18(7), 722-733, (1996). 4. Smith J. R, “Integrated spatial and feature image query”,
Pattern Analysis and Multimedia system, 7(2), 129-140,
5. Kian-Lee, C.S.,Ma “Information Embedding Base On
Users Relevance Feedback Technique in CBIR”. Pattern
Analysis and Application, 3486, 294-304, (1999).
6. John p. Eakins, “Towards Intelligent Image Retrieval”,
Pattern recognition, 35, 3-14, (2001).
7. Hun Woo Yoo, “Visual Information Retrieval System Via
Content-Based Approach” Pattern Recognition, 35(3),
8. Hun-woo, Yoo, “Expert system for color image retrieval.”
Expert System With Application, 28, 347-357 (2004).
9. Dengsheng Zhang, “Region Based Image Retrieval with
High –Level Semantics Using Decision Tree Learning”,
Pattern recognition, (2008)
10. Quynh Nguyen Huu1 , Ha Nguyen Thi Thu1 and Tao Ngo
Quoc2 “An Efficient Content Based Image Retrieval
Method For Retrieving Images”ICIC International, 1349-
11. Priyanka Shinde, Anushka Sinkar , Mugdha Toro ,
Prof.Shrinivas Halhalli “Image Retrieval Based on its
Contents Using Features Extraction “International Research
Journal of Engineering and Technology (IRJET) e-ISSN:
2395-0056 Volume: 03 Issue: 01 Jan (2016)
12. Mohammad Sadeq Navabi* Zahra Ahmadi Brooghani
“Content-Based Image Retrieval through Combined Data of
Color Moment and Texture Mohammad” IJCSNS
International Journal of Computer Science and Network
Security, VOL.17 No.2, February (2017).
All rights reserverd @ IJCSN International Journal www.IJCSN.org