CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Image Retrieval using Entropy

by NST Sai, R. C. Patil
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 24 - Number 8
Year of Publication: 2011
Authors: NST Sai, R. C. Patil
10.5120/2992-3901

NST Sai, R. C. Patil . Image Retrieval using Entropy. International Journal of Computer Applications. 24, 8 ( June 2011), 42-49. DOI=10.5120/2992-3901

@article{ 10.5120/2992-3901,
author = { NST Sai, R. C. Patil },
title = { Image Retrieval using Entropy },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 24 },
number = { 8 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume24/number8/2992-3901/ },
doi = { 10.5120/2992-3901 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:10:29.544851+05:30
%A NST Sai
%A R. C. Patil
%T Image Retrieval using Entropy
%J International Journal of Computer Applications
%@ 0975-8887
%V 24
%N 8
%P 42-49
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content based image retrieval address the problem of retrieving images relevant to the user needs from image databases on the basis of low-level visual features that can be derived from the images. Grouping images into meaningful categories to reveal useful information is a challenging and important problem. This paper represent effective approaches for Content Based Image Retrieval (CBIR) that represent each image in the database by feature vector computed by using entropy of sub block of bit plane image. This paper present four method for calculating the feature vector of image .All the proposed methods tested on image database which include 800 images with 8 classes. Euclidean distance is used for similarity measure. Performance of each method calculated by using overall average precision and overall average recall for comparison of proposed method. Overall precision and overall recall computed using 40 queries on the image database. It is found that as the image divide into more sub block the performance goes on increasing.

References
  1. NST Sai, R.C. Patil ,”Average Row and Column Vector Wavelet Transform for CBIR”, Second international conference on Advance in Computer Vision and Information Technology (ACVIT2009),Aurangabad, India.
  2. NST Sai, , R.C. Patil,”New Feature Vector for Image Retrieval Walsh Coefficients”, Second international conference on Advance in Computer Vision and Information Technology (ACVIT2009),Aurangabad, India.
  3. NST Sai, , R.C. Patil,”Image Retrieval using DCT Coefficients of Pixel Distribution and Average Value of row and Column Vector ”IEEE International Conference on Recent Trends in Information ,Telecommunication and Computing(ITC2009),Kochi, Kerala, India.
  4. NST Sai, , R.C. Patil,” Moments of Pixel Distribution of CBIR” International Conference and Workshops on Emerging Trends in Technology (ICWET2010),Mumbai, India.
  5. NST Sai, Ravindra patil ,”New Feature Vector for Image Retrieval: Sum of the Value of Histogram Bins ”IEEE Conference on Advance in Computing, Control & Telecommunication Technologies (ACT2009),Trivandrum, India.
  6. NST Sai, , R.C. Patil,”Image Retrival usng Equalized Histogram Image Bins Moment” Inter national Joint Journal Conference in Engneering ,IJJCE,2010,Trivandrum,India.
  7. R.C. Gonzalez, and R.E. Woods, Digital Image Processing 2nd ed.,Prentice Hall, Inc., New Jersey, 2002.
  8. K.C. Ting,D.B.L.Bong,Y.C.Wang,"Performance Analysis of Single and Combined Bit-Planes Feature Extraction for Recognition in Face Expression Database ", Proceedings of the International Conference on Computer and Communication Engineering 2008,May 13-15, 2008 Kuala Lumpur, Malaysia .
  9. Guoping Qiu, “Colour Image Indexing Using BTC”, IEEE Transition on Image Processing, vol. No 12,.Janauary 2003.
  10. Pdamshree Suresh,RMD Sundaram,Aravindhan Arumugam,” Feature Extraction in Compressed Domain for Content Based Image Retrieval ”,International Conference on Advanced Computer Theory and Engineering.2008.
  11. H.B.Kekre, Sudeep D. Thepade, Archana Athawale, Anant Shah, Prathamesh Verlekar, Suraj Shirke, “Walsh Transform over Row Mean and Column Mean using Image Fragmentation and Energy Compaction for Image Retrieval”, International Journal on Computer Science and Engg.(IJCSE),Volume 2S, Issue1, January 2010.
  12. H.B.Kekre, Sudeep D. Thepade, Archana Athawale, Anant Shah, Prathmesh Verlekar, Suraj Shirke, “Image Retrieval using DCT on Row Mean, Column Mean and Both with Image Fragmentation”, (Selected), ACM-International Conference and Workshop on Emerging Trends in Technology (ICWET 2010), TCET, Mumbai, 26-27 Feb 2010, The paper will be uploaded on online ACM Portal.
  13. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker, “Query by Image and Video Content: The QBIC System”, IEEE Computer, 28(9):23–32, Sept. 1995.
  14. A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, “Content-based image retrieval at the end of the early years,” IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI), 22(12):1349–1380, Dec. 2000.
  15. K. Hirata and T. Kato, ªQuery by Visual Example,” Advances in Database Technology EDBT '92, Third Int'l Conf. Extending Database Technology, 1992.
  16. W.Y. Ma and B.S. Manjunath, “Pictorial Queries: Combining Feature Extraction with Database Search,” Technical Report 18, Dept. of Electrical Eng., Univ. of California at Santa Barbara, 1994.
  17. W.Y. Ma and B.S. Manjunath, “Pictorial Queries: Combining Feature Extraction with Database Search,” Technical Report 18, Dept. of Electrical Eng., Univ. of California at Santa Barbara, 1994.
  18. A. Gupta and R. Jain, ªVisual Information Retrieval,” Comm. ACM, vol. 40, no. 5, 1997.
  19. C.E. Jacobs, A. Finkelstein, and D.H. Salesin, “Fast Multiresolution Image Querying,” Proc. SIGGRAPH 95, 1995.
  20. W.J.Z. Wang, G. Wiederhold, O. Firschein, and S.X. Wei, “Wavelet Based Image Indexing Techniques with Partial Sketch Retrieval Capability,” J. Digital Libraries, 1997.
  21. Seung Jun-Lee, Yong-Hwan Lee, Hyochang Ahn, Sang Burm Rhee, “Color image descriptor using wavelet correlogram,” The 23rd international conference on Circuits/systems, computers and communication, 2008.
  22. A Gupata and R. Jain, “Visual Information Retrieval,” Comman. ACM, vol.40, no.5, 70- 79, 1997.
  23. M.Mohammed Sathik,"Feature Extracton on ColorED x-Ray Images by Bit-plane Slicing Technique",International Journal of Engineering Science and Technology Vol. 2(7), 2010, 2820-2824.
  24. Govind Haldankar, Atul Tikare and Jayprabha Patil, “Converting Gray Scale Image to Color Image” in Proceedings of SPIT-IEEE Colloquium and International Conference, Mumbai, India, Vol. 1, 189.
  25. Pratt W.K., Digital image processing, A Wiley Interscience Publication, 1991.
  26. N.Ravia Shabnam Parveen, Dr. M.Mohamed Sathik, “Feature Extraction by Bit Plane Slicing Technique”, in International Journal of Computing, Communication and Information System, Volume 1.
  27. M. K. Mandal, T. Aboulnasr, and S. Panchanathan,, “Image Indexing Using Moments and Wavelets”, IEEE Transactions on Consumer Electronics, Vol. 42, No. 3, August 1996.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR Entropy Bit Plane Image Sub block Precision Recall Euclidean Distance

Powered by PhDFocusTM