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Reseach Article

A Methodology for Sketch based Image Retrieval based on Score level Fusion

by Y.jhansi, E.sreenivasa Reddy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 3
Year of Publication: 2015
Authors: Y.jhansi, E.sreenivasa Reddy
10.5120/19167-0629

Y.jhansi, E.sreenivasa Reddy . A Methodology for Sketch based Image Retrieval based on Score level Fusion. International Journal of Computer Applications. 109, 3 ( January 2015), 9-13. DOI=10.5120/19167-0629

@article{ 10.5120/19167-0629,
author = { Y.jhansi, E.sreenivasa Reddy },
title = { A Methodology for Sketch based Image Retrieval based on Score level Fusion },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 3 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number3/19167-0629/ },
doi = { 10.5120/19167-0629 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:48.829113+05:30
%A Y.jhansi
%A E.sreenivasa Reddy
%T A Methodology for Sketch based Image Retrieval based on Score level Fusion
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 3
%P 9-13
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Retrieving sketches to match with a hand drawn sketch query is highly desired feature. This paper proposes a novel methodology for efficient retrieval of sketch based images. This system extracts features from the query sketch, HOG and GMM features are used and these features are combined using score level fusion which can match user drawn sketch with database sketches efficiently. The methodology is tested on bench mark images and the performance evaluation is carried out using metrics like Precession and Recall. The results derived are tested for efficiency against models based on HOG and GMM.

References
  1. Y. Cao, C. Wang, L. Zhang and L. Zhang, "Edgel Index for Large-Scale Sketch Based Image Search". In CVPR, pages 761- 768, 2011.
  2. R. Hu, M. Barnard and J. Collomosse, "Gradient Field Descriptor for sketch based and Localization". In ICIP, pages 1025- 1028, 2010.
  3. W. H. Leung and T. Chen, "User –independent retrieval of free-form hand-drawn sketches". In Proc. of IEEE ICASSP,vol. 2,pp. 2029-2032, may 2002.
  4. Chao Ma,Xiaokang Yang,Chongyang Zhang, Xiang Ruan, Ming-Husan Yang, "Sketch retrieval via dense strokes", In BMVC(2013).
  5. M. Eitz, R. Richter, T. Boubekeur, K. Hildebrand and M. Alexa, "Sketch-Based Shape Retrieval". In SIGGRAPH (2012).
  6. Wing Ho Leung and Tsuhan Chen, "Retrieval of Hand Drawn Sketches with partial matching", Acoustics, Speech and signal processing, 2003, Proc (ICASSP'03), IEEE International conference vol. 3 pages III 5-8.
  7. Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur and Marc Alexa, "A descriptor for large scale image retrieval based on sketched feature lines", In proc. The sixth Eurographics symposium on sketch based interfaces and modeling, New Orleans, pp. 29-36, Aug 2009.
  8. Datta. R, Joshi D, Jia Li and James Z. Wang, "Image retrieval: Ideas, influences and trends of the New Age", In ACM computing Surveys 40,2(2008),1-60.
  9. M. Eitz, K. Hildebrand, T. Boubekeur and M. Alexa, "An evaluation of descriptors for large-scale image retrieval from Sketched feature lines", in Computers & Graphics, 2010.
  10. Chalechale . A,Naghdy G,Mertins A, "Sketch –based image matching using angular partitioning",IEEE Transactions on systems,Man and Cybernetics, Part A 35,1(2005).
  11. Anoop M. Namboodri,Anil K. Jain, "Retrieval of On- line Hand-Drawn Sketches" ,In ICPR'04 Proc. of pattern recognition Vol 2. pages 642-645.
  12. Kai-Yu Tseng, Yen-Liang Lin, Yu-Hsiu Chen, Winston H. Hsu, "Sketch-based image retrieval on mobile devices using compact hash bits",proc. of the 20th ACM international conference on multimedia, 2012 pages 913-916.
  13. Feifei CUI, Gongping YANG, "Score level Fusion of Fingerprint and Finger vein Recognition", Journal of Computational information systems 7:16(2011)5723-5731.
  14. A. K. Jain,K. Nandakumar,A. Ross,"Score normalization in multimodal biometric systems",In pattern recognition ,vol. 38,no. 12,pp. 2270-2285,2005
  15. N. Dalal and B. Triggs ,"Histogram of Oriented gradients for human detection",In CVPR,pages 886- 893,2005.
  16. Z. Robotka and A. Zempleni, "Image retrieval using GaussianMixtureModels",Annals Univ. Sci. Budapest, Sect. Comp,vol. 31,(2009),pp. 93-105.
  17. Jacob Goldberger, Shiri Gordon, Hayit Greenspan, "An efficient Image similarity Measure based on a Approximations of KL divergence Between Two Gaussian Mixtures",In proc. of ICCV 2003, Nice, October 2003,vol. 1,pp. 487-493.
  18. Vedaldi and B. Fulkerson. VLFeat: An open and portable library of computer vision algorithms. http://www. vlfeat. org/,2008.
  19. L. Zhang. , F. Lin. , and B. Zhang. "Support vector machine learning for image retrieval". Proc. IEEE Int. Conf. on Image Processing, vol. 2, pp. 721-724, 2001.
  20. J. Li, Amir Najmi. , and Robert M. Gray. "Image classification by a two-dimensional hidden Markov model". IEEE Transactions on Signal Processing, 48(2),517-533,Feb 2000.
  21. S. Hussain, "Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network", In Emerging Trends and Applications in Information Communication Technologies, pp. 501-511, 2012.
  22. N. Nikvand and Z. Wang, "Generic image similarity based on kolmogorov complexity", In IEEE International Conference on Image processing(ICIP), 2010 pp. 309-312.
  23. Ajita Rattani, Nitin Agarwal, Hunny Mehrotra and P. Gupta, "An Efficient fusion based classifier", in proceedings of Workshop on computer vision, Graphics and Image processing(WCVGIP), Hyderabad,2006
Index Terms

Computer Science
Information Sciences

Keywords

HOG GMM Sketch based images fusion performance evaluation.