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Advanced Sketch Based Image Retrieval System Using Object Boundary Selection Algorithm

Authors(2):

Aishwarya Deore, Dr. B. L. Gunjal
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In recent era for some cases, colorful image retrieval on the basis of their sketches is area of interest as far as image processing is concern. In image retrieval process sketch of particular image is given as an input and its colorful image is expected as an output. Problem of sketch and actual image matching is that there is appearance gap between them. This gap is due to noise in edges of photo realistic images. Hence our proposed process considers these issues in Sketch Based Image Retrieval process. Our system eliminates the impact of noise in edges of photo realistic images. Our proposed process is based on histogram of line relationship (HLR) descriptor. We proposed “Object boundary selection” algorithm that followed by HLR. In our system we mainly contributing that, matching process is done on Hadoop using Map-reduce technique.

Aishwarya Deore, Dr. B. L. Gunjal

Sketch Based Image Retrieval, histogram of line relationship, object boundary selection, Hadoop, Map-reduce

  1. Shu Wang, Jian Zhang, Tony X. Han, and Zhen jiang Miao, "Sketch-Based Image Retrieval Through Hypothesis-Driven Object Boundary Selection With HLR Descriptor" vol. 17, no. 7,pp. 1045-1057 , july 2015
  2. Baisa L Gunjal and Suresh N Mali,"MEO based secured, robust, high capacity and perceptual quality image watermarking in DWTSVD domain", SpringerPlus,pp 1-16 ,2015.
  3. K. Bozas and E. Izquierdo, Large scale sketch based image retrieval using patch hashing, Adv. Visual Comput., vol. 7431, ,pp. 210-219, 2012.
  4. R. Zhou, L. Chen, and L. Zhang, "Sketch-based image retrieval on a large scale database", in Proc. 20th ACM Int. Conf. Multimedia, ,pp. 973-976, 2012
  5. M. Eitz, K. Hildebrand, T. Boubekeur, and M. Alexa, "A descriptor for large scale image retrieval based on sketched feature lines", in Proc.6th Eurograph. Symp. Sketch-Based Interfaces Modeling , pp. 29-36,,2009.
  6. Baisa L. Gunjal , Suresh N. Mali ,"Insight into New Color Image Watermarking With DWT-DCT and only DCT with Comparative Analysis in YIQ Color Space", International Journal of Advanced Research in Computer Science,Volume 3, No. 3, pp.493 May-June 2012.
  7. R. Hu and J. Collomosse, "A performance evaluation of gradient field hog descriptor for sketch based image retrieval", Comput. Vis. Image-Understand., vol. 117, no. 7, pp. 790-806, 2013,
  8. M. Eitz, K. Hildebrand, T. Boubekeur, and M. Alexa, "Sketch-based image retrieval: Benchmark and bag-of-features descriptors", IEEE Trans. Vis. Comput. Graph. vol. 17, no. 11, ,pp. 1624-1636, Nov. 2011
  9. P. Sousa and M. J. Fonseca, "Sketch-based retrieval of drawings using spatial proximity " , J. Vis. Languages Comput., vol. 21, no. 2, pp. 69-80, 2010.
  10. R. Hu, T. Wang, and J. Collomosse, "A bag-of-regions approach to sketch-based image retrieval", in Proc. IEEE Int. Conf. Image Process, pp. 3661-3664, Sep. 2011.
  11. O. Chum, J. Philbin, J. Sivic, M. Isard, and A. Zisserman," Total recall: Automatic query expansion with a generative feature model for object retrieval", in Proc. IEEE Int. Conf. Comput. Vis.,pp. 18. Oct. 2007
  12. T. Menp and M. Pietikinen, , J. Bigun and T. Gustavsson, Eds, "Multiscale binary patterns for texture analysis, in Image Analysis", ser. Lecture Notes Comput. Sci.. Berlin, Germany: Springer-Verlag, vol. 2749, pp. 885-892.,2003,
  13. C. Ma, X. Yang, C. Zhang, X. Ruan, M.-H. Yang, and O. "Coporation,Sketch retrieval via dense stroke features", in Proc. Brit. Mach. Vis.Conf. , vol. 2, pp.165. 2013
  14. Y. Cao, C. Wang, L. Zhang, and L. Zhang, "Edgel index for large-scale sketch-based image search", in Proc. IEEE Conf. Comput. Vis. Pattern Recogn., pp. 761-768,June 2011.
  15. Baisa L Gunjal and Suresh N Mali "Strongly Robust and Highly Secured DWT-SVD Based Color Image Watermarking: Embedding Data in All Y, U, V Color Spaces", I.J. Information Technology and Computer Science,NO. 3, PP.1-7, 2012.
  16. C. L. Zitnick," Binary coherent edge descriptors", in Proc. 11th Eur.Conf. Comput. Vis.: Part II, pp. 170-182,2010
  17. J. Philbin, M. Isard, J. Sivic, and A. Zisserman, "Descriptor learning for efficient retrieval", in Proc. 11th Eur. Conf. Comput. Vis. Conf. Comput. Vis.: Part III, vol. 6313, pp. 677-691, 2010.
  18. J. Canny," A computational approach to edge detection", IEEE Trans.Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679-698, Nov.1986.
  19. S. Parui and A. Mittal, "Similarity-invariant sketch-based image retrieval in large databases", in Proc. 13th Eur. Conf. Comput. Vis. Conf. Comput. Vis, vol. 8694, pp. 398-414., .2014
  20. E. Shechtman and M. Irani, "Matching local self-similarities across images and videos," in Proc. IEEE Conf. Comput. Vis. Pattern Recogn., Jun. 2007, pp. 1–8

Publication Details

Published in : Volume 2 | Issue 4 | July-August - 2016
Date of Publication Print ISSN Online ISSN
2016-08-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
233-240 IJSRSET162460   Technoscience Academy

Cite This Article

Aishwarya Deore, Dr. B. L. Gunjal, "Advanced Sketch Based Image Retrieval System Using Object Boundary Selection Algorithm ", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.233-240, July-August-2016.
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