Call for Paper - August 2022 Edition
IJCA solicits original research papers for the August 2022 Edition. Last date of manuscript submission is July 20, 2022. Read More

Image Similarity Measurement using Shape Feature

IJCA Proceedings on National Conference on Advances in Communication and Computing
© 2015 by IJCA Journal
NCACC 2015 - Number 1
Year of Publication: 2015
Shweta R. Patil
V. S. Patil

Shweta R Patil and V s Patil. Article: Image Similarity Measurement using Shape Feature. IJCA Proceedings on National Conference on Advances in Communication and Computing NCACC 2015(1):6-9, September 2015. Full text available. BibTeX

	author = {Shweta R. Patil and V.s. Patil},
	title = {Article: Image Similarity Measurement using Shape Feature},
	journal = {IJCA Proceedings on National Conference on Advances in Communication and Computing},
	year = {2015},
	volume = {NCACC 2015},
	number = {1},
	pages = {6-9},
	month = {September},
	note = {Full text available}


In this paper, we describe an incipient method for image retrieval predicated on the local invariant shape feature, designated scalable shape context. The feature utilizes the Harris-Laplace corner to locat the fix points and coinside scale in the animal and flower image. Then, we utilize shape context to explain the local shape. Correspondence of feature points is achieved by a weighted bipartite graph matching algorithm and the homogeneous attribute between the query and the indexing image is presented by the match cost. The practical results show that our method is efficient than shape context and SIFT for the animal and flower image retrieval.


  • C. T. Zahn and R. Z. Roskies. Fourier descriptors for plane closed curves. IEEE Transactions on Computers, 1972.
  • C Teh, R Chin. On image analysis by the methods of moments. IEEE Transaction pattern analysis 1988, 10(4):254-266.
  • C. Harris and M. Stephens. A combined corner and edge detector of the 4th alvey vusion conference, 1988, pp: 147-151.
  • Jacobs C E. Fast multi-resolution image querying, proceeding of SIGGAPH, 1995,227-286 .
  • F Mokhtarian, S Abbasi, L Kittler. Efficient and robust retrieval byshape content through curvature scale space. Processing international workshop on image databased and multi-media search 1996,pp:35-42.
  • S Liao, M Pawlak. On image analysis by moments. IEEETransactions Pattern Analysis and Machine Intelligence,1996,18(3):254-266.
  • S. Belongie, J. Malik, and J. Puzicha, Shape Matching and Object Recognition Using Shape Contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002,24 (24): 509-521.
  • K Mikolajczyk, C Schmid. Scale& affine invariant interesting pointdetectors. International Journal of Computer Vision. 2004,60(1).
  • Dong Liu, Xiaoyan Sun, Feng Wu, Shipeng Li, Ya Qin Zhang, Image compression with edge-based inpainting. IEEE Transactions on Circuits and Systems for Video Technology, 2007,17 (10), pp: 1273–1287.
  • SongHai Zhang, Tao Chen, YiFei Zhang, ShiMin Hu and Ralph R . Martin. Vectorizing Cartoon Animations. IEEE Transactions on Visualization and Computer Graphics, 2009,15 (4).
  • Yang Ping, Wang GuoZhao. Unbiased curvilinear structure extraction for cartoon images. Eighth International Symposium on Voronoi Diagrams in Science and Engineering, 2011, pp:220–227.