On the Design of a Content based Image Retrieval System
Abstract
With the abundance of multimedia content on the World Wide Web, research and learning of effective
feature representation and similarity measures have become crucial. Image searching poses several
challenges. Lately, many researchers have been exploring the field. Automatic annotation of images
based on digital content processing proves to be an encouraging direction in the field. Content based
image retrieval system development is an emerging field. Accuracy of the results of semantic search
depends on the understanding of searcher’s purpose, the meaning of conditions imposed in the search
query and their mapping in the searchable data space. A visual content semantic search engine is
proposed in this paper. The search engine employs digital image features for searching the image
database. The presented algorithm produces promising results. The performance of our algorithm is
tested on an extensive set of tags and queries resulting in accurate and efficient results.
References
I.K. Sethi, I.L. Coman and D. Stan, "Mining association rules between
low-level image features and high-level concepts", Data Mining and
Knowledge Discovery: Theory, Tools and Technology III, vol. 4384,
pp. 279-290, 2001.
V.N. Gudivada and V.V. Raghavan, "Content based image retrieval
systems", Computer, vol. 28, no. 9, pp. 18-22, 1995.
C.H. Lin, R.T. Chen and Y.K. Chan, "A smart content-based image
retrieval system based on color and texture feature", Image and Vision
Computing, vol. 27, no. 6, pp. 658-665, 2009.
P.S. Hiremath and J. Pujari, "Content based image retrieval using color,
texture and shape features", Proc. of the 15th Int. Conf. on Advanced
Computing and Communications, IEEE, Guwahati, India, December
-21, 2007, California, pp. 780-784, 2007.
H. Yu, M. Li, H.J. Zhang and J. Feng, "Color texture moments for
content-based image retrieval", Proc. of the Int. Conf. on Image
Processing, Rochester, NY, USA, September 22-25, 2002, IEEE,
pp. 929-932, 2002.
Y. Liu, D. Zhang, G. Lu and W.Y. Ma, "A survey of content-based
image retrieval with high-level semantics", Pattern Recognition,
vol. 40, no. 1, pp. 262-282, 2007.
D. Papadias, M. Mantzourogiannis, P. Kalnis, N. Mamoulis and
I. Ahmad, "Content-based retrieval using heuristic search", Proc. of the
nd Annual International ACM SIGIR Conference on Research and
Development in Information Retrieval, SIGIR Berkeley, CA, USA,
August 15-19, 1999, New York: ACM, pp. 168-175, 1999.
J.S. De Bonet and P.A. Viola, "Structure driven image database
retrieval", Proc. of Conference on Advances in Neural Information
Processing Systems, Denver, CO, USA, December 2-4, 1997,
M.I. Jordan, M.J. Kearns, S.A. Solla, Eds. USA: MIT Press Cambridge,
pp. 866-872, 1997.
S. Surya and G. Sasikala, "Survey on content based image retrieval",
IJCSE, vol. 2, no. 5, pp. 691-696, 2011.
R.C. Veltkamp and M. Tanase, "Content-based image retrieval systems:
A survey", Utrecht University, Netherlands, pp. 1-62, 2002.
A.B. Gonde, S. Murala, S.K. Vipparthi, R. Maheshwari and
R. Balasubramanian, "3D Local Transform Patterns: A New Feature
Descriptor for Image Retrieval", Proc. of Int. Conf. on Computer Vision
and Image Processing, Roorkee, UP, India, September 9-12, 2017,
B.B Chaudhuri, M.S. Kankanhalli, B. Raman, Eds. Singapore:
Springer, pp. 495-507, 2017.
M.S. Lew, "Next-generation web searches for visual content",
Computer, vol. 33, no. 11, pp. 46-53, 2000.
K. Grauman, "Efficiently searching for similar images",
Communications of the ACM, vol. 53, no. 64, pp. 84-94, 2010.
E. Kim, X. Huang and J. Heflin, "Finding VIPs-A visual image persons
search using a content property reasoner and web ontology", Proc. of
IEEE Int. Conf. on Multimedia and Expo, ICME 2011, Barcelona,
Spain, July 11-15, 2011. New York: IEEE, pp. 1-7, 2011.
J. Wan, D. Wang, S.C.H. Hoi, P. Wu, J. Zhu, Y. Zhang and J. Li, "Deep
learning for content-based image retrieval: A comprehensive study",
Proc. of the 22nd ACM Int. Conf. on Multimedia, Orlando, FL, USA,
November 3-7, 2014. New York: ACM, pp. 157-166, 2014.
W. Adams, G. Iyengar, C.Y. Lin, M.R. Naphade, C. Neti, H.J. Nock
and J. R. Smith, "Semantic indexing of multimedia content using visual,
audio and text cues", EURASIP J. Adv. Sig. Pr., vol. 2003, no. 2,
pp. 170-185, 2003.
A.S. Barb and C.R. Shyu, "Visual-semantic modeling in content-based
geospatial information retrieval using associative mining techniques",
IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 1, pp. 38-42,
V. Murthy, E. Vamsidhar, J.S. Kumar and P.S. Rao, "Content based
image retrieval using Hierarchical and K-means clustering techniques",
IJEST, vol. 2, no. 3, pp. 209-212, 2010.
P. Srivastava and A. Khare, "Integration of wavelet transform, local
binary patterns and moments for content-based image retrieval", J. Vis.
Commun. Image R., vol. 42, pp. 78-103, 2017.
L. Piras and G. Giacinto, "Information fusion in content based image
retrieval: A comprehensive overview", Inform. Fusion, vol. 37,
pp. 50-60, 2017.
Y. Mistry, D. Ingole and M. Ingole, "Content based image retrieval
using hybrid features and various distance metric", Journal of Electrical
Systems and Information Technology, vol. 5, no. 3, pp. 1-15, 2017.
Y. Liu, D. Zhang and G. Lu, “SIEVE– Search images effectively
through visual eliminationâ€, Proc. of Int. Workshop on Multimedia
Content Analysis and Mining, Weihai, China, June 30- July 1, 2007,
N. Sebe, Y. Liu, Y. Zhuang, Th. S. Huang, Eds. Berlin: Springer,
pp. 381-390, 2007.
S.-F. Chang, W.-Y. Ma and A. Smeulders, "Recent advances and
challenges of semantic image/video search", Proc. of IEEE Int. Conf.
on Acoustics, Speech and Signal Processing, Honolulu, HI, USA,
April 15-20, 2007, New York, pp. IV-1205-IV-1208, 2007.
M. Batko, F. Falchi, C. Lucchese, D. Novak, R. Perego, F. Rabitti, J.
Sedmidubsky and P. Zezula, "Building a web-scale image similarity
search system", Multimedia Tools and Applications, vol. 47, no. 3,
pp. 599-629, 2010.
D.G. Thakore and A. Trivedi, "Content based image retrieval
techniques–Issues, analysis and the state of the art", Proc. of the Int.
Symp. on Computer Engineering & Technology, Mandi Gobindgarh,
Punjab, India (March 19-20, 2010), pp. 1-5, 2010.
Y.L. Lin and M.J.J. Wang, “Automated body feature extraction from
D imagesâ€, Expert Systems with Applications, vol. 38, no. 3, pp. 2585-
, March 2011.
P.M. Szczypiński, M. Strzelecki, A. Materka and A. Klepaczko,
“MaZda– A software package for image texture analysisâ€, Comp. Meth.
Prog. Bio., vol. 94, no. 1, pp. 66-76, April 2009.
M.F. Porter, "An algorithm for suffix stripping", Program, vol. 14,
no. 3, pp. 130-137, 1980.