International Journal of Information Engineering and Electronic Business(IJIEEB)
ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)
Published By: MECS Press
IJIEEB Vol.7, No.3, May. 2015
An Approach for Effective Image Retrievals Based on Semantic Tagging and Generalized Gaussian Mixture Model
Full Text (PDF, 541KB), PP.39-44
The present day users navigate more using electronic gadgets, interacting with social networking sites and retrieving the images of interest from the information groups or similar groups. Most of the retrievals techniques are not much effective due to the semantic gap. Many models have been discussed for effective retrievals of the images based on feature extraction, label based and semantic rules. However effective retrievals of images are still a challenging task, model based techniques together with semantic attributes provide alternatives for efficient retrievals. This article is developed with the concepts of Generalized Gaussian Mixture Models and Semantic attributes. Flicker dataset is considered to experiment the model and efficiency is measured using Precision and Recall.
Cite This Paper
Anuradha. Padala, Srinivas. Yarramalle, Krishna Prasad. MHM,"An Approach for Effective Image Retrievals Based on Semantic Tagging and Generalized Gaussian Mixture Model", IJIEEB, vol.7, no.3, pp.39-44, 2015. DOI: 10.5815/ijieeb.2015.03.06
Ramadass Sudhir, S. Santhosh Baboo, "A Efficient Content based Image Retrieval System using GMM and Relevance Feedback", International Journal of Computer Application, Vol. 72-Number 22,2013.
Shanmugapriya, N. and R. Nallusamy, "A NEW CONTENT BASED IMAGE RETRIEVAL SYSTEM USING GMM AND RELEVANCE FEEDBACK", Journal of Computer Science, Vol.10, Issue-2, pp. 330-340.
Eskicioglu M.A and Fisher P.S (1995) "Image Quality Measures and their Performance", IEEE Transactions on Communications, Vol.43, No.12.
Sumiti Bansal Er. Rishamjot Kaur, "A Review on Content Based Image Retrieval using SVM", International Journal of Advanced Research in Computer Science and Software Engineering, Vol.4, Issue-7, pp. 232-235, July 2014.
Jia Li, "Linear Discriminant Analysis", URL: http://sites.stat.psu.edu/~jiali/course/stat597e/notes2/lda.pdf 10/09/2014 2:36 PM.
D.Santhosh, Tina Esther Trueman, "Artificial Neural Network Technique for CBIR Based On Query Image Feature Extraction", International Journal of Innovative Research in Computer and Communication Engineering, Vol.2, Special Issue-3, July 2014.
Sílvio M. Duarte Queirós, Nuno Crokidakis, and Diogo O. Soares-Pint, "Effect of platykurtic and leptokurtic distributions in the random-field Ising model: Mean-field approach", Phys. Rev. E 80, 011143 – Published 30 July 2009.
Nikhil R Pal and Sankar K Pal, "A Review On Image Segmentation Techniques", Pattern Recognition, Vol. 26, Issue.9, pp 1277-1294, 1993.
Y. Srinivas, "An Efficient Approach for Medical Image Segmentation Based on Truncated Skew Gaussian Mixture Model using K-Means Algorithm", International Journal of Computer Science and Telecommunications, Vol. 2, Issue 6, pp 81-88, Sep 2011.
Yarramalle, Srinivas; Rao, K. Srinivas, "Unsupervised image segmentation using finite doubly truncated Gaussian mixture model and hierarchical clustering", Journal of Current Science, Vol. 93, Issue. 4, pp 507, 2007.
S.Najimun Nisha, Mrs.K.A.Mehar Ban, "An Enhanced Image Retrieval Using K-Mean Clustering Algorithm in Integrating Text and Visual Features", International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 1,pp 10-15, March 2014.
Cheng, "Color Image Segmentation:Advances and Prospects", Pattern Recognition, Vo1.34, pp2259-2281, 2001.
D. Martin, C. Fowlkes,D. Tal, and J.Malik "A database of human Segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics", in proceedings of 8th International Conference on Computervision, vol.2, pp.416-423, 2006.
T. Yamazaki, Tatsuya Yamazaki, "Introduction of EM Algorithm into Color Image Segmentation", CiteSeer, Venue: Proc. ICIPS'98.
Jeff A.Bilmes, "A Gentle Tutorial of the EM Algorithm and its application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models", Technical Report, University of Berkeley, ICSI-TR-97-021, 1997.
Lie. T, Sewehand.W, "Statistical approach to X-ray CT imaging and its applications in image analysis", IEEE Trans. Med. Image. Vol.11, No.1, pp 53-61, 1992.
Kelly. P.A, "Adaptive segmentation of speckled images using a hierarchical random field model". IEEE Transactions Acoust. Speech. Signal Processing, Vol.36, No.10, pp.1628-1641, 1988.
Mclanchlan G, Krishnan T, "The EM Algorithm and Extensions", John Wiley and Sons, New York -1997.
Mclanchlan G, Peel.D, "The EM Algorithm For Parameter Estimations", John Wiley and Sons, New York -2000.
Vishal Jain, Dr. Mayank Singh, "Ontology Based Information Retrieval in Schematic Web: A Survey", I.J. Information Technology and Computer Science, No.10, pp 62-69, 2013.
Hadi A. Alnabriss, Ibrahim S.I. Abuhaiba, "Improved Image Retrieval With Color And Angle Representation", I.J. Information Technology and Computer Science, No.06, pp 68-81, 2014.