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Semantic Gap in CBIR: Automatic Objects Spatial relationships Semantic Extraction and Representation
Hui Hui Wang, Dzulkifli Mohamad, N. A. Ismail
Pages - 192 - 204     |    Revised - 30-06-2010     |    Published - 10-08-2010
Volume - 4   Issue - 3    |    Publication Date - July 2010  Table of Contents
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KEYWORDS
Semantic Gap, Objects Spatial Relationships semantic, Automatic Image Semantic Extraction, Image Retrieval
ABSTRACT
The explosive growth of image data leads to the need of research and development of Image retrieval. Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users’ mind. This paper is proposed a novel technique for objects spatial relationships semantics extraction and representation among objects exists in images. All objects are identified based on low level features extraction integrated with proposed line detection techniques. Objects are represented using a Minimum Bound Region (MBR) with a reference coordinate. The reference coordinate is used to compute the spatial relation among objects. There are 8 spatial relationship concepts are determined: “Front”, “Back”, “Right”, “Left”, “Right-Front”, “Left-Front”, “Right-Back”, “Left-Back” concept. The user query in text form is automatically translated to semantic meaning and representation. Besides, the image similarity of objects spatial relationships semantic has been proposed.
CITED BY (2)  
1 Abdulbaqi, h. a., sulong, g., & hashem, s. h. (2014). a sketch based image retrieval: a review of literature. journal of theoretical and applied information technology, 63(1).
2 Kyriazos, G. K., Gerostathopoulos, I. T., Kolias, V. D., Stoitsis, J. S., & Nikita, K. S. (2011, August). A semantically-aided approach for online annotation and retrieval of medical images. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE (pp. 2372-2375). IEEE.
1 Google Scholar 
2 Academic Index 
3 refSeek 
4 iSEEK 
5 Socol@r  
6 Bielefeld Academic Search Engine (BASE) 
7 Scribd 
8 WorldCat 
9 PDFCAST 
A. Rosenfeld. “Picture processing by computer”. ACM Computing Surveys, 1(3):147-176, 1969.
A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. “Content-based image retrieval at the end of the early years”. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1349-1380, December 2000.
Belkhatir M. “An operational model based on knowledge representation for querying the image content with concepts and relations”. Multimed Tools Application, 43:1–23. Springerlink Netherlands, 2009
Bradshaw B. “Semantic based image retrieval: A probabilistic approach”. In Proceedings of the Eight ACM International Conference on Multimedia, United States, 2000
C.Y.Chang, H.Y.Wang, C.F.Li. “Semantic analysis of real world images using support vector machine”. Expert systems with application : An international journal, 36(7):10560-10569, 2009
E. Chang, K. Goh, G. Sychay, G. Wu, CBSA: CBSA: “Content-based Soft Annotation for Multimodal Image Retrieval using Bayes Point Machines”, In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ), pp. 26-38, 2003.
Facebook, http://www.facebook.com. Accessed at June 2010
H. Tamura and S. Mori. “A data management system for manipulating large images”. In Proceedings of Workshop on Picture Data Description and Management, pages 45-54, Chicago, Illinois, USA, April 1977
Haiying Guan, Sameer Antani, L. Rodney Long, and George R. Thomas. “Bridging the semantic gap using rnaking SVM for image retrieval”. In Proceedings of the sixth IEEE international Conference on Symposium on Biomedical Imaging: From Nano to Macro, USA 2009.
Hong Fu. “Attention driven image interpretation, annotation and retrieval”. PhD thesis. The Hong Kong Polytechnic University. 2006
Hui Hui Wang, Dzulkifli Mohamad, N.A.Ismail. “Image Retrieval: Techniques, challenge and Trend”. In International conference on Machine Vision, Image processing and Pattern Analysis, Bangkok, 2009
Hui Hui Wang, Dzulkifli Mohamad, N.A.Ismail. “Towards Semantic Based Image Retrieval : A Review”. In The 2nd International Conference on Digital Image Processing (ICDIP 2010), Singapore,2010.Proceedings of SPIE, Vol 7546, 2010
Inote : Image Annotation in Java, http://www.iath.virginia.edu/inote/. Accessed at June 2010
Jeon,J.,Laverenko,V.,Manmatha, R “ Automatic image annotation and retrieval using cross-media relevance models". In:Proceedings of international ACM Conference on Research and Development in Information Retrieval, 2003
Jian Hu, Gang Wang, Fred Lochovsky, Jian-Tao Sun, Zheng Chen. “Understanding User’s Query Intent with Wikipedia”. Proceedings of the 18th international conference on World wide web. ACM. 2009
L. Hollink, G. Nguyen, G. Schreiber, J. Wielemaker, and B. Wielinga, "Adding spatial semantics to image annotations," In 4th International Workshop on Knowledge Markup and Semantic Annotation, 2004
Lavrenko,V., Manmatha,R.,Jeon,J:”A model for learning the semantic of pictures”. In proceeding of Advances in Neural Information Processing Systems, NIPS, 2003
M. L. Kherfi, D. Ziou, and A. Benard. “Image retrieval from the World Wide Web: Issues, techniques and systems”. ACM Computing Surveys, 36(1):35-67, 2004
Mittal A, Cheong LF. “Framework for synthesizing semantic-level indexes”. Multimedia Tools and Applications 20(2):135–158.2003
Najlae Idrissi. “Bridging the Semantic Gap for Texture-based Image Retrieval and Navigation”, Journal Of Multimedia, 4(5):277-283, October 2009
P Duygulu, K Barnard, N de Fretias, and D Forsyth. “Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary”. In Proceedings of the European Conference on Computer Vision, pages 97–112, 2002
Photo Blogging made Easy-fotopages, http://www.fotopages.com. Accessed at June 2010
Photoblog-Your Life in Photos, http://www.photoblog.com. Accessed at June 2010
R.Datta, D.Joshi, J.Li, J.Z.Wang. “Image Retrieval: Ideas, Inuences, and Trends of the New Age”. ACM Transactions on Computing Surveys, 40(2), 2008
Travel Photography and Professional Stock Phtography-lonely Planet Images, http://www.lonelyplanetimages.com. Accessed at June 2010
Wikipedia, http://wikipedia.org. Accessed at June 2010
Y. Mori, H. Takahashi, and R. Oka. “Image-to-word transformation based on dividing and vector quantizing images with words”. In Proceedings of the First International Workshop on Multimedia Intelligent Storage and Retrieval Management, 1999
Ying Liu, Dengsheng Zhang, Guojun Lu, Wei-Ying M. “A survey of content-based image retrieval with high-level semantics”. Pattern Recognition, 40(1):262 – 282, 2007
Zhao and Grosky “Bridging the semantic gap in Image retrieval”. Idea Group Publishing Series, Book Chapter 2, pp 14-36 (2002)
Zurina Muda, Paul H. Lewis, Terry R. Payne, Mark J. Weal. “Enhanced Image Annotations Based on Spatial Information Extraction and Ontologies”. In Proceedings of the IEEE International Conference on Signal and Image Processing Application, ICSIPA 2009
Mr. Hui Hui Wang
- Malaysia
hh8wang@gmail.com
Mr. Dzulkifli Mohamad
- Malaysia
Mr. N. A. Ismail
- Malaysia


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