Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i7/82950
Year: 2016, Volume: 9, Issue: 7, Pages: 1-6
Original Article
Riaz Ahmed Shaikh* , Jian-Ping Li, Asif Khan and Kamlesh Kumar
School of Computer Science & Engineering, University of Electronic Science and Technology of China, Chengdu - 611731, Sichuan, China; [email protected], [email protected], [email protected], [email protected]
*Author for Correspondence
Riaz Ahmed Shaikh
School of Computer Science & Engineering, University of Electronic Science and Technology of China, Chengdu - 611731, Sichuan, China; [email protected]
Background/Objectives: Unstructured random scene perception and understanding is a challenging problem in the field of computer vision and image processing. Methods/Statistical analysis: Two images with very different appearance may have the same color, texture and shape features. To recognize two different pictures having similar color, texture and shape we can apply spatial investigation. Findings: A methodology in the light of Markov random field has been proposed in this work to recuperate the fundamental spatial layout from a solitary image and start to examine its use as a foundation for scene understanding and content analysis in content based image retrieval. Our representation comprises of three key components (1) coarsely depicting the orientation of significant scene surfaces, (2) an examination of low level features for the understanding of image, and (3) a shape obliged Markov random field definition that enforces shape priors over the regions. Application/Improvements: We experimentally assess different Markov random field formations and exhibit the adequacy of our proposed approach in scene understanding and content analysis.
Keywords: CBIR, Content Analysis, MRF, Shape, Spatial Layout
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