Earticle

초록

영어

Content Based Image Retrieval (CBIR) has been the most significant area in the applications of Pattern recognition and Computer Vision for the last three decades. However, there are many open problems left unresolved. Among these, one of the current problems of CBIR is to obtain an effective Similarity Measure. The CBIR systems make use of Integrated Region Matching (IRM) to match segmented images which is computationally economic, but it is not a metric distance whereas systems that use Minimum Cost Region Matching (MiCRoM) as a similarity measure is a metric distance, but computationally expensive. In order to address the above problem, this paper has developed the Optimal Cost Region Matching (OCRM) similarity measure for region based image retrieval. The proposed OCRM uses the north-west corner rule of the Transportation problem that fulfills the monge property. The experiment carried out on 1000 color images taken from the Corel database that are compared with IRM, and MiCRoM similarity measures.

목차

Abstract
 1. Introduction
 2. Proposed Methodology
  2.1. Feature Extraction and Representation
  2.2 Segmentation
  2.3 OCRM: Optimal Cost Region Matching Similarity Measure
 3. Experimental Results
 4. Conclusion
 References

키워드

저자

• N. Gnaneswara Rao [ Department of CSE, Vignan University, Vadlamudi, A.P., India ]
• T. Sravani [ Software Engineer, Visakhapatnam ]
• V. Vijaya Kumar [ Dept. of CSE/IT, Anurag Group of Institutions, Ghatkesar, JNT University Hyderabad , A.P., India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605