A NEW APPROACH TO SHAPE-BASED IMAGE RETRIEVAL

Authors

  • Mehdi Chehel Amirani
  • Zahra Sadeghi Gol
  • Ali Asghar Beheshti Shirazi

DOI:

https://doi.org/10.47839/ijc.7.3.530

Keywords:

Principle Component Analysis, Linear Discriminant Analysis, Neural Networks, Feature Extraction, Curvature Function, Image Retrieval

Abstract

Content-based image retrieval (CBIR) is very active research topic in recent years. This paper introduces a new approach to shape-based image retrieval. At first, feature points are determined at the boundary of the shape as the extremums of a new version of the curvature function and the initial features are calculated at these points. The proposed method utilizes a supervised system for nonlinear combination of initial features for extraction of efficient and low dimensional feature vector for each shape. The retrieval performance of the approach is illustrated using the MPEG-7 shape database. Our experiments show that the proposed method is well suited for object indexing and retrieval in large databases.

References

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Published

2014-08-01

How to Cite

Amirani, M. C., Sadeghi Gol, Z., & Beheshti Shirazi, A. A. (2014). A NEW APPROACH TO SHAPE-BASED IMAGE RETRIEVAL. International Journal of Computing, 7(3), 99-106. https://doi.org/10.47839/ijc.7.3.530

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Section

Articles