Color image retrieval using geometric properties

I. S. Hsieh, K. C. Fan

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this paper, we present a novel region-based color image retrieval system using geometric properties. First, a region-growing technique is employed to cluster the connected color pixels with the same color in an image to form color regions, which are the primitive elements in our proposed approach. In the feature extraction module, two important descriptive geometry features are extracted, the spatial relational graph (SRG) and the Fourier description coefficients (FDCs) of each color region. In the matching module, relational distance graph matching between two SRGs is performed to find the best matches with the minimum relational distance. Then, shape matching is applied to obtain the best match with the minimum geometric distance. In our work, the method proposed by Cinque is modified to perform the relational distance graph matching, then the wavelet transform is applied to extract the critical points on the contour of color regions. Experimental results reveal the feasibility of our proposed approach in solving the color image retrieval problem.

Original languageEnglish
Pages (from-to)729-751
Number of pages23
JournalJournal of Information Science and Engineering
Volume17
Issue number5
StatePublished - Sep 2001

Keywords

  • Hungarian method
  • Image retrieval
  • Maximin algorithm
  • Shape matching
  • Wavelet transform

Fingerprint

Dive into the research topics of 'Color image retrieval using geometric properties'. Together they form a unique fingerprint.

Cite this