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Multimedia Tools and Applications

, Volume 49, Issue 2, pp 323–345 | Cite as

Robust image retrieval based on color histogram of local feature regions

  • Xiang-Yang Wang
  • Jun-Feng Wu
  • Hong-Ying Yang
Article

Abstract

Color histograms lack spatial information and are sensitive to intensity variation, color distortion and cropping. As a result, images with similar histograms may have totally different semantics. The region-based approaches are introduced to overcome the above limitations, but due to the inaccurate segmentation, these systems may partition an object into several regions that may have confused users in selecting the proper regions. In this paper, we present a robust image retrieval based on color histogram of local feature regions (LFR). Firstly, the steady image feature points are extracted by using multi-scale Harris-Laplace detector. Then, the significant local feature regions are ascertained adaptively according to the feature scale theory. Finally, the color histogram of local feature regions is constructed, and the similarity between color images is computed by using the color histogram of LFRs. Experimental results show that the proposed color image retrieval is more accurate and efficient in retrieving the user-interested images. Especially, it is robust to some classic transformations (additive noise, affine transformation including translation, rotation and scale effects, partial visibility, etc.).

Keywords

Image retrieval Local feature region Color histogram Spatial information Classic transformations 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.School of Computer and Information TechnologyLiaoning Normal UniversityDalianChina
  2. 2.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina

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