A ROI image retrieval method based on CVAAO

Image and Vision Computing,
Volume 26, Issue 11, 1 November 2008, Pages 1540-1549
Yung-Kuan Chan, Yu-An Ho, Yi-Tung Liu, Rung-Ching Chen

Abstract

A novel image feature called color variances among adjacent objects (CVAAO) is proposed in this study. Characterizing the color variances between contiguous objects in an image, CVAAO can effectively describe the principal colors and texture distribution of the image and is insensitive to distortion and scale variations of images. Based on CVAAO, a CVAAO-based image retrieval method is constructed. When given a full image, the CVAAO-based image retrieval method delivers the database images most similar to the full image to the user. This paper also presents a CVAAO-based ROI image retrieval method. When given a clip, the CVAAO-based ROI image retrieval method submits to the user a database image containing a target region most similar to the clip. The experimental results show that the CVAAO-based ROI image retrieval method can offer impressive results in finding out the database images that meet user requirements.

Article Outline

1. Introduction

2. Related works

2.1. The ROI image retrieval methods reviewing

2.2. The Generic algorithm

2.3. ANMRR

3. CVAAO and CVAAO-based image retrieval method

4. The CVAAO-based ROI image retrieval method

4.1. Database creating

4.2. Image querying aspect

4.2.1. The candidate region image segmenting stage

4.2.2. The region image matching stage

4.3. Suitable parameters decision

5. Experiments

5.1. Performances of CVAAO-based and CVAAO-based ROI image retrieval methods

5.2. The robustness in resisting the variations of images

6. Conclusions

References

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