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Stacked Euler vector (SERVE): a gray-tone image feature based on bit-plane augmentation
Arijit Bishnu1, Bhargab B Bhattacharya
1Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India. arijit.bishnu@iitkgp.ac.in
IEEE Transactions on Pattern Analysis and Machine Intelligence
|December 16, 2006
Summary
A novel Stacked Euler Vector (SERVE) feature efficiently characterizes gray-tone images. This method enhances image retrieval performance by combining SERVE with existing features, as shown by COIL database experiments.
Area of Science:
- Computer Vision
- Image Processing
- Pattern Recognition
Background:
- Gray-tone image characterization is crucial for image retrieval.
- Existing features may have limitations in capturing complex image information.
Purpose of the Study:
- Introduce a new combinatorial feature, Stacked Euler Vector (SERVE), for gray-tone image characterization.
- Evaluate SERVE's effectiveness in improving image retrieval performance.
Main Methods:
- SERVE is computed as a four-tuple of Euler numbers from specific bit planes.
- The computation is simple, fast, and avoids floating-point operations.
- SERVE is used to augment other existing image features.
Main Results:
- SERVE effectively characterizes gray-tone images.
- Augmenting features with SERVE significantly improves image retrieval performance.
- Experimental validation on the COIL database demonstrates SERVE's efficacy.
Conclusions:
- Stacked Euler Vector (SERVE) is a computationally efficient and effective feature for gray-tone images.
- SERVE shows promise for enhancing image retrieval systems.
- The proposed method offers a valuable addition to the field of image analysis.
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