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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
PubMed
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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:

Related Experiment Videos

  • 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.