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Related Experiment Video

Updated: Jun 25, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Color object indexing and retrieval in digital libraries.

Jie Wei1

  • 1Dept. of Comput. Sci., City Univ. of New York, NY 10031, USA. wei@cs.ccny.cuny.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 5, 2008
PubMed
Summary

This study enhances illumination invariant object recognition by improving chromaticity representation and indexing. The new method uses CIE UCS transform and DCT domain processing for more accurate and efficient image retrieval in digital libraries.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Libraries

Background:

  • Previous work achieved illumination invariant object recognition using color band normalization and chromaticity histograms.
  • Limitations included uniform quantization of chromaticity and processing in uncompressed image domains.

Purpose of the Study:

  • To develop an improved algorithm for illumination invariant object recognition and retrieval.
  • To address limitations of previous methods for more accurate and efficient digital library applications.

Main Methods:

  • Utilized the CIE UCS transform for improved chromaticity quantization, aligning with human visual perception.
  • Implemented indexing directly in the Discrete Cosine Transform (DCT) domain using macro-block coefficients.
  • Incorporated a smoothing step for normalized chromaticity histogram frames to enhance data reduction.
  • Employed vector quantization for clustering 36-dimensional model vectors, reducing search space significantly.

Main Results:

  • The proposed algorithm demonstrates desirable results in experiments.
  • Achieved illumination invariant object indexing and retrieval.
  • Reduced search space by an order of magnitude through clustering.

Conclusions:

  • The developed approach offers a more perceptually relevant and computationally efficient method for color-object indexing and retrieval.
  • This advancement is particularly beneficial for enhancing search capabilities in digital libraries.