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Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

Rehan Ashraf1, Mudassar Ahmed2, Sohail Jabbar2

  • 1Department of Computer Science, National Textile University, Faisalabad, Pakistan. rehan@ntu.edu.pk.

Journal of Medical Systems
|January 27, 2018
PubMed
Summary
This summary is machine-generated.

This study enhances content-based image retrieval (CBIR) by combining YCbCr color, canny edge histograms, and discrete wavelet transform. The novel approach significantly improves image search accuracy and efficiency.

Keywords:
Artificial neural networkCBIRCanny descriptorDiscrete wavelet transformHistogramSimilarityYCbCr

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Area of Science:

  • Computer Science
  • Information Technology
  • Digital Image Processing

Background:

  • Multimedia complexity has increased, making similar content retrieval a challenge.
  • Content-Based Image Retrieval (CBIR) uses visual features for image searching.
  • Effective feature extraction is crucial for CBIR performance.

Purpose of the Study:

  • To propose an improved CBIR method for accurate multimedia content retrieval.
  • To explore the effectiveness of combining different feature extraction techniques.
  • To evaluate the proposed method's performance against existing approaches.

Main Methods:

  • Utilized YCbCr color space for image representation.
  • Implemented canny edge histogram and discrete wavelet transform for feature extraction.
  • Employed Artificial Neural Networks (ANN) for image classification and retrieval.
  • Tested the algorithm on the standard Wang image database.

Main Results:

  • The combined approach of edge histogram and discrete wavelet transform enhanced retrieval performance.
  • Different wavelet functions were compared to determine optimal suitability.
  • The proposed method demonstrated superior performance compared to existing CBIR techniques.
  • Evaluated using Precision and Recall metrics.

Conclusions:

  • The proposed CBIR method, integrating YCbCr color, canny edge histogram, and DWT, offers significant improvements.
  • This approach provides a more effective solution for content-based image search.
  • The study highlights the importance of combined feature descriptors for robust image retrieval.