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On the Use of Normalized Compression Distances for Image Similarity Detection.

Dinu Coltuc1, Mihai Datcu2, Daniela Coltuc3

  • 1Faculty of Electrical Engineering, Electronics and Information Technology, Valahia University of Targoviste, Târgoviște 130024, Romania.

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Summary
This summary is machine-generated.

Normalized Compression Distance (NCD) feature vectors, derived from image transformations, effectively detect image similarity, outperforming direct NCD calculations for various image processing tasks.

Keywords:
NCD feature vectorsimage similaritylossless compressionnormalized compression distancenormalized information distancerobust similarity

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Area of Science:

  • Computer Vision
  • Image Processing
  • Information Theory

Background:

  • Normalized Compression Distance (NCD) is a metric for measuring the similarity between data objects.
  • Direct NCD application for image similarity detection has limitations.
  • Feature extraction methods can enhance similarity detection capabilities.

Purpose of the Study:

  • To evaluate the effectiveness of NCD-based feature vectors for image similarity detection.
  • To explore the correlation between NCD feature vectors and image similarity.
  • To assess the robustness of the proposed method against common image processing operations.

Main Methods:

  • Generating NCD-based feature vectors by computing NCD between original images and their translated/rotated versions.
  • Utilizing various geometric transforms (translations, rotations) and standard compressors.
  • Testing feature vector configurations on filtered images and the Kodak image set with common image processing applied.

Main Results:

  • Direct NCD computation failed to detect similarity for simple filtering.
  • NCD-based feature vectors demonstrated robustness against smoothing, lossy compression, contrast enhancement, and noise.
  • The method showed some robustness against geometric transformations like scaling, cropping, and rotation.

Conclusions:

  • NCD-based feature vectors offer a more robust approach to image similarity detection compared to direct NCD.
  • The proposed method shows promise for applications requiring reliable image similarity assessment under various image degradations.
  • Further research into optimal transform and compressor combinations is warranted.