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Automatic object extraction over multiscale edge field for multimedia retrieval.

Serkan Kiranyaz1, Miguel Ferreira, Moncef Gabbouj

  • 1Institute of Signal Processing, Tampere University of Technology, FIN-33101 Tampere, Finland. serkan@cs.tut.fi

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|December 13, 2006
PubMed
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This study introduces a multiscale method for extracting object boundaries from Canny edge fields, improving content-based image retrieval. The approach excels at identifying main objects, even in complex images, outperforming color and texture features.

Area of Science:

  • Computer Vision
  • Image Processing
  • Multimedia Systems

Background:

  • Content-based image and video retrieval relies on effective feature extraction.
  • Automatic object boundary extraction is crucial for indexing and retrieval accuracy.
  • Existing methods may struggle with complex images containing noise, texture, and variations.

Purpose of the Study:

  • To develop an automatic object boundary extraction method using Canny edge fields.
  • To enhance content-based indexing and retrieval in image and video databases.
  • To evaluate the proposed method's performance against traditional features like color and texture.

Main Methods:

  • A multiscale approach is employed for image simplification, progressively removing noise and texture while preserving major edges.

Related Experiment Videos

  • Edges are extracted at each scale and analyzed using perceptual subsegment analysis, guided by Gestalt laws.
  • The object extraction process is integrated as a feature extraction module within the MUVIS framework.

    • Main Results:

    • The method demonstrates promising performance in extracting main object boundaries, even in images with crowded textural edges.
    • It effectively handles objects with variations in color, texture, and illumination.
    • The integrated system achieved promising retrieval performance, outperforming methods relying solely on color or texture features.

    Conclusions:

    • The proposed multiscale object boundary extraction method offers a robust solution for content-based retrieval.
    • It provides superior performance compared to color and texture-based retrieval in specific scenarios.
    • The method shows significant potential for advancing multimedia indexing and retrieval systems.