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A modified shape context method for shape based object retrieval.

Radhika Mani Madireddy1, Pardha Saradhi Varma Gottumukkala2, Potukuchi Dakshina Murthy3

  • 1Department of CSE, Pragati Engineering College, Surampalem, AP 533437 India.

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This study simplifies the shape context method for object recognition using Fourier Transforms. The novel approach enhances recognition efficiency and is invariant to common transformations.

Keywords:
Distance measureFeature extractionObject recognitionShape representation

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Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Shape context is a crucial descriptor for object recognition.
  • Existing methods can be complex, necessitating simplification.
  • Object recognition requires robust descriptors invariant to transformations.

Purpose of the Study:

  • To simplify the shape context method for object recognition.
  • To introduce a novel approach incorporating Fourier Transform.
  • To evaluate the descriptor's efficiency and invariance properties.

Main Methods:

  • A simplified shape context descriptor is designed.
  • Fourier Transform is integrated into the descriptor.
  • Descriptor computation considers all contour points relative to a reference point.
  • Invariance to translation, rotation, and scaling is tested.
  • Euclidean distance is used for similarity matching.

Main Results:

  • The modified shape context descriptor demonstrates invariance to translation, rotation, and scaling.
  • Experiments on three standard databases show improved efficiency.
  • The proposed descriptor outperforms other concurrent descriptors.

Conclusions:

  • The simplified shape context method with Fourier Transform is effective for object recognition.
  • The modified descriptor offers enhanced efficiency and robustness.
  • This approach provides a valuable alternative for image recognition tasks.