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Contour map registration using fourier descriptors of gradient codes.
1Division of Electrical Engineering, National Research Council of Canada, Ottawa, Ont., Canada K1A 0R8.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
Summary
This study introduces a novel method using Fourier descriptors of gradient codes to locate a subpicture (P1) within a contour map (P2). The technique accurately estimates P1's position and angular misalignment in P2.
Area of Science:
- Image processing
- Computer vision
- Pattern recognition
Background:
- Estimating the position and orientation of objects within images is crucial for various applications.
- Existing methods may struggle with unknown angular misalignments and complex contour maps.
Purpose of the Study:
- To develop a robust method for estimating the position and angular misalignment of a subpicture (P1) within a contour map (P2).
- To leverage Fourier descriptors of multidirectional gradient codes for accurate localization.
Main Methods:
- Generating multidirectional gradient codes and their Fourier descriptors from subpicture P1 measurements.
- Creating a contour map for P2 with a specific isopleth value (c*).
- Employing a two-level classifier using Fourier descriptors and phase correlation to estimate P1's location on P2's isopleths.
Main Results:
- The proposed method successfully estimates the position of subpicture P1 within contour map P2.
- Angular misalignment between P1 and P2 can be determined with significant accuracy.
- Simulations confirm the effectiveness of the technique in various scenarios.
Conclusions:
- Fourier descriptors of multidirectional gradient codes offer a powerful approach for subpicture localization in contour maps.
- The method provides a reliable solution for determining both translational and rotational differences between images.
- This technique has potential applications in image registration and object recognition.
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