Research Article Open Access

Omni-Zernike Algorithm for Template Matching in Catadioptric System

Mohammed Rziza1, Amina Radgui2 and Anisse Khald1
  • 1 Mohamed V University, Morocco
  • 2 National Institute of Posts and Telecommunications, Morocco

Abstract

Image descriptor have been widely applied in many computer visions and image understanding applications including pattern recognition, robotic, video surveillance, camera calibration and image retrieval, etc. Invariants features are robust when apply several transformations of photometry (illumination, blur, noise, JPEG compression) and transformations of geometry (scaling, rotation, translation and viewpoint change). In this study, we present representation and matching region descriptors. Consequently, a set of region used provided by catadioptric system for evaluation of the performance. These regions are normalized by unit circle form with form and size change. In this contribution, the image descriptors of regions used is Moment's Zernike. They are most suitable invariants in omnidirectional context thanks to the polar coordinates used both omnidirectional geometry and Zernike Moments formulation. The aim is realize a robust matching between object's block by using a measure of distance between Zernike's moment descriptors for optimal similarity. Results shown clearly demonstrate the performance of our method and powerful than most important region descriptors (GLOH, SIFT, PCA-SIFT, complex moments and steerable filters) in term of the ROC curve or precision-recall criterion.

Journal of Computer Science
Volume 16 No. 12, 2020, 1789-1795

DOI: https://doi.org/10.3844/jcssp.2020.1789.1795

Submitted On: 6 October 2020 Published On: 30 December 2020

How to Cite: Rziza, M., Radgui, A. & Khald, A. (2020). Omni-Zernike Algorithm for Template Matching in Catadioptric System. Journal of Computer Science, 16(12), 1789-1795. https://doi.org/10.3844/jcssp.2020.1789.1795

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Keywords

  • Zernike Moment
  • Block Matching
  • Omnidirectional Images