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Proceedings Paper

Minimum image resolution for shape recognition using the generic Jacobi Fourier moments
Author(s): C. Toxqui-Quitl; A. Padilla-Vivanco; C. Santiago Tepantlán
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Paper Abstract

We consider the use of Jacobi-Fourier moments for the classification of objects from motion blurred images. A set of numerical features are extracted from an image. These features are invariant to the changes in the scale, orientation, position, and illumination of the objects in the vision field. The test images used here have been acquired when the objects are vibrating at different frequencies and moving at constant velocity. The blur extent by image motion can be obtained using moment descriptors of the motion. Also, the acquisition system is characterized by means the optical transfer function (OTF); which can be computed by the geometric moments of motion function of the object centroid. The classification method is tested using images from objects which have intrinsically little differences between them. Experimental results show that, the proposed classification method based in Jacobi Fourier moments can be well addressed to grade images smeared by motion. A comparison of effectiveness is done with motion descriptors based on geometric moments.

Paper Details

Date Published: 2 November 2011
PDF: 10 pages
Proc. SPIE 8011, 22nd Congress of the International Commission for Optics: Light for the Development of the World, 80117W (2 November 2011); doi: 10.1117/12.903372
Show Author Affiliations
C. Toxqui-Quitl, Univ. Politécnica de Tulancingo (Mexico)
A. Padilla-Vivanco, Univ. Politécnica de Tulancingo (Mexico)
C. Santiago Tepantlán, Univ. Politécnica de Tulancingo (Mexico)


Published in SPIE Proceedings Vol. 8011:
22nd Congress of the International Commission for Optics: Light for the Development of the World
Ramón Rodríguez-Vera; Ramón Rodríguez-Vera; Ramón Rodríguez-Vera; Rufino Díaz-Uribe; Rufino Díaz-Uribe; Rufino Díaz-Uribe, Editor(s)

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