Classification of mechanical parts using an optical-digital system and the Jacobi-Fourier moments

Toxqui-Quitl, C.; Padilla-Vivanco, Alfonso; Báez-Rojas, José Javier

doi:10.1117/12.827707

Cited by 2 publications

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“…Using the geometric moments defined in Equation (1) we obtained the centroid of the object in each image [7,8]. In the Figure 11 is showed the trajectory of the object under lineal motion and vibration motion.…”

Section: Resultsmentioning

confidence: 99%

Minimum image resolution for shape recognition using the generic Jacobi Fourier moments

2011

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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.

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Section: Resultsmentioning

confidence: 99%

Minimum image resolution for shape recognition using the generic Jacobi Fourier moments

2011

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High-precision and fast computation of Jacobi–Fourier moments for image description

et al. 2013

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A high-precision and fast algorithm for computation of Jacobi-Fourier moments (JFMs) is presented. A fast recursive method is developed for the radial polynomials that occur in the kernel function of the JFMs. The proposed method is numerically stable and very fast in comparison with the conventional direct method. Moreover, the algorithm is suitable for computation of the JFMs of the highest orders. The JFMs are generic expressions to generate orthogonal moments changing the parameters α and β of Jacobi polynomials. The quality of the description of the proposed method with α and β parameters known is studied. Also, a search is performed of the best parameters, α and β, which significantly improves the quality of the reconstructed image and recognition. Experiments are performed on standard test images with various sets of JFMs to prove the superiority of the proposed method in comparison with the direct method. Furthermore, the proposed method is compared with other existing methods in terms of speed and accuracy.

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Classification of mechanical parts using an optical-digital system and the Jacobi-Fourier moments

Cited by 2 publications

References 0 publications

Minimum image resolution for shape recognition using the generic Jacobi Fourier moments

Minimum image resolution for shape recognition using the generic Jacobi Fourier moments

High-precision and fast computation of Jacobi–Fourier moments for image description

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