Shift and scale invariant pattern recognition using Mellin radial harmonics

Mendlovic, David; Marom, Emanuel; Konforti, Naim

doi:10.1016/0030-4018(88)90374-4

Cited by 82 publications

(30 citation statements)

References 6 publications

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“…The former filters involve the Mellin radial harmonics for scale invariance [16], the logarithmic harmonics for projection invariance [15], and the circular harmonics for rotation invariance [10]. Fang and Hausler [4] introduced a new class of transforms that achieve STIR invariance simultaneously.…”

Section: Related Workmentioning

confidence: 99%

Translation, rotation, and scale-invariant object recognition

Torres-Méndez

Ruiz‐Suárez

Sucar

et al. 2000

IEEE Trans. Syst., Man, Cybern. C

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Abstract-A method for object recognition, invariant under translation, rotation, and scaling, is addressed. The first step of the method (preprocessing) takes into account the invariant properties of the normalized moment of inertia and a novel coding that extracts topological object characteristics. The second step (recognition) is achieved by using a holographic nearest-neighbor algorithm (HNN), in which vectors obtained in the preprocessing step are used as inputs to it. The algorithm is tested in character recognition, using the 26 upper case letters of the alphabet. Only four different orientations and one size (for each letter) were used for training. Recognition was tested with 17 different sizes and 14 rotations. The results are encouraging, since we achieved 98% correct recognition. Tolerance to boundary deformations and random noise was tested. Results for character recognition in "real" images of car plates are presented as well.

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Section: Related Workmentioning

confidence: 99%

Translation, rotation, and scale-invariant object recognition

Torres-Méndez

Ruiz‐Suárez

Sucar

et al. 2000

IEEE Trans. Syst., Man, Cybern. C

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“…It has been shown [Hsu and Arsenault 1982;Mendlovic, Marom and Konforti 1988;Mendlovic, Konforti and Marom forthcoming] that the classical correlator configuration can be made invariant to one additional parameter by using a matched filter containing only a part of the input data. This added parameter could be the angular orientation of an object when the correlation is performed with respect to only one harmonic out of the circular harmonic decomposition [Hsu and Arsenault 1982], or the scale of the object when the matched filter consists of only one harmonic out of the radial harmonic decomposition [Mendlovic, Marom and Konforti 1988]. Recently we described two other types of harmonic decompositions, the logarithmic harmonic [Mendlovic, Kontbrti and Marom, tbrthcoming] which enables projection (i.e., aspect view) invariant pattern recognition and the more general deformation harmonic [Marom, Mendlovic and Konforti, forthcoming] that can handle any type of distortion parameters (including those mentioned above).…”

Section: Introductionmentioning

confidence: 99%

Composite reference image for joint transform correlator

Mendlovic

Konforti

Marom

1991

Multidim Syst Sign Process

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Abstract. Extension of the joint transform correlator (JTC) operation to include a complex reference image has been presented. Such amplitude and phase reference images are common when using a single harmonic (circular, radial, logarithmic, etc.) in correlation setups or when implementing composite filters. The analysis of an aspect view (tilt) invariant pattern recognition system, using logarithmic harmonics decomposition, JTC principles and composite filter techniques, is described followed by experimental results that can be obtained in real time.

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“…In order to reduce the arduous computational burden of storing and processing vast image dictionaries, arising from the object image variability effects caused by intrinsic and extrinsic inconsistencies, synthetic discriminant functions (SDF) and distortion tolerant filters have been developed [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46]. In the vein of SDF, this paper presents a novel and straightforward technique for substantially reducing the number of images in the target dictionary without adversely affecting robustness of the system.…”

Section: Introductionmentioning

confidence: 99%

Synthetic template: effective tool for target classification and machine vision

Heidary¹

2013

IJACSA

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Abstract-A process for replacing a voluminous image dictionary, which characterizes a certain target of interest in a constrained zone of effectiveness representing controlled states including scale and view angle, with a synthetic template has been developed. Synthetic template (ST) is a spatial map (grayscale image) obtained by combining the set of zone-specific training images that are ascribed to the target of interest. It has been shown that the solo-template ST correlation filter outperforms filter banks comprised of multiple target-class training images. A geometric interpretation of the basic ST concept is employed in order to further explain and substantiate its properties.

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Shift and scale invariant pattern recognition using Mellin radial harmonics

Cited by 82 publications

References 6 publications

Translation, rotation, and scale-invariant object recognition

Translation, rotation, and scale-invariant object recognition

Composite reference image for joint transform correlator

Synthetic template: effective tool for target classification and machine vision

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