Abstract

Rotation invariant estimation is an important and computationally difficult process in the real-time human computer interaction. Our new methodologies propose here for on-line image rotation angle estimation, correction and feature extractions based on line integrals. We reveal that a set of projection data of line integrals from single (fan-arc and fan-beam) or multi point sources (Radon transform) are employed for orientation estimation. After estimating orientation, image angle variations are altered to its principal direction. We further combine Boltzmann machine and k-mean clustering to obtain parameter optimized Gabor filters, which are used to extract non-redundant compact set of features for classification. The proposed method of fan-line, fan-arc and Radon transform are compared for real-time image orientation detection. Accuracy of classification is evaluated with the classifiers viz., back propagation, Hamming neural network, Euclidean-norm distance, and k-nearest neighbors. Experiment on a database of 535 images consisting of license plate and iris images. The viability of suggested algorithms has been tested with different classifiers. Thus, this paper proposes an efficient rotation invariant recognition for on-line images recognition.

Highlights

  • Where R1(u), R2(u) are specified intervals and u is a single scalar variables

  • The rotation transformation is described as a rotation about an axis that is perpendicular to the xy plane and passes through the pivot point

  • In order to evaluate the efficacy of the estimation process, comparison of rotation estimation of projection data of fan beam arc, fan beam line and Radon transform have been carried out

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Summary

ROTATION-INVARIANCE USING LINE INTEGRALS

A vector is a quantity including both magnitude and direction, such as force, velocity, displacement and acceleration. Force is not constant one, at different points the force may peak in different directions with strength In accordance with these basic studies, a projection of a 2D function f(x,y) is a set of line integrals, from which data can be produced by radiating from single and multiple sources. These two sources are employed to estimate the rotation angle of the objects. With the basics of rotation transformation and line integrals, we can introduce new ray sampling coordinates x' and y' and Jacobian (J) is described as ‘arc’ sensor spacing has the angular spacing in degrees else linear spacing in pixel. Where fb (r,φ ) is the density at the point with polar coordinates (r,φ) in the region, while (d − r cos(θ − φ)) is the perpendicular distance between the ray and this point

Fan Beam Arc and Line
Single Source Point
Estimation using Radon Transform
PARAMETER OPTIMIZED GABOR FILTERS
Parameter Selection and Conditions
PERFORMANCE ANALYSIS AND EXPERIMENTS
RESULTS
CONCLUSION

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