Analytical approach to classification by  object reconstruction from features

Albrecht Melan; Stephan Rudolph

doi:10.1117/12.395061

4 August 2000 Analytical approach to classification by object reconstruction from features

Albrecht Melan, Stephan Rudolph

Proceedings Volume 4052, Signal Processing, Sensor Fusion, and Target Recognition IX; (2000) https://doi.org/10.1117/12.395061
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

Classification is a central task in pattern recognition. To classify objects into object classes, features are calculated from objects. Objects classes are determined by class boundaries. If it is thus possible to reconstruct objects from their features, variations of feature on their objects and on class boundaries can be studied explicitly. In this work the classical steps in pattern recognition form object space to feature space are extended by the concept of physical similarity and by a back-transform form feature space to object space. The analytic assumptions and numeric properties of this back-transformation from feature space into object space are investigated using gray scale images. Higher moments of these grey scale images are computed and later used for reconstruction. When a grey scale image is written as a discrete valued 2D function, the function lies in the Hilbert space of quadratic integrable functions. Quadratic integrable functions can be written as a series of orthonormal functions, where the coefficients of the series are calculated using a scalar product of the image and the orthonormal base functions. Using Legendre polynomials as base functions, the scalar products for the determination of the series' coefficients can be calculated from the moments and the polynomials coefficients only thus yielding the back-transformation.

Citation Download Citation

Albrecht Melan and Stephan Rudolph "Analytical approach to classification by object reconstruction from features", Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); https://doi.org/10.1117/12.395061

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