Object Identification from Images of Variable Scale

Martin J. Lahart

doi:10.1117/12.936674

9 January 1984 Object Identification from Images of Variable Scale

Martin J. Lahart

Proceedings Volume 0432, Applications of Digital Image Processing VI; (1984) https://doi.org/10.1117/12.936674
Event: 27th Annual Technical Symposium, 1983, San Diego, United States

Abstract

When objects must be identified from distorted imagery, a choice must be made between feature sets that are invariant to the distortion and those that are not. Sets of invariants almost always contain less information, resulting in classification error rates that are higher under distortion free conditions, but which are no larger when distortion is present. The choice can be evaluated by calculating error rates as a function of the eigenvalues of the correlation matrix, noise, number of classes and a distortion parameter. An example of this evaluation is given by comparing identification of ships by using a subtraction correlator and moment features. The distortion parameter is scale, to which the correlator is sensitive and the moment comparison is invariant.

Citation Download Citation

Martin J. Lahart "Object Identification from Images of Variable Scale", Proc. SPIE 0432, Applications of Digital Image Processing VI, (9 January 1984); https://doi.org/10.1117/12.936674

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KEYWORDS

Distortion

Optical correlators

Monte Carlo methods

Error analysis

Library classification systems

Binary data

Matrices

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