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A new technique to derive invariant features for unequally scaled images

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3 Author(s)
Raveendran, P. ; Fac. of Eng., Malaya Univ., Kuala Lumpur, Malaysia ; Omatu, S. ; Poh Sin Chew

This paper presents a new technique to derive features for images that are translated, scaled equally/unequally and rotated. The problem is formulated using conventional regular moments. It is shown that the conventional regular moment-invariants remain no longer invariant when the image is scaled unequally in the x- and y-directions. A method is proposed to form moment-invariants that do not change under such unequal scaling. The newly formed moments are also invariant to translation and reflection. However, it is not invariant for images that are rotated. A neural network is trained to estimate the angle of rotation; it is then used to derive the invariant moments for images that are unequally scaled, translated and rotated. Computer simulation results are also included to show the validity of the method proposed

Published in:

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on  (Volume:4 )

Date of Conference:

12-15 Oct 1997