Title :
Classification of elongated and contracted images using new regular moments
Author :
Raveendran, P. ; Jegannathan, S. ; Omatu, Sigeru
Author_Institution :
Fac. of Eng., Malaya Univ., Kuala Lumpur, Malaysia
fDate :
27 Jun- 2 Jul 1994
Abstract :
This paper presents a technique to classify images that have been elongated or contracted. 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. Results of computer simulations for images are also included verifying the validity of the method proposed
Keywords :
image classification; image processing; invariance; contracted images; elongated images; image classification; moment-invariants; regular moments; unequal scaling; Computer simulation; Equations; Image coding; Image recognition; Information science; Intelligent systems; Mirrors; Pattern recognition; Reflection; Systems engineering and theory;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374880
