Title :
New regular moment invariants to classify elongated and contracted images
Author :
Raveendran, P. ; Jegannathan, S. ; Omatu, Sigeru
Author_Institution :
Fac. of Eng., Malaya Univ., Kuala Lumpur, Malaysia
Abstract :
This paper presents a technique to classify images that have been elongated or contracted. It is first shown that the conventional regular moment invariant remains 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; contracted image classification; elongated image classification; regular moment invariants; Application software; Computer simulation; Image coding; Intelligent systems; Pattern recognition; Reflection; Shape; Systems engineering and theory;
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
DOI :
10.1109/IJCNN.1993.714135