A cellular automata-based model for edge detection

• Autorzy: Wongthanavasu S. , Sadananda R. , Qi Y.
• Języki publikacji: EN

Abstrakty

EN

The paper discusses two-dimensional uniform cellular automata for image processing. A cellular automaton rule using von Neumann neighbothood is proposed for carrying out edge detection on binary images. The composition model and characterization of the state space of the rule are analyzed using a finite state machine, a state graph, a deterministic finite automaton, and a characteristic polynomial. The rule is extended to deal with 8-bit gray-scale images, and has been tested on a set of images. Our work shows that a cellular automata-based model for edge detection provides an optimum edge map non binary images, and is an average better that comparative edge operators for 8-bit gray-scale images.

Słowa kluczowe

EN

cellular automata; image processing; finite state machine; deterministic finite automation; characteristic polynominal

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2000
• Tom: Vol. 9, No. 4
• Strony: 775--796
• Opis fizyczny: Bibliogr. 17 poz.

Twórcy

autor

Wongthanavasu S.

autor

Sadananda R.

autor

Qi Y.

• Computer Science and Information Management Program, School of Advanced Technologies, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand,