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Geometrical shape recognition using a cellular automaton architecture and its VLSI implementation. (English)
Real-Time Imaging 3, No. 4, 243-254 (1997).
Summary: The paper presents a new, fast geometrical shape recognition technique based on the properties of cellular automata (CA). The VLSI implementation of the architecture developed for this purpose is also presented. The digitized binary image of the geometrical shape is loaded onto a 2D CA grid. This binary image is the initial global state of the CA. The CA evolves in time until a final stable global state is reached. The geometrical shapes are classified into four different categories, according to the symmetries of their final stable global state, and are then recognized. Eleven geometrical shapes have been recognised using the proposed technique. The die size dimensions of this chip for a $8 \times 8$ pixel image are 2.56 mm $\times$ 2.70 mm = 6.91 mm$^2$, and its maximum frequency of operation is 35 MHz. Targeted applications include classification and inspection tasks in industry.
Classification: I.2.10 I.5.4 I.5.5