Title :
A digitally programmable current mode analog shunting inhibition cellular neural network
Author :
Bermak, Amine ; Boussaid, Farid ; Bouzerdoum, Abdesselam
Author_Institution :
Sch. of Eng. & Math., Edith Cowan Univ., Joondalup, WA, Australia
Abstract :
A novel read-out and column circuit for VLSI implementation of a shunting inhibition cellular neural network (SICNN) is proposed. Image enhancement and edge detection based on SICNN with programmable mask size are achieved within a CMOS imager. In contrast to most existing implementations, the circuit is based on a mixed analog digital approach in which the read-out is realized using a digital circuit while the processing takes advantage of the compactness and low power of the current mode approach. The mask size and coefficients can be varied with a digitally programmable current mode analog processor. In addition, the pixel output and the processed SICNN output are obtained simultaneously on the ¯y resulting in a real-time computation of SICNN. The imager has been fabricated using 0.7 μm CMOS technology
Keywords :
CMOS image sensors; cellular neural nets; current-mode circuits; edge detection; image enhancement; mixed analogue-digital integrated circuits; programmable circuits; readout electronics; 0.7 micron; CMOS imager; column circuit; digitally programmable current mode circuit; edge detection; image enhancement; mixed analog digital approach; pixel output; programmable mask size; read-out circuit; real-time computation; shunting inhibition cellular neural network; CMOS image sensors; CMOS process; CMOS technology; Cellular neural networks; Digital circuits; Image enhancement; Image processing; Neurons; Silicon carbide; Very large scale integration;
Conference_Titel :
Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on
Conference_Location :
Jounieh
Print_ISBN :
0-7803-6542-9
DOI :
10.1109/ICECS.2000.913036