Title :
Neural hardware for image processing
Author :
Ancona, Fabio ; Rovetta, Stefano ; Zunino, Rodolfo
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Abstract :
The paper describes a board-based hardware implementation of a neural algorithm performing vector quantization for very low bit-rate video compression. The Neural Gas model has been chosen for its remarkable properties in terms of both consistency (quality of the quantization process) and easy implementation. The neuroboard interfaces to a PC through a standard ISA bus. The board supports both training (codevector adjustment) and run-time operation. The main advantages of the implemented solution lie In its simplicity and easy control for HW tests and SW development.
Keywords :
data compression; digital signal processing chips; neural nets; vector quantisation; video coding; ISA bus; Neural Gas model; board-based hardware implementation; codevector adjustment; consistency; neural algorithm; run-time operation; vector quantization; very low bit-rate video compression; Application software; Hardware; Image coding; Image processing; Instruction sets; Prototypes; Runtime; Signal processing algorithms; Testing; Vector quantization;
Conference_Titel :
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Print_ISBN :
0-7803-3694-1
DOI :
10.1109/MWSCAS.1997.662330
