Title :
Fuzzy reasoning for the design of CNN-based image processing systems
Author :
Balsi, M. ; Voci, F.
Author_Institution :
Dipt. di Electron. Eng., Rome Univ., Italy
Abstract :
Fuzzy reasoning in image processing has been proved to be a very effective way to formalize complex inference techniques based on heuristics or experience, taking perceptual quality criteria into account. In this paper, we discuss implementation of fuzzy reasoning image processing on the standard cellular neural network universal machine. In this way, it is possible to employ such powerful massively parallel chips to speed up use of known algorithms, and to systematize design of new perceptual-quality driven CNN applications
Keywords :
cellular neural nets; fuzzy neural nets; image morphing; image processing equipment; inference mechanisms; neural chips; parallel processing; CNN-based image processing systems; complex inference techniques; fuzzy reasoning; massively parallel chips; perceptual quality criteria; standard cellular neural network universal machine; Algorithm design and analysis; Boolean algebra; Cellular neural networks; Fuzzy logic; Fuzzy reasoning; HTML; Image processing; Pixel; Signal processing algorithms; Turing machines;
Conference_Titel :
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location :
Geneva
Print_ISBN :
0-7803-5482-6
DOI :
10.1109/ISCAS.2000.856350
