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

Volume

2

fYear

2000

fDate

2000

Firstpage

405

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISCAS.2000.856350

Filename

856350