Fuzzy inferring mathematical morphology and optical implementation


Autoria(s): 刘立人
Data(s)

1996

Resumo

Fuzzification is introduced into gray-scale mathematical morphology by using two-input one-output fuzzy rule-based inference systems. The fuzzy inferring dilation or erosion is defined from the approximate reasoning of the two consequences of a dilation or an erosion and an extended rank-order operation. The fuzzy inference systems with numbers of rules and fuzzy membership functions are further reduced to a simple fuzzy system formulated by only an exponential two-input one-output function. Such a one-function fuzzy inference system is able to approach complex fuzzy inference systems by using two specified parameters within it-a proportion to characterize the fuzzy degree and an exponent to depict the nonlinearity in the inferring. The proposed fuzzy inferring morphological operators tend to keep the object details comparable to the structuring element and to smooth the conventional morphological operations. Based on digital area coding of a gray-scale image, incoherently optical correlation for neighboring connection, and optical thresholding for rank-order operations, a fuzzy inference system can be realized optically in parallel. (C) 1996 Society of Photo-Optical Instrumentation Engineers.

Identificador

http://ir.siom.ac.cn/handle/181231/1598

http://www.irgrid.ac.cn/handle/1471x/10324

Idioma(s)

英语

Fonte

刘立人.,Opt. Eng.,1996,35(10):2912-2920

Palavras-Chave #mathematical morphology #rank-order filter #mean filter #fuzzy inference #image processing #optical processing
Tipo

期刊论文