Application of neural network pattern recognition to the geometrical characterisation of optical fibres

Automation of the image shearing measurement technique applied to optical fibre geometry is discussed. The use of both edge detection filters and a multi-layer perceptron neural network to identify the critical `just touch´ condition are compared. The repeatability of cladding diameter measurements using both methods are presented which demonstrate the superiority of the neural network technique