Novel Neural Network Model For Surface Roughness And Image Enhancement With DWT .

-Surface roughness, is a measure of surface quality is one of the specified requirements in a machining process. Integrating machine vision in technical community for past few decades of years is a major parameter that deals. Many researches have been carried out on machine vision applications in industries, as they have the benefit of being noncontact and speedy process than contact methods. Machine Vision, can be used to analyze and determine the area of the surface, and machine vision information can assist sensors to make intelligent decision on the applications. In this work, surface roughness Estimation has been done by Machine vision system. Extraction of features for the enhanced images in spatial frequency domain done with the help of Transform techniques. A neural network (NN) is trained with feature extracted values as input acquired from wavelet Transform and examined to obtain Rt as output. The estimated surface roughness parameter (Rt) results obtained based on NN are compared with Rt values obtained from the Stylus method .