Surface roughness of machined components has a significant influence on the service performance such as lubrication, friction, wear, fatigue, corrosion, adhesion in surface coating etc. Hence, inspection and control of the surface roughness of components are very important in manufacturing and metal cutting industries. Most of the surface roughness measuring instruments used in industries are contact type, off-line stylus instruments which are not adoptable for highly automated factory environment. The proposed method uses a machine vision technique and LED front lighting method as a substitute for evaluation of surface roughness measurements by stylus instrument.A light scattered pattern from the machined surface is captured and processed to obtain a characteristics feature of optical information viz. Ga (Grey Level value) which is further processed to evaluate the surface roughness value.A comparative study made on surface roughness values obtained by the traditional method and the Machine vision technique shows favorable results. The Machine Vision Techniques using Front Lighting is suitable for online non-contact method which can be adopted for automated inspection environment.