This paper deals with inspection of highly reflective chrome coated rings used in textile machinery using machine vision. These rings are mass produced in very large numbers in a textile machinery manufacturing company and the inspection was carried out manually using optical methods. Introduction of automated vision inspection had not helped the industry fully to achieve 100% quality inspection. Moreover, the whole procedure had to be made quicker in view of the number of components manufactured which is of the order of hundreds of thousands and to be inspected 100% thereafter. Also in order to improve inspection speed and to ensure 100% quality inspection, it was absolutely essential to improve the complete inspection process. Also a proper sorting algorithm was to be considered to classify defective and nondefective components. The effect of curvature, reflective nature of material and the real-time inspection make the imaging and defect detection and classification difficult. The use of dark field illumination has been tried out in this work to quicken the process of defect detection and also to improve the accuracy of detection. The images of the defects captured using a CCD camera of the inner and outer surfaces of the coated ring components have been analysed. The images were subjected to a simple thresholding technique to segment out defects, thus avoiding the use of complex image processing algorithms. It was observed that the classification of defects using dark field illumination was very effective for this particular case and the results as well as analysis of the same are presented in this paper. Copyright © 2011 Inderscience Enterprises Ltd.