Automatic thresholding for defect detection by background histogram mode extents

Automatic thresholding is a popular segmentation technique that is widely used for automated visual inspection of defects. Many methods have been proposed for appropriate selection of the threshold value. However, most of these methods perform well for images where defects and background have distinguishable histogram modes and select a threshold close to a valley between the two modes which is usually very hard to locate except for the clearly bi-modal histograms. Additionally, where defect detection requires bi-level segmentation, these methods require a prior knowledge of the number of thresholding levels. In this paper, a new approach for threshold selection is taken that aims to find the threshold value at the boundary of the intensity ranges of defects (object) and background by comparing the histogram modes of the background and defective regions. The proposed method automatically detects defective regions as well as defect-free regions or background. By study of the histogram of the background region, appropriate threshold values are automatically selected at the extents of the background histogram mode. The proposed method proved very effective on several standard images of surface defects. The significance of the method's efficiency is well seen in successfully segmenting defects in images with non-uniform background and with no visible bi- or multi-modal behavior. Another significance of the technique is segmentation of defects comprising of two intensity regions (such as bumps and pits) without specifying the number of threshold levels. (C) 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.