Abstract
This study develops an automated visual inspection system for detecting and classifying defects in a micro-drill with 0.35 mm diameter using image processing techniques. The orientation of the micro-drill is first determined through image projection. Next, the digital image captured by the CCD is then segmented into regions of interest (ROI). The randomized line detection algorithm and the geometric relationship of the edge points in the ROI are then employed to identify the defects detected. Experimental results show that the developed automatic visual inspection system is as efficient as manual inspection, and can provide additional information concerning the defects for parameters tuning and quality control.
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