Image based contamination detection on hard disk head gimbal assembly

Abstract

Contamination may appear in various stages of hard disk manufacturing including the head gimbal assembly. Currently, the detection of contamination requires manual intervention. An image based automatic contamination detection strategy is therefore presented. After a preprocessing step, the contamination detection algorithm first detects potential areas of contamination using circle detection. Then, each of the contamination contenders are classified as either a contamination or noncontamination using a set of specific rules. The algorithm has been tested on 1,050 head gimbal assembly images of which 313 depicted contaminations. Our preliminary results yields an accuracy of 73.8% with a false negative rate of 34.8% and a false positive rate of 23.6%. Future work includes finetuning the contamination classification rules.