Illumination-robust Recognition and Inspection in Carbide Insert Production

In processes of the production chain of carbide inserts, such as unloading or packaging, the conformity test of the insert type is performed manually, which causes a statistic increase of errors due to monotony and fatigue of workers as well as the wide variety of insert types. A measuring method is introduced that automatically inspects the chipformer geometry, the most significant quality feature of inserts. The proposed recognition approach is based on local energy model of feature perception and concatenates the phase congruency in terms of local filter orientations into a compact spatial histogram. This method has been tested on several inserts of different types. Test results show that prevalent insert types can be inspected and classified robustly under illumination variations.