In the past decades, the theories of invariant moments have been researched extensively and wildly used in many fields. However, for the laser-welding spots of titanium tubes or other fixed objects, the invariant moments are inapplicable. Besides, the studies and experiments about image classification by means of the original moment values were barely proposed. In this paper, the method of classification based on original moment values is introduced, and an improved approach of KPCA (kernel principal component analysis) in order to reduce the inner-class distance of the qualified laser-welding spots is also discussed. Finally, experiments are carried out to validate the classification ability, and results show that the original moment values are suited as pattern features in classification of fixed objects.
