ASM Location Algorithm Based on Feature Points Expansion and Features Extracted by PCA
Luo Shengpin · Optoelectronic Technology · 2015
ASM(Active Shape Model)algorithm has been being widely used in location of the target object.However,the localization accuracy of the traditional ASM algorithm is low and the model tends to converge to a wrong location easily.So an improved ASM algorithm based on feature points expansion and gray features extracted by PCA(Principal Component Analysis)is proposed. In order to improve the accuracy of ASM algorithm in target location,equidistant interpolation is applied to the expansion of feature points firstly;Secondly,PCA is applied to the processing of the normal gray information instead of the derivation of grey value.It is experimentally indicated that the a significant increase in the localization accuracy and robustness is realized with the improved algorithm with the average localization error decreased by more than 38%.