Active Detection and Correction of Shape Distortions Based on Moment Invariants for Active Shape Models
ASM中基于不变矩图形畸变主动检测与修正

The active shape model is one of the important method in the field of the deformable models. In the fields of the medical image analysis and machine vision, it is an ever-increasingly broad application method. During the process of image fitting, however, distortions and displacements often happen if the target is not clear or the initial position of the model is not ideal, and there is a lack of effective correction strategies. In this paper, we firstly propose an active detection and correction based on the boundary moment invariants. By introducing the boundary moment invariants, the changes of the model can be quantification, and can be detected and corrected according to the statistical information which is obtained from the training set. Using the proposed method, distortions are effectively avoided and the accuracy of fitting result is obviously increased with little extra time. Finally, the results of our practical implementation prove that the proposed strategy works satisfactorily.