Using Improved SIFT Algorithm to Implement Surface Defects Detection for Bridge Cable

In order to realize automatic nondestructive testing for surface cable damage on a cable-stayed bridge，a distributed machine vision system was developed. It uses four cameras to acquire images around the cable surface. Surface defection may be distributed in several images. An improved scale invariant feature transform(SIFT) feature matching algorithm for image mosaicing is proposed to real time processing to obtain a whole defect effectively. First，feature points are extracted by a Harris operator. Second，according to defect images collected by the system，the steps of the SIFT operator such as the distribution of the main direction for the matching feature points and the matcking image rotation is simplified. The simplified SIFT operator is employed to describe the feature points and match the images. Finally，image fusion is implemented and a complete image of a defect is obtained. Experimental results show that the algorithm complexity is greatly reduced and improves detection integrity for surface cable defects using our improved SIFT to automatically stitch the defect images together.