An ultrasonic image mosaic method based on improved SIFT algorithm

被引：0
|
作者：
Chi, Dazhao [1 ]
Xu, Zhixian [1 ]
Liu, Haichun [2 ]
Li, Qingsheng [2 ]
Guo, Qiang [2 ]
Su, Weigang [2 ]
Jia, Tao [2 ]
机构：
[1] National Key Laboratory of Precision Welding and Joining of Materials and Structures, Harbin Institute of Technology, Harbin,150001, China
[2] PipeChina Engineering Quality Supervision and Inspection Company, Beijing,100013, China
来源：
Hanjie Xuebao/Transactions of the China Welding Institution | 2024年 / 45卷 / 10期
关键词：
A comprehensive non-destructive testing of large structures usually needs a series of C-scans. In order to obtain a panoramic image of the structure under test; the method of sub-image mosaic is studied. According to the dynamic process of ultrasonic imaging and combined with digital image processing technology; an improved image mosaic method for ultrasonic C-scan detection is proposed based on the traditional scale invariant feature transform (SIFT) algorithm. Firstly; in view of the low success rate of ultrasound image registration using the traditional SIFT algorithm; the obtained matching feature points are screened through the vector difference of the starting positions of ultrasonic probe. Secondly; a dynamic programming method is used to find the best stitching path. Finally; a gradual in and out fusion is carried out along the best path for stitching to improve the visual effect of the fused area. Artificial defect contained block and welded piece are prepared and tested. The results of ultrasonic image mosaic show that the improved SIFT algorithm can effectively stitch multiple ultrasonic C-scan sub-images into panoramic images; and the proposed method has high accuracy of feature point matching and small image fusion distortion; which is better than the conventional SIFT image mosaic algorithm. In the mosaic image; the positions of targets match well; which can achieve overall non-destructive evaluation of structural processing quality. © 2024 Harbin Research Institute of Welding. All rights reserved;
D O I：
10.12073/j.hjxb.20240630001
中图分类号：
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页码：1 / 7
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