Abstract: Image segmentation is the key link in the 3D reconstruction of ultrasonic phased array NDT, and the accuracy and efficiency of the segmentation are the important guarantee for the accuracy and real time of the 3D reconstruction of the image. The ultrasonic phased array NDT image contains a lot of noise and intensity in homogeneity. Traditional CV model uses fixed iterative step to segment the ultrasonic phased array NDT image, which leads to low segmentation efficiency and low precision. This paper makes use of the characteristics of the over segmentation of the traditional watershed algorithm to make a watershed transformation to the image. The number of pixels and intensity information in each region are counted, and a weight matrix is obtained. The matrix is introduced into the CV model, and the adaptive weight CV model is obtained. In the iterative process of level set function, the weight matrix can adaptively adjust the iteration step size according to the image information. The experiment shows that, in the segmentation of the ultrasonic phased array image, compared with the CV model and the LBF model, the weighted CV model proposed in this paper has higher efficiency and segmentation accuracy.

Key words: ultrasonic phased array, CV model, watershed, adaptive weight