An Image Entropy Recurrence Map-Based Screening Method for Ultrasound B-Scan Image Segments Containing Defects

In recent years, defect detection based on ultrasound B-scan images has been widely utilized in industry to detect the quality and presence of defects in products. However, there are still some difficulties in the process of processing B-scan images, such as sampling noise, the large amount of data, and so on. In this paper, we analyze the acoustic characteristics of an ultrasound B-scan image time series, design an image preprocessing method to make the image information gray-scale lossless, and propose a screening method for ultrasound B-scan image segments containing defects based on the theory of image entropy and a recurrence diagram. Comparison experiments between this method and the traditional image entropy screening algorithm show that this method can solve the above difficulties to a certain extent and has its own superiority. The method proposed in this paper provides a new idea for processing ultrasound B-scan image sequences and presents a new choice when the traditional method is limited.