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, huge amount of data and so on. In this paper, we analyse the acoustic characteristics of 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 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 in limitation.