Abstract
With the rapid development of industries such as nuclear power and shipbuilding, radiographic testing (RT) is widely used in these fields as an important means of weld inspection. It also produces a large number of radiographic films, which consume a great deal of manpower and material resources. It is therefore beneficial for the radiographic film to be digitised for storage and archiving. Text detection in RT weld images is an important prerequisite for the archiving of digitised films. This paper proposes a novel text detection method that employs mask convolution and frequency-domain filtering, which can detect text at different positions, with different fonts and of different sizes in RT weld images. The method is evaluated using 366 different images and shows significant efficacy for text detection in RT weld images, with the precision value reaching 96%. The method used in this paper is also compared with other methods that are commonly used in other fields and the results show that the proposed method gives improved results compared to state-of-the-art methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have