Analysis of resist images with pattern defects by Hough transform

Abstract

Abstract EUV technology has led to smaller device features, emphasizing the importance of minimizing defects in production. Research has focused on improving resist material uniformity to address variability in resulting patterns caused by stochastic factors, with attention paid to the underlying chemistry. In this study, we developed an automated method for analyzing resist patterns with defects using image recognition techniques. This method involves the analysis of line-and-space resist patterns using image processing technologies, comparison using established standards, and the identification of patterns with defects. A modified version of Hough transform technique was employed to automatically analyze approximately 2500 scanning electron microscopy images. Using our method, we can identify defective and deformed patterns by comparing the detected line-and-space resist patterns with the established standard. The indices that characterize the resist patterns with defects are proposed. Finally, simulated images were also used to uncover the chemical information underlying defective resist patterns.