Frequency-dependent Image Reconstruction Error for Micro Defect Detection

Published: 01 Jan 2023, Last Modified: 07 May 2025ACML 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Micro defects, such as casting pores in industrial products, have been detected by human visual inspection using X-ray CT images and image processing tools. Automatic detection of micro defects is challenging for anomaly detection methods using image reconstruction errors and nearest neighbor distances because these metrics are dominated by low-frequency information and are insensitive to minor defects. Although recent methods achieve high anomaly detection performances, their detection abilities are insufficient for micro defects. To overcome these problems, we propose to extend a state-of-the-art anomaly detection method by introducing frequency-dependent losses to capture reconstruction errors appearing around micro defects and frequency-dependent data augmentation to improve the sensitivity against the errors. We demonstrate the effectiveness of the proposed method through experiments with MVTec AD dataset especially on the detection of micro defects.
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