The surface defect detection is an important process in the production of mobile phones. To detect var-ious mobile phone surface defects and acquire detailed features of tiny defects, this paper proposes a Hierarchical Multi-Frequency based Channel Attention Net (HMFCA-Net). In particular, an attention mech-anism that uses multi-frequency information and local cross-channel interaction is proposed to represent the weighted defect features. A deformable convolution based ResNeSt network is introduced to handle various defect shapes. Besides, to overcome the extreme aspect ratio problem caused by the tiny phone surface defects, a RoI Align is introduced to decrease localization error. Experiments on the public DAGM dataset and a self-collected dataset named MPSSD shows that the proposed method achieves promising performance on defect detection task. (c) 2021 Elsevier B.V. All rights reserved.
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