@inproceedings{0d162c8254e64612859e1419fa992456,
title = "A Cascaded Zoom-In Method for Defect Detection of Solder Joints",
abstract = "Defect detection of solder joints plays an essential role in PCB quality control. Feature-Extraction based detection method is popular where color-histogram features and SIFT features are widely used. The histogram feature is simple but incapable of detecting all defect categories. The SIFT feature is invariant to scale and rotation and is able to detect tiny defects, but high computational complexity limits its application. With the observation that most solder joints are defect free in practice, a two-step Cascaded Zoom-In (CZI) detection method is proposed to explore the possibility of combing the merits of both the histogram and the SIFT features. The output of most defect-free solder joints is mostly with a high confidence score in the first step and avoids a costive computation in the second step. Experiments based on real-world data are implemented and demonstrate that our proposed method is not only computationally simple but also with a high detection accuracy.",
keywords = "Anomaly detection, Computer vision, Defect detection, Feature extraction",
author = "Zhiwei Zhang and Hua Wang and Shengmin Zhou and Ronghua Zhou and Lei Sun",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 14th IEEE International Conference on Signal Processing, ICSP 2018 ; Conference date: 12-08-2018 Through 16-08-2018",
year = "2019",
month = feb,
day = "2",
doi = "10.1109/ICSP.2018.8652335",
language = "English",
series = "International Conference on Signal Processing Proceedings, ICSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1081--1086",
editor = "Yuan Baozong and Ruan Qiuqi and Zhao Yao and An Gaoyun",
booktitle = "2018 14th IEEE International Conference on Signal Processing Proceedings, ICSP 2018",
address = "United States",
}