Automatic Solder Joint Defect Classification using the Log-Gabor Filter


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This paper proposes the validity of a Gabor filter bank for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance measure based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.



Advanced Materials Research (Volumes 97-101)

Edited by:

Zhengyi Jiang and Chunliang Zhang






N. S. S. Mar et al., "Automatic Solder Joint Defect Classification using the Log-Gabor Filter ", Advanced Materials Research, Vols. 97-101, pp. 2940-2943, 2010

Online since:

March 2010




[1] H. H. Loh and M. S. Lu: Printed circuit board inspection using image analysis, IEEE Transactions on Industry Applications, Vol 35, (1999), pp.426-432.

DOI: 10.1109/28.753638

[2] B. C. Jiang, C. C. Wang and Y. N. Hsu: Machine vision and background remover-based approach for PCB solder joints inspection, Vol 45, (2007), pp.451-464.

DOI: 10.1080/00207540600607184

[3] T. H. Kim, T. H. Cho, Y. S. Moon and S. H. Park: Visual inspection system for the classification of solder joints, Pattern Recognition, Vol 32, (1999), pp.565-575.

DOI: 10.1016/s0031-3203(98)00103-4

[4] L. Bing, Z. Yun, Y. Guangzhu and Z. Xianshan: ANN Ensembles Based Machine Vision Inspection for Solder Joints, IEEE International Conference on Control and Automation, (2007), pp.3111-3115.

DOI: 10.1109/icca.2007.4376934

[5] G. Acciani, G. Brunetti and G. Fornarelli: Application of neural networks in optical inspection and classification of solder joints in surface mount technology, IEEE Transactions on Industrial Informatics, Vol 2, (2006), pp.200-209.

DOI: 10.1109/tii.2006.877265

[6] T. Ong, Z. Samad and M. Ratnam: Solder joint inspection with multi-angle imaging and an artificial neural network, The International Journal of Advanced Manufacturing Technology, Vol 38, (2008), pp.455-462.

DOI: 10.1007/s00170-007-1117-6

[7] J. Cook, C. McCool, V. Chandran and S. Sridharan: Combined 2D/3D Face Recognition Using Log-Gabor Templates, IEEE International Conference on Video and Signal Based Surveillance, AVSS06 (2006), pp.83-83.

DOI: 10.1109/avss.2006.35

[8] J. Daugman: Two-dimensional spectral analysis of cortical receptive field profiles, Vision Research, Vol 20, (1980), pp.847-856.

DOI: 10.1016/0042-6989(80)90065-6

[9] D. J. Field: Relations between the statistics of natural images and the response properties of cortical cells, J Opt Soc Am A, Vol 4, (1987), pp.2379-2394.

[10] N. S. S. Mar, C. Fookes and P. K. D. V. YarLagadda: Design of automatic vision-based inspection system for solder joint segmentation, Achievements in Materials and Manufacturing Engineering, (2009), pp.145-151.

[11] J. Cook, V. Chandran, S. Sridharan and C. Fookes: Gabor Filter Bank Representation for 3D Face Recognition, Digital Image Computing: Techniques and Applications (DICTA05), (2005), pp.16-23.

DOI: 10.1109/dicta.2005.39

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