Rapid Location of LED Die Array Based on Cross Correlation in Frequency Domain

Abstract:

A rapid template matching algorithm is used to locate l-emitting d (LED) die array on wafer planes in vision-based LED sorting or die-bonding system, the image of LED die array is first converted to binary image and is pre-processed through morphological operations such as dilation and erosion, and the cross correlation operation between LED die templatae and wafer image in frequency domain is implemented by using fast Fourier transform (FFT), and the pixel coordinates of all LED dies on the wafer plane can be determined at one time using the cross correlation in frequency domain (CCFD) instead of in spacial domain. Experimental results of LED die array measurement to a large-diameter LED wafer show that detection efficiency is far higher than conventional normalized cross-correlation (NCC) algorithm, and is only half of consumed time to compare with the sequential similarity detection algorithm (SSDA), the proposed CCFD algorithm can be used for rapid LED die array location in vision-baesd LED sorting or die-bonding machines.

• Periodical: Applied Mechanics and Materials (Volume 441)
• Pages: 651-654
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.441.651
• Online since: December 2013
• Authors: He Xi Li
• Keywords: Cross Correlation, Frequency Domain, LED Die, Template Matching

References

[1] Lingyun Xue, Jiale Fang, Wei Huang and Meng Li. Research on LED die geometric parameter measurement based on shape recognition and sub-pixel detection, 2010 8th World Congress on Intelligent Control and Automation (WCICA), Jinan, China, pp.6204-6210.

DOI: 10.1109/wcica.2010.5554416

[2] Tao Wu, Bin Li, Longwen Wang and Yu Huang. Study on real-time correction method of die declination angles in LED sorting system, 2010 International Conference on Mechatronics and Automation (ICMA), Xian, China, pp.1443-1448.

DOI: 10.1109/icma.2010.5589001

[3] Haining Zhang and Biwei Zhang, LED wafer segmented method of image recognition based on sub-pixel precision threshold, Electronic Design Engineering(In Chinese), Vol. 19, No. 4(2011), pp.113-116.

[4] Mori M. and Kashino K. Fast template matching based on normalized cross correlation using adaptive block partitioning and initial threshold estimation. 2010 IEEE International Symposium on Multimedia (ISM), Taichung, pp.196-203.

DOI: 10.1109/ism.2010.36

[5] Di Stefano L. , Mattoccia S. and Mola M. An efficient algorithm for exhaustive template matching based on normalized cross correlation. 2003 12th International Conference on Image Analysis and Processing, pp.322-327.

DOI: 10.1109/iciap.2003.1234070

[6] Zhenhua H. and Peiying Z. An Improved SSDA applied in target tracking, 1988 9th International Conference on Pattern Recognition, Rome, vol. 2, pp.767-769.

DOI: 10.1109/icpr.1988.28353

[7] Carsten Steger, Markus Ulrich and Charistian Wiedemann. Machine vision algorithms and applications, Tsinghua University Press, Beijing, 2008, pp.302-308.