Automated detection of light-emitting-diode chip surface blemishes on two background textures

Hong-Dar Lin

doi:10.1117/1.2829150

1 January 2008 Automated detection of light-emitting-diode chip surface blemishes on two background textures

Hong-Dar Lin

Author Affiliations +

Optical Engineering, Vol. 47, Issue 1, 017201 (January 2008). https://doi.org/10.1117/1.2829150

Abstract

This research explores the automated detection of surface blemishes that fall across two different background textures in a light-emitting-diode (LED) chip. Water-drop blemishes, commonly found on chip surfaces, impair the appearance of LEDs as well as their functionality and security. Automated inspection of a water-drop blemish is difficult, because the blemish has a semi-opaque appearance and a low intensity contrast with the rough exterior of the LED chip. Moreover, the blemish may fall across two different background textures, which further increases the difficulties of defect detection. We first use the one-level Haar wavelet transform to decompose a chip image and extract four wavelet characteristics. Then, the T² statistic of multivariate statistical analysis is applied to integrate the multiple wavelet characteristics. Thus, the wavelet-based T² approach judges the existence of water-drop blemishes. Finally, we compare the defect detection performance among the wavelet-based T² method and traditional methods. Experimental results show that the proposed method achieves a 95.8% probability of accurately detecting the existence of water-drop blemishes, and an approximate 92.6% probability of correctly segmenting their regions.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Hong-Dar Lin "Automated detection of light-emitting-diode chip surface blemishes on two background textures," Optical Engineering 47(1), 017201 (1 January 2008). https://doi.org/10.1117/1.2829150

Published: 1 January 2008

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