Open Access

ARTICLE

Fast and High-Resolution Optical Inspection System for In-Line Detection and Labeling of Surface Defects

M. Chang^1,2,3, Y. C. Chou^1,2, P. T. Lin^1,2, J. L. Gabayno^2,4

1 Department of Mechanical Engineering, Chung Yuan Christian University, Chung Li, Taoyuan, Taiwan 32023.
2 Center for Biomedical Technology, Chung Yuan Christian University, Chung Li, Taoyuan, Taiwan32023.
3 The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China 430074.
4 Mapua Institute of Technology, Muralla St., Intramuros, 1002 Manila, Philippines.

Computers, Materials & Continua 2014, 42(2), 125-140. https://doi.org/10.3970/cmc.2014.042.125

Abstract

Automated optical inspection systems installed in production lines help ensure high throughput by speeding up inspection of defects that are otherwise difficult to detect using the naked eye. However, depending on the size and surface properties of the products such as micro-cracks on touchscreen panels glass cover, the detection speed and accuracy are limited by the imaging module and lighting technique. Therefore the current inspection methods are still delegated to a few qualified personnel whose limited capacity has been a huge tradeoff for high volume production. In this study, an automated optical technology for in-line surface defect inspection is developed offering high performance in spatial resolution and detection speed for any surface. The inspection system consisting of an LED array which illuminates a wide inspection area on the test object captures scattered light from surface defects using a 12288-pixel line CCD at 12 kHz acquisition rate. A 3.5 \(\mu\) m per pixel resolution of the line CCD provides a detection width capability of at most 43 mm which is equivalent to 147 megapixels image data acquired per second. To handle the large volume of data per acquisition cycle, the data are transmitted from a host CPU to multiple GPU devices where CUDA-based image processing kernels are adopted to perform detection and labeling of surface defects in parallel. The processed data is sent back to the CPU to display user-defined defect maps. 2-D inspection of back-coated flat mirrors, 43 mm x 70 mm\(^{2}\) in size, using a single CCD module and multiple GPU reveals that surface flaws such as bubbles, cracks, and edge defects are detected accurately. The acquisition time to capture and load the data to a CPU is 1.7 s while the processing time to transmit the same data for surface defect detection in a GPU is 248 ms. The latter time scale is considerably faster compared to minute-long computations in solely CPU-based processing algorithm of the same test object. The minimum width of detected surface defects is about 10 \(\mu \)m with true detection rates above 94%. Moreover, the inspection system is easily configurable by tasking multiple CCD imaging modules to different GPU devices to allow inspection of larger test objects. This flexibility can improve both acquisition and detection speeds to boost in-line circuit chips, packaging, and touchscreen panel inspection systems.

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Keywords

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