Abstract
The main task of vision-based industrial defect inspection is to implement efficient non-contact visual quality control, i.e., to detect if there is a defect and to achieve an accurate 3D shape measurement of such a defect, and this kind of vision defect inspection system has been widely applied in various industrial application. However, it is still not the case in the inspection of transparent microdefect on the polarizer (which is the most important part of an LCD screen). Optical measurement devices (such as confocal microscopy) are often utilized to fulfil this task. To solve problems lied in the current confocal microscopy inspection system, such as expensive and non-real-time processing, this research aims to develop a novel vision-based 3D shape measurement system for polarizer transparent microdefect characterization. The innovation of this system, which has been verified by our optical model simulation, is that the 3D sizes of microdefect have a monotonically relation to the grayscale of the microdefect image. Hence, a microdefect imaging system, which could acquire defect image accurately, is first well designed and implemented. Then, a support vector regression (SVR) algorithm is derived by the trained data, i.e., 100 acquired defect images and its corresponding 3D shape value by confocal microscopy. Characterized 3D measurement of microdefect is thereby obtained by this SVR algorithm. 30 polarizer microdefect samples have been imaged and measured by our proposed system, and several important performance indicators, including processing speed, accuracy and system reproducibility, have been elaborately tested. The experimental results show that the proposed system could achieve a high-accuracy measurement but in a much faster and more efficient way than the confocal microscopy. Besides, this developed imaging system has been evaluated in real applications, and over 300 samples have been detected, which also validate the effectiveness of the proposed system.
Highlights
Industrial vision inspection, as one of the hottest researches and application topics in computer vision and artificial intelligence, has attracts more and more attention from both the academia and the industry [1]–[8]
The system is capable of quickly measuring the center depth of the polarizer defect (< 0.01s), which is 99% higher than that of the confocal microscope
The system can achieve high measurement accuracy, compared with the confocal microscope as the ground truth of measurements, the measurement accuracy can reach about 80%, so as to accurately determine whether the polarizer indentation can be repaired by itself, and improve the production practice
Summary
Industrial vision inspection, as one of the hottest researches and application topics in computer vision and artificial intelligence, has attracts more and more attention from both the academia and the industry [1]–[8]. Cao et al [21] proposed a large-complex-surface surface defect detection system, and the size of detection area on the equipment cabinet surface is 500 mm × 470 mm These systems were developed to ac-quire the 3D shape measurement either by multi-camera vision or structured light vision, and none of them could be applied to the measurement of polarizer defect due to its super-small size. A novel vision-based fast 3D shape measure-ment system for polarizer transparent microdefect char-acterization, is elaborately researched in this work. The innovation of this measurement system is that the 3D sizes of microdefect have a monotonically relation to the grayscale of the microdefect image, which has been verified by our optical model simulation.
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