Abstract
Production technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is insufficient for conducting quality control under this increased capacity. Therefore, high-speed and high-accuracy automated optical inspection is becoming increasingly crucial. In this article, we propose an automated inspection method for a compact camera lens using a circle Hough transformation, weighted Sobel filter, and polar transformation. Our analysis of defects in the compact camera lens identified problems including of the circular texture and the non-fixed position of the inspection region. To overcome these problems, we design an inspection algorithm for locating and inspecting a circular region. A machine learning support vector machine method is then applied for obtaining a precise detection result. The experimental results show that the proposed inspection method is suitable for detecting defects in a complicated circular inspection region, and that the proposed system exhibited high performance.
Highlights
Automatic optical inspection (AOI) techniques are becoming increasingly crucial in various applications because quality control plays an important role in contemporary manufacturing
We propose an automatic inspection method for a compact camera lens using a weighted Sobel filter, polar coordinate transformation, and support vector machine (SVM) classification method
We analysis the characteristics of defects, and we propose a hybrid-based inspection algorithm for a compact camera lens to solve the problems
Summary
Automatic optical inspection (AOI) techniques are becoming increasingly crucial in various applications because quality control plays an important role in contemporary manufacturing. A simple thresholding method can be applied to high-intensity defect detection This approach fails when the image quality of the captured image is low or has insufficient contrast. The aforementioned inspection approaches fail when the intensity or contrast of the defective regions is similar to the texture of the testing image. If the shape of a defective region is similar to the texture of the product’s surface, the frequency-based inspection approach cannot be applied. A hybrid strategy is applied to detect defects when using a compact camera module because this approach can suffer from various defects and problems including defocus, black/white dots, color defects, line defects, and dim defects.[8,9,10] AOI has been used to check the surface of a lens and a printed circuit board.[11,12] Discrete cosine transform has been used for measuring energy, which represents the amount of change in intensity.
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