Transparent material internal defect detection method based on time-sharing exposure image synthesis

Abstract

The invention relates to a transparent material internal defect detection method based on time-sharing exposure image synthesis, and the method is characterized in that bright field irradiation and dark field irradiation are respectively carried out on a to-be-detected object made of a transparent material in transmission, and a camera acquires a bright field image and a dark field image of the surface of the to-be-detected object in a time-sharing exposure mode; after suspected defects are extracted from a bright field, the suspected defects are converted into a dark field for re-judgment, complex and time-consuming filtering processing is not required to be designed in the bright field, and the overall operation time is shortened; comprehensive processing is carried out in the bright anddark field images, and discrimination for distinguishing defects and dust is achieved through dark field assistance, so that the defect detection rate is improved; complex frequency domain processingis not needed, the development period is shortened, and the later maintenance of developers is easy; and the whole logic design is simplified, the algorithm development period is shortened, the algorithm operation efficiency is improved, and the detection problem in the actual production process of the AOI equipment is improved.

Description

technical field [0001] The invention relates to the technical field of defect detection, in particular to a method for detecting internal defects of transparent materials based on time-sharing exposure image synthesis. Background technique [0002] With the rapid development of the mobile phone industry, especially the development of 5G communication technology, the demand for transparent materials such as glass is increasing day by day. However, transparent materials such as glass are prone to internal defects during the processing process. At present, more manual inspection is performed, which is inefficient and expensive. Therefore, there is an urgent demand for this type of AOI equipment (automatic optical inspection equipment). When detecting internal defects of transparent materials, it is most likely to be interfered by dust and dirt on the surface of the material. Traditional transparent materials are processed by a single field of view algorithm. The logic design of...

AI Technical Summary

Problems solved by technology

However, transparent materials such as glass are prone to internal defects during processing, and currently more manual inspection is performed, which is inefficient and expensive, so there is an urgent need for this type of AOI equipment (automatic optical inspection equipment)

When detecting internal defects of transparent materials, it is most likely to be interfered by dust and dirt on the surface of the material. Traditional transparent materials are processed by a single field of view algorithm. The logic design of the single field of view algorithm is complicated, takes a long time and cannot meet the production inspection requirements. Moreover, the time-consuming algorithm leads to an increase in the detection time of AOI equipment; the foreground extraction of the algorithm is easily disturbed by surface dust and dirt, and the detection rate is low, which cannot meet the requirements of AOI detection and replacement labor; the cost is too high, and the development cycle is long. The comprehensive effect is poor and it is not easy to debug

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