Lens surface defect intelligent detection system based on machine vision and its implementation method
A technology of intelligent detection and realization method, applied in the direction of instruments, measuring devices, scientific instruments, etc., can solve the problems of difficult to achieve unified judgment standards, missed detection, poor result accuracy, etc., to reduce manual operation of buttons, improve detection efficiency, The effect of low manufacturing cost
Active Publication Date: 2019-03-12
FUZHOU UNIV
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Problems solved by technology
[0002] At present, most domestic lens manufacturers use manual sampling for quality inspection. This method has low efficiency in the quality inspection process, poor accuracy of quality inspection results, and the following serious defects: (1) It is prone to missed inspections, Long-term repetitive work makes the human eye fatigue easily, which often leads to missed inspection of waste products, causing serious losses to lens manufacturers and users, and causing extremely bad social impact; (2) Unable to guarantee uniform quality standards, manual inspection, Whether it is qualified or not is subjectively judged by the inspector according to the feeling, and it is difficult to unify the judgment standards of different people or even the same person in different states; (3) The data records and storage of manual inspection are not digitized, and the data of the inspection results cannot be realized share in real time
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[0043] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0044] This embodiment provides an intelligent detection system for lens surface defects based on machine vision, such as figure 1 As shown, it includes an image acquisition unit, a PC, a data processing unit, a manipulator unit and a transmission unit; the output end of the image acquisition unit is connected to the input end of the PC, so as to transmit the captured lens defect image to The PC; the output end of the PC is connected to the input end of the data processing unit, and the output end of the data processing unit is connected to the manipulator unit and the transmission unit.
[0045] In this embodiment, the image acquisition unit includes an industrial camera, the industrial camera is connected to the PC through a USB interface, and the industrial camera is arranged above the conveyor belt.
[0046] In this example, if figure 2As shown, ...
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The invention relates to an intelligent detection system for lens surface defects based on machine vision and an implementation method thereof, which includes an image acquisition unit, a PC, a data processing unit, a manipulator unit and a transmission unit; the output end of the image acquisition unit and the The input end of the PC is connected to transmit the collected lens defect images to the PC; the output end of the PC is connected to the input end of the data processing unit, and the output end of the data processing unit is connected to the PC. The robot unit and the transfer unit are connected. The PC in the present invention uses Matlab to develop defect identification algorithms, determines whether there are defects in the lenses, transmits the data to the single-chip computer, removes the defective lenses through the single-chip computer and the manipulator, and displays the defects on the human-computer visualization interface, thereby realizing machine vision online test.
Description
technical field [0001] The invention relates to the field of lens detection, in particular to a machine vision-based intelligent detection system for lens surface defects and an implementation method thereof. Background technique [0002] At present, most domestic lens manufacturers use manual sampling for quality inspection. This method has low efficiency in the quality inspection process, poor accuracy of quality inspection results, and the following serious defects: (1) It is prone to missed inspections, Long-term repetitive work makes the human eye fatigue easily, which often leads to missed inspection of waste products, causing serious losses to lens manufacturers and users, and causing extremely bad social impact; (2) Unable to guarantee uniform quality standards, manual inspection, Whether it is qualified or not is subjectively judged by the inspector according to the feeling, and it is difficult to unify the judgment standards of different people or even the same per...
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IPC IPC(8): G01N21/958G01N21/01G06T5/00G06T7/00
CPCG06T7/0008G01N21/01G01N21/958G01N2021/0181G06T2207/30108G06T2207/20032G06T2207/20224G06T5/70
Inventor 任志英张志忠陈炳兴郭毅强黄艺坤
Owner FUZHOU UNIV