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Machine vision based portable computer touchpad edge detection method

A portable computer, edge detection technology, applied in instruments, image data processing, computing and other directions, can solve problems such as false detection

Inactive Publication Date: 2018-11-30
FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST +1
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Problems solved by technology

[0004] The purpose of the present invention is to propose a machine vision-based portable computer touchpad edge detection method, using machine vision technology instead of manual detection, to achieve fast, effective and accurate detection of portable computer touchpad edge defects, thereby improving detection efficiency and effectively solving manual problems. Detection of false positives and missed detections

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  • Machine vision based portable computer touchpad edge detection method

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Embodiment Construction

[0019] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and through specific implementation methods.

[0020] A kind of portable computer touchpad edge detection method based on machine vision of the present embodiment, portable computer touchpad edge detection method comprises the following steps:

[0021] Step A: If figure 1 As shown in S1, the image of the edge of the touchpad is collected using a visual imaging system;

[0022] Preferably, it includes using a prism imaging principle to collect the edge image of the touch panel. By using the refraction principle of the prism, the polychromaticity of the image can be maintained, so that the collected edge image of the touch panel is clear and complete without deviation, and the edge image of the computer touch panel in the small gap can be obtained effectively.

[0023] Step B: If figure 1 As shown in S2, according to the collected touchpad edge...

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Abstract

A machine vision based portable computer touchpad edge detection method is disclosed. The portable computer touchpad edge detection method comprises the following steps: acquiring a touchpad edge image by using a visual imaging system; extracting an image ROI of the touchpad edge image according to the acquired touchpad edge image; pre-processing the extracted image ROI by mean filtering; segmenting the image ROI of the touchpad edge image by using a threshold method; obtaining a connected region of the image ROI of the segmented touchpad edge; and determining and selecting a defective area according to the connected region. The machine vision based portable computer touchpad edge detection method adopts the machine vision technology to replace manual detection to realize fast, effective and accurate detection of edge defects of the touchpad of the portable computer, thereby improving the detection efficiency and effectively solving the problem of wrong and missed detection due to manual detection.

Description

technical field [0001] The invention relates to the technical field of edge detection, in particular to a machine vision-based portable computer touch panel edge detection method. Background technique [0002] Edge defect detection of touchpads of portable computers is very important to the production of touchpads of computers, which is related to the experience of users using computers and the service life of touchpads of computers. In the actual production process, the detection of edge defects on touchpads of portable computers is basically done by human eyes. The detection accuracy of the traditional method is not high, and it is prone to false detection and missed detection. Moreover, the efficiency of manual detection is low, and it cannot detect edge defects quickly and effectively, and cannot meet the actual production needs. [0003] Machine vision refers to the use of machines instead of human eyes for measurement and judgment. Through machine vision products, the...

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Application Information

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IPC IPC(8): G06T7/13G06T7/136G06T7/187
CPCG06T2207/10004G06T2207/20024G06T7/13G06T7/136G06T7/187
Inventor 李启宏王华龙魏登明李力李志鹏
Owner FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST
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