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Deep learning product defect detection system and method based on Raspberry Pi

A deep learning and product defect technology, applied in the field of image recognition, can solve problems such as high cost

Pending Publication Date: 2020-12-01
FOSHAN UNIVERSITY
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Based on this, in order to solve the problem of the high cost of using industrial CCD, PLC industrial computer and Labview programming to realize the detection and identification of defective products in the prior art, the present invention provides a deep learning product defect detection based on Raspberry Pi System and method, its specific technical scheme is as follows:

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  • Deep learning product defect detection system and method based on Raspberry Pi
  • Deep learning product defect detection system and method based on Raspberry Pi
  • Deep learning product defect detection system and method based on Raspberry Pi

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Embodiment Construction

[0039] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with its embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0040] It should be noted that when an element is referred to as being “fixed” to another element, it can be directly on the other element or there can also be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and similar expressions are used herein for purposes of illustration only and are not intended to represent the only embodiments.

[0041] Unless otherwise defined, all technical and scientific t...

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Abstract

The invention provides a deep learning product defect detection system based on Raspberry Pi, and the system comprises: an collection module which is used for collecting an image of a to-be-detected product; the Raspberry Pi that is in communication connection with the acquisition module, receives and preprocesses the acquired image of the product to be detected, identifies a defective product according to the preprocessed image of the product to be detected, and acquires image information of the defective product; and the display module that is in communication connection with the Raspberry Pi, receives the defective product image information, and displays a defective product image and a defective product image contour according to the defective product image information. The invention can realize detection and identification of defective products, has the advantage of low cost, and has very high popularization and use values. Correspondingly, the invention further provides a deep learning product defect detection method based on the Raspberry Pi.

Description

technical field [0001] The present invention relates to the technical field of image recognition, in particular to a deep learning product defect detection system and method based on Raspberry Pi. Background technique [0002] In modern manufacturing, machine vision technology has undergone earth-shaking changes and has become an irreplaceable link. Machine vision technology based on deep learning has been widely used in processing fields such as machinery, packaging, and cosmetics. For example, in disease diagnosis, machine vision technology can diagnose various medical images. By recognizing ophthalmic OCT images, the corresponding diseases can be known. For example, in industrial manufacturing, SVM support vector machine technology can be used to detect product defects, which improves the accuracy while improving production efficiency and reduces manpower and material expenditures. Another example is in automatic driving, machine vision technology can identify complex s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/13G06T5/00G06N3/04G06N3/08G06K9/00G01N21/88
CPCG06T7/0004G06T7/13G06N3/08G01N21/8851G06T2207/10024G06T2207/20081G06T2207/20084G06T2207/30108G01N2021/8887G06V20/10G06V2201/06G06N3/045G06T5/70
Inventor 谭泰铭
Owner FOSHAN UNIVERSITY
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