Wood surface defect detection method and system based on machine vision

A wood surface, machine vision technology, applied in neural learning methods, optical testing flaws/defects, instruments, etc., to achieve the effect of ensuring accuracy, high degree of automation, and reducing errors
CN112102254APending Publication Date: 2020-12-18FOSHAN POLYTECHNIC
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
FOSHAN POLYTECHNIC
Publication Date
2020-12-18

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Abstract

The invention discloses a wood surface defect detection method and a wood surface defect detection system based on machine vision, which can enhance the texture of a wood image, perform noise removalpreprocessing on the image by using median filtering, construct a neural network recognition model and an improved BP neural network algorithm, and provide a two-stage neural network board surface defect detection model structure. Errors are effectively reduced, the detection precision is ensured, and the product quality is improved; by arranging a servo motor and a lead screw, manual operation can be completely replaced in the wood board surface defect detection process, and the automation degree is high. In the process that the camera collects images of the surface of a wood board, accordingto the type and specification of the wood board to be detected, an upper computer sends the type and specification of the wood board to a PLC, the servo motor drives the lead screw to conduct transmission, the camera is moved to the corresponding position, positioning is accurate, image collection of wood boards of different types and specifications is achieved, and the detection efficiency of the board is improved.
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Description

technical field

[0001] The invention relates to the technical field of wood detection, in particular to a method and system for detecting wood surface defects based on machine vision. Background technique

[0002] The factors that affect the quality of wood mainly include: surface defects, size and color and so on. In the prior art, the detection of the wood surface is mainly carried out manually, and the detection effect and efficiency mainly depend on the experience of the inspectors, and the human influence factors are large and the degree of automation is very low. At the same time, the manual inspection operation also has the disadvantages of high labor intensity and low production efficiency.

[0003] As far as the detection method is concerned, the existing wood surface detection technology also has the following disadvantages: 1) The traditional contact measurement technology restricts the wood production efficiency and processing accuracy, and reduces the quality o...

Claims

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