Wood defect detecting and sorting device and method based on depth camera and deep learning

Abstract

The invention discloses a wood defect detecting and sorting device and method based on a depth camera and deep learning, the wood defect detecting and sorting device comprises an industrial personal computer, a detecting mechanism and a sorting mechanism arranged on the rear side of the detecting mechanism, and the detecting mechanism comprises a detecting conveying belt and a depth image collecting mechanism. According to the method, RGB images and depth information of the wood surface are collected through a depth camera, and RGBD color depth information is reconstructed through combinationof a GAN network and wavelet transform. In wavelet transformation, wood cracks in training data are manually marked, and a self-adaptive crack wavelet basis function is formed. Wavelet reconstructionis carried out on the basis to improve the efficiency of a subsequent algorithm, and the defect type is obtained through analysis in combination with a deep learning algorithm. The algorithm can sortwoods with different defect types, so that the defect discrimination efficiency is improved, and the sorting efficiency is greatly improved.

Description

technical field [0001] The invention belongs to the field of wood defect detection, and in particular relates to a wood defect detection and sorting device and method based on a depth camera and deep learning. Background technique [0002] Timber is widely used in home furnishing and house construction. With the continuous increase of timber market demand and limited forestry resources, there will be waste of timber raw materials. One of the main reasons is the lack of accurate detection of timber defects. Defects on the wood surface mainly include wormholes, cracks, nodules, etc. The traditional manual inspection method has low detection efficiency and high technical requirements for inspectors, so it is no longer suitable for the current wood production. Today there is a need for rapid non-destructive testing of wood defects using new detection methods. Contents of the invention [0003] Purpose of the invention: In view of the deficiencies in the prior art, the purpose...

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Problems solved by technology

[0002] Timber is widely used in home furnishing and house construction. With the continuous increase of timber market demand and limited forestry resources, there will be waste of timber raw materials. One of the main reasons is the lack of accurate detection of timber defects. Defects on the wood surface mainly include wormholes, cracks, nodules, etc. The traditional manual inspection method has low detection efficiency and high technical requirements for inspectors, so it is no longer suitable for the current wood production

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