Smoothness-characteristic-quantity-based surface gray scale defect detection method for rotary-cut wooden product

Abstract

The invention relates to a smoothness-characteristic-quantity-based surface gray scale defect detection method for a rotary-cut wooden product. The method comprises the following steps: acquiring an image of the rotary-cut wooden product by using CCD (Charge Coupled Device) cameras placed at the middle upper positions of two LED (Light-Emitting Diode) strip light sources which are arranged symmetrically and adopt high-angle illuminating ways serving as illumination light sources, converting the acquired image into a digital signal through an image acquiring card, and transmitting the digital signal to a computer system; performing target area determination, smoothness characteristic quantity calculation and gray scale defect judgment on the input image, wherein the judgment threshold value of each gray scale defect is determined by using a self-adaptive maximum interclass variance method. By adopting the detection method, automatic online detection on the surface gray scale defects of the rotary-cut wooden product is realized, the production cost is reduced, the detection efficiency is increased, the detection rate of the gray scale defects is increased greatly, and the phenomena of detection missing and error detection are well overcome.

Description

technical field [0001] The invention relates to the fields of machine vision and product quality inspection, in particular to a method for detecting surface gray defects of rotary-cut wood products based on smoothness feature quantities. Background technique [0002] Due to natural wood raw materials and production processes, the surface of disposable rotary-cut wood products produced contains various types of grayscale defects, such as knots, discoloration, decay, boreholes, green skin and pollution, etc.; Moreover, such rotary-cut wood products containing grayscale defects cannot be used for subsequent production and use. Therefore, it is necessary to detect surface grayscale defects of rotary-cut wood products, reject unqualified products, or adjust the production process appropriately parameters to improve the yield and product quality of wood products. [0003] At present, the manual visual inspection method is mainly used to detect the surface gray defects of rotary c...

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Problems solved by technology

[0007] In order to overcome the low detection efficiency, low degree of automation, inability to use non-contact visual detection methods, and existing statistical features based on mean, variance, skewness, etc. In order to solve the problems of missed detection and wrong detection, the present invention provides a method for detecting surface gray defects of rotary cut wood products based on smoothness feature quantity

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