Computer image based automatic identification method of timber knot flaws

Abstract

The invention discloses a computer image based automatic identification method of timber knot flaws. The method comprises the major steps of firstly, acquiring timber images by use of digital cameras, secondly, performing preprocessing, such as image recombination, image denoising and image enhancement, on the acquired timber images, thirdly, performing characteristic extraction on the preprocessed images by use of an image digital processing algorithm, fourthly, judging the quasi-circle or ellipse shape features of the timber flaws by virtue of Hough transformation according to flaw edge characteristics and determining candidate regions, fifthly calculating the area of knot flaws by use of a line-by-line pixel area scanning algorithm, and sixthly, identifying the timber knot flaws by use of a comparison area threshold and characteristic parameters. The method is used for identifying the timber knot flaws by use of the image identification technique, and is high in identification accuracy, high in speed and simple to operate; the method is capable of meeting the requirements of the modern timber processing industry on the knot flaw identification speed and quality, and also capable of accurately locating the knot flaws to facilitate high-speed automatic cutting of the knot flaws.

Description

technical field [0001] The invention belongs to the technical field of wood processing, and relates to a computer image automatic recognition method for wood knot defects. Background technique [0002] my country's timber market demand is huge, and the quality of timber processing has gained more and more attention. The quality of wood processing is closely related to the level of wood processing technology, and the identification of wood defects determines the advanced level of wood processing technology. National standard sawn timber defects (GB / T4823-1995) stipulates that wood defects are divided into nine categories: knots, discoloration, decay, moths, cracks, wood structure defects, processing defects, deformation and damage, among which knots are the biggest defects of wood. Therefore, the identification of wood defects mainly focuses on the identification and detection of knots. At present, for the identification of wood knot defects, most domestic wood processing e...

AI Technical Summary

Problems solved by technology

[0004] The invention provides a computer image automatic recognition method for wood knot defects, which overcomes the disadvantages that the traditional knot defect recognition method is easily disturbed by human subjective consciousness and difficult to meet the high-speed and precise requirements of wood processing automation at the same time

Images