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Title: Measurement of cutter marks on planed wood surfaces with machine vision methods
Author: Yang, Diming
ISNI:       0000 0004 2704 5102
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2006
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Cutter marks on machined wood surfaces are generated by the planing and moulding wood machining process. Cutter mark defect is referred to as inconsistency of widths and heights of the cutter mark waves, which is critical in some sectors of the woodworking industry. Machining speeds in the woodworking industry are remarkably high. In order to meet the demands of high efficiency and high quality, in-process measurement of cutter marks on machined wood surfaces is highly desirable. Machine vision technology is being widely used in various quality control applications due to its advantages of non-contact and high data rates. Clearly, machine vision is also highly suitable for in-process measurement of wood surfaces. This research focuses on using machine vision techniques to measure cutter marks on planed wood surfaces. Before machine vision methods are investigated, a laser profilometer is investigated for its feasibility of measuring cutter marks on wood surfaces. Although the profilometer cannot be used for in-process applications, it provides a good reference for other methods. Three major machine vision methods and their vanatwns are investigated. They are the Light Sectioning method and the Differential Light Sectioning method, the Shadow Analysis method and the Multi-Angle Shadow Analysis method, the two Image Photometric Stereo method and the one-Image Shape From Shading method. Nme samples, made of three species of wood - beech, oak and ramin, with cutter mark widths of l.5mm, 2mm and 2.5mm generated on the samples of each species, are tested. Surface profiles measured with all the machine vision methods are compared to the reference profiles measured with the laser profilometer. Experiments indicate that the Light Sectioning method and the Shadow Analysis method both work to some extent, the Differential Light Sectioning method and the Multi-Angle Shadow Analysis method are not practical; the two-Image Photometric Stereo method is the most reliable machine vision method among all the methods investigated; and the one-Image Shape From Shading method needs further studies.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Mechanical Engineering not elsewhere classified ; Wood surface quality ; Cutter mark ; Machme vision ; Light sectiomng ; Shadow analysis ; Photometnc stereo