Automatic detection of sound knots and loose knots on sugi using gray level co-occurrence matrix parameters

Abstract

& Context Knowledge of the occurrence of sound and loose knots on the surface of sawn sugi (Cryptomeria japonica L.f.) is important for its grading and application. & Objectives This study examined an optical system for detecting sound and loose knots in sugi instead of human being using the combining information of the color and texture features. & Methods The proposed system could be conceptually divided into two components: a CCD camera scanning system and a defect detecting algorithm developed by the authors. In the algorithm, the contrast parameter calculated from a graylevel co-occurrence matrix was used to locate the potential defects represented by sound knots and loose knots. The rulebased approach, which was built according to the color feature histograms, was used to identify sound knots and loose knots. A series of samples containing single or multiple sound and/or loose knots were selected at random to verify the efficiency and accuracy of the proposed system. & Results There were 94 sound knots and 86 loose knots on the surfaces of these samples, and the accuracy of locating the positions of sound knots and loose knots was 94.7% and 97.6%, respectively. The accuracies of identifying knots as sound or loose were 96.6% and 98.8%, respectively. The overall detection accuracy of the system was 93.9%. & ConclusionsThe results indicate that the proposed vision system is an efficient means of detecting sound knots and loose knots.

Effect of knots and holes on the modulus of elasticity prediction and mapping of sugi (Cryptomeria japonica) veneer using near-infrared hyperspectral imaging (NIR-HSI)

“…It should be noted that knots have a weaker effect on the surrounding area than holes ( Figure 5). The mapped MOE data also differentiated between a sound knot (intergrown knot) and a dead knot (encased knot), which was also identified previously (Hu et al 2004(Hu et al , 2011. Figure 6 shows that a sound knot has less predicted MOE values compared to a dead knot.…”

Recent research and development advances of wood science and technology in China: impacts of funding support from National Natural Science Foundation of China

“…Green processing in the regulation of pollution, energy consumption, and carbon emission has been given more emphasis due to the emerging problems of environmental pollution and climate change. For wood machining, research mainly focuses on the theory and technology of sawing for small diameter logs, zero-degree clearance angle sawing, virtual slicing (Chen and Zhao 2012), optimum cutting (Zheng et al 1989), detection and elimination of defects (Yu and Qi 2011;Hu et al 2011), fuzzy control of planning process (Han et al 2004), wide belt sanding, and sanding for heterogeneous surfaces (Wang et al 2012a). For wood drying, researches have been focused on drying methods of timbers, including vacuum drying (He et al 2013), microwave drying (Li et al 2005), superheated steam drying (Cheng et al 2004), radio-frequency vacuum drying , combined drying, and energy-saving drying (Gu 2007).…”

A Quality Control System Prototype for Detecting Knot Defects in the Wooden Panel Manufacturing

“…These techniques are in use and becoming popular in the quality control of products such as textile [3][4][5][6], ceramic [7][8][9], steel [10,11], glass [12], electronic circuits [13], weld bead [14] , metal lids [15] and cylindrical parts [16] to keep up with high quality standards set by the competitive markets. There are also academic studies [17][18][19][20][21][22] on applying image processing techniques in the quality control of wooden surfaces. There are existing quality control systems in the wider wood industry.…”