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Colour vision in forest and wood engineering

机译：森林和木材工程中的色觉

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摘要

Colour is an important factor in the wood industry. Wood products are often graded by producers and consumers using colour parameters. Colour is used to sort wood for defects, but also to perform genetic screenings or to make an aesthetic judgement. The task of sorting wood following a colour scale is very complex, requiring special illumination (Singh et al., 1993; Paulsen & Mcclure, 1986) and training (Lidror & Prussia, 1989). Also, this task cannot be performed for long durations without fatigue and loss of accuracy. This paper describes a machine vision system designed to perform colour classification in real-time. Applications for sorting a variety of products are included, e.g. seeds, meat, baked goods, plants and wood. First the theory of colour classification of agricultural and biological materials is introduced. Then, some tools for classifier development are presented. Finally, the implementation of the algorithm on real-time image processing hardware and example applications for industry are described. This paper also presents an image analysis algorithm and a prototype machine vision system which was developed for industry. This system will automatically locate the surface of some plants using a digital camera and predict information such as size, potential value and type of this plant. The algorithm developed will be feasible for real-time identification in an industrial environment.
机译：颜色是木材工业中的重要因素。生产者和消费者经常使用颜色参数对木制品进行分级。颜色用于对木材进行缺陷分类，也用于进行基因筛查或进行美学判断。按照色阶对木材进行分类的任务非常复杂，需要特殊的照明（Singh等，1993; Paulsen＆Mcclure，1986）和培训（Lidror＆Prussia，1989）。同样，如果没有疲劳和精度损失，则不能长时间执行此任务。本文介绍了一种旨在实时执行颜色分类的机器视觉系统。包括用于分类各种产品的应用，例如种子，肉，烘焙食品，植物和木材。首先介绍了农业和生物材料的颜色分类理论。然后，介绍了一些用于分类器开发的工具。最后，描述了该算法在实时图像处理硬件上的实现以及行业示例应用。本文还提出了一种针对工业开发的图像分析算法和原型机器视觉系统。该系统将使用数码相机自动定位某些植物的表面并预测信息，例如该植物的大小，潜在价值和类型。开发的算法对于工业环境中的实时识别将是可行的。

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