• 论文与研究报告 •

### 基于数学形态学的木材单板节子识别改进算法

1. 1. 中国林业科学研究院林业新技术研究所 北京 100091;
2. 中国林业科学研究院木材工业研究所 北京 100091
• 收稿日期:2014-08-11 修回日期:2014-10-11 出版日期:2015-09-25 发布日期:2015-10-16
• 通讯作者: 郭文静
• 基金资助:

中国林业科学研究院林业新技术研究所基本科研业务费专项基金项目"基于图像识别的装饰单板外观分等技术研究"(CAFINT2013C06)。

### An Improved Algorithm of Veneer Knot Image Recognition Based on Mathematical Morphology

Chen Yongping1,2, Guo Wenjing1, Wang Zheng1

1. 1. Research Institute of Forestry New Technology, CAF Beijing 100091;
2. Research Institute of Wood Industry, CAF Beijing 100091
• Received:2014-08-11 Revised:2014-10-11 Online:2015-09-25 Published:2015-10-16

[目的] 提出一种基于数学形态学的木材单板节子识别改进算法,对木材单板表面节子进行快速识别和面积判断,旨在转化生产中由计算机智能控制自动分等代替人力分拣,提高木材单板分等效率。[方法] 选取带有节子的木材单板为研究对象,以图像识别初步结果为基础,首先采集木材单板图像并进行灰度变换; 然后根据灰度图像中节子和背景占据的不同灰度级范围,运用最大熵原理选择灰度阈值对图像进行分割,使节子从背景中初步分离出来; 接着通过形态学运算去除各初选节子外部的干扰特征量,使节子外轮廓得以较准确显现; 最后增加检出特征的外形轮廓判定,以防止板面可能存在的裂缝、污痕等其他特征量因颜色较深从背景中分离出来,被误检识别为节子。[结果] 图像分割处理后节子周围存在的一些干扰特征量,通过形态学膨胀处理可切断干扰特征量和节子之间的联系,膨胀后继续进行腐蚀操作可保持节子真实大小,比较形态学开闭运算2种处理方法,形态学闭运算处理后节子更容易被识别出; 检出的特征轮廓在进行椭圆拟合后辅以符合节子外形的条件限制可以提高识别精度,防止非节子被检出,其中通过计算特征轮廓点和拟合椭圆的匹配度大小可以初选是否符合节子特征,节子外形的条件限制主要用于过滤一些虽能拟合为椭圆但为长形物体比如裂隙等的影响。[结论] 通过本项研究,可直观获取单板表面的节子数量和节子相对大小,其实际生产中使用硬件对接后,根据图像采集设备与待采集对象的相对位置、采集图像的分辨率等情况,结合系统判定结果可得出节子的真实大小,实现木材单板的自动分等。

Abstract:

[Objective] Knot is an important evaluation index in the classification of wood veneer. The quantity of veneer knots and the maximum knot area can, to some extent, determine the grade of a wood veneer. Whereas by now, the classification of wood veneer processed in China mainly depends on visual inspection, which is of low efficiency. Therefore, quick identification and area assessment are performed to the surface knot of wood veneer with image recognition. Instead of artificial sorting is automatic classification by computer smart control, which can significantly promote the classification efficiency of wood veneer and is of great significance for the development and progress of wood industry. [Method] The wood veneer with knots are selected as object in this study. Bases on the preliminary results of image identification, an improved identification calculation for wood veneer knots using mathematical morphology is proposed. In order to solve the problem of missing characteristic quantity of partial knots or identification of non-knot characteristic quantity existing in the image identification of wood veneer, this work can be divided into 5 steps, those were, original image extraction, graying processing, image segmentation, margin inspection of characteristic quantity and knot identification. Firstly, images of wood veneer are collected, and grey level transformation is performed for the images for sequential image identification. Secondly, according to the knots in the gray images and different gray scope in the background, the image is split with the gray threshold chosen by the maximum entropy principle, so as to preliminarily separate the knots from the background. Then the interference characteristics outside the knots preliminarily selected are removed with morphological algorithm, thus the outer contour of knots can be accurately presented. Finally, outline assessment is performed for the characteristics detected, to prevent other factors such as crack and dirt being separated from the background due to their dark color and considered as knots. [Result] This study shows that, there are some interference characteristics around the knots after image segmentation, the relationship between interference characteristics and knots can be cut off by morphological expansion, and the corrosion operation after expansion can maintain the real size of knots. By comparing the morphological opening-and-closing operations, it is found that the knots processed by morphological closing operation can be more easily identified. The identification accuracy can be improved by performing ellipse fitting and outline condition restriction for the characteristic profile inspected, to prevent the identification of non-knots. Furthermore, knots can be preliminary assessed by calculating the characteristic profile points and the matching degree of ellipse, and the knots outline restriction is mainly used for filtering the influence of rectangular objects (such as crack) that can be fitted into ellipse. [Conclusion] The knots quantity and relative size on the surface of wood veneer can be obtained by visual inspection, in the practical production processes, after interfacing with hardware, the real size of knots can be obtained according to the relative position of image collecting equipment and collecting objects and the resolution of images collected, etc. by combining the system assessment results, thus to realize the automatic classification of wood veneer.