【作者】 李明涛；

【导师】 王宏伟；

【作者基本信息】 大连理工大学 ， 控制理论与控制工程， 2007， 硕士

【摘要】 木材材积的测量方法如手工测量查表求取、激光测量等耗费人力物力、成本高、精度低，很难适应当今社会经济的发展和我国各行业对于木材需求量增加的国情。从上世纪90年代初，国内开始从事应用计算机视觉的方法进行木材的在线自动计数和材积测量的研究，取得了一定的成果，但还处于理论研究阶段，没有出现成熟的产品。基于数字图像处理的木材材积测量技术正是为了克服上述困难应运而生的。木材材积测量技术具有成本低廉，操作简单，处理速度快等优点。木材材积测量系统的研究不仅具有一定的理论意义，同时还具有良好的市场前景。本课题是采用计算机视觉的方法进行木材材积和数量的测量，主要研究内容是系统的软件部分，包括图像的采集显示、预处理、物体的分割、材积和数量的测量。图像处理中，能否达到满意的处理效果，图像预处理是很关键的一步，它是其它算法的基础，本文根据木材截面的特点，提出了根据颜色空间的提取、改进的图像标记等算法改善目标提取效果，基本上能达到满意的预处理效果。另外根据图像处理的具体特点，文中提出了一种新的基于类圆的粘连体分割方法，当物体间的缝隙在二值化后能部分或全部判定为背景，即粘连的物体在二值化后能有明显的凹陷时，识别率很高，误差几乎可以为零。反之，则误差会上升。最后通过对分割后的图像进行标记处理，计算各个截面的最小直径，找出相对应的木材材积。对图像进一步腐蚀，再做标记，统计标号的个数，即图像中木材的根数。形成木材材积计算的非接触测量系统。本文在最后进行了试验总结和误差分析，分析了造成系统误差的各种因素，从实际的角度对考察系统的实用性进行分析，指出进一步开发的方向和建议。为木材数量和材积计算软件的商业化打下了良好的基础。更多还原

【Abstract】 At present, almost all company count log volume one by one by workers or laser light, it is laborious, low effective, also counting by workers may cause high error and high cost. So, these manufactories desire a cheap counter and volume-meter. From the first of 1990s, by using computer vision, studies of this area had been begun. Although a bit progress had been got since then, there is much to do if it is used at spot in factory. This study do some research on theory, the product will have a good future.Based on digital image process, the log volume-meter technology is born to conquer the drawback of previously methods. It has many merits such as low cost, easy operation, and high efficiency. The research of log volume-meter system not only has the sense of theory, but also has bright market prospect.In this paper, the author tries to measure the log volume of image by making use of computer vision. The main research includes the following area: image acquisition and display, pre-process, segment of object, measurement of log quantity and volume. During the image process, whether can we get an ideal result depend on the pre-process of image which is the foundation of the whole system. In this paper, the algorithm threshold the object through the specified color space, and mend the image through labeling algorithm. We can get a acceptable result as expected. A new segmentation method based on quasi-circular assumption is presented. This method require a good binary image, if it exist concave, the aggregated objects will be segmented and recognized correctly and the error is lower, otherwise, it may lead to error result. Finally, the software counts the min diameter of each log from the pre-process image. After erosion and labeling of image, it can gain the quantity of the log. This is a non-contact measurement system.This paper finally presents the experiential result and error analyse. I analyse the practicability of the system from the view of application, and provide suggestions of further development which pave the way for the application of the system.更多还原