| 1. | Application of artificial neural networks in the testing of wood defects
人工神经网络在木材缺陷检测中的应用 |
| 2. | Illustrative plats of defects in wood
木材缺陷图谱 |
| 3. | Defect in timber
木材缺陷70 |
| 4. | The influence factors of fracture life are composites boards lay structure , wood - lacuna , and bamboo structure
影响疲劳蠕变断裂寿命分散性的因素主要有层合板的铺设结构、木材缺陷和竹材结构等的影响。 |
| 5. | After the experimental certification , the application of mathematical morphology for image post - processing enhanced the visibility and the accuracy of the segmentation results of wood surface defect images
经实验验证，应用数学形态学进行图像后处理，增强了木材缺陷图像分割结果的可视性和准确性。 |
| 6. | The theory that discern the log knobs flaw by video method provide the essential theory premise and technology for the design and application of wood flaw detecting and discerning
本论文研究的视频识别原木节子缺陷的理论，为工业化木材缺陷计算机视频检测设备的设计与应用，提供了必要的理论前提和技术基础。 |
| 7. | After the experiment of sample log was carried out . the software is correct and accurate . to distinguish the log internal defect by x - ray scanner provide the essential theory premise and technology for the design and application of wood flaw detecting and discerning
本论文研究的利用x射线测定原木内部缺陷的理论，为工业化木材缺陷计算机视频检测设备的设计与应用，提供了必要的理论前提和技术基础。 |
| 8. | Firstly , the thesis concluded the methods of detecting technology by computer vision in forest industry . based on analyzing the development of image processing and pattern recognition in detail and on outlining the present methods , the thesis illuminated the present level of the computer vision technology used in wood processing ; visual c + + 6 . 0 of microsoft company is applied as a tool to develop image - processing module
本文首先对计算机视觉检测技术进行了概述，然后较为深入的阐述了图象处理和模式识别等技术，对现有的木材缺陷检测的主要方法进行了总结评述，阐明了目前视觉检测技术在木材加工中的应用及发展水平；本文运用微软公司的visualc + + 6 . 0作为开发工具。 |
| 9. | The thesis is an important part of the project application of machine vision in wood surface defect defection that aided by the fund of national nature science . in the system , the machine vision system is used to automatically recognized the wood defects by the neural network , and has been researched the model patterns of wood defects
本文是国家自然科学基金资助项目“计算机视觉技术在木材表面缺陷检测中的应用”的重要组成部分，应用计算机视觉系统，通过神经网络模式识别技术对木材缺陷的自动识别，对木材缺陷模式特征进行了研究。 |
