利用计算机视觉技术的烟叶质量分选系统研究

利用计算机视觉技术开发了烟叶质量分选系统。该系统对采集系统进行定标，控制感光度。提取了180个特征参数并进行选择形成特征向量，去除了标准样本中的奇异样本。利用人工神经网络对多个地区的烟叶进行学习和分类，检测准确率均在80%以上，半数地区检测准确率在90%以上。对烟叶分类该系统具有较高的实用价值。

Application of Computer Vision Technique to Research on Classifying System of Tobacco Leaves

Examining the external quality of tobacco leaves is now mostly relied on the sense of human being. A computer vision system of tobacco leaves grading was introduced in this paper. This system has some subsystems. The demarcation system can control and set the phototonus of CCD camera. The learning system is used to extract and select eigenvalue, then to constitute characteristic vector. It can also remove the freak samples from the standard samples. The neural network is used to learn and grade the tobacco leaves in several areas. And the results of grading indicated that the examination precision of computer vision is all above 80% coincided with grading of human being, and about a half of products from different areas are more than 90%. So this system is highly practical in tobacco leaves garding.