In this paper , we introduce a recently finished image - processing system for the high - resolution observation of solar magnetic field in the huairou solar observing station ( hsos ) 摘要文章介绍了怀柔太阳观测基地最近完成的一套实时高分辨太阳磁场观测系统。
The perpetually declining cost and increasing availability of hardware required and a steady flow of new applications in commercial , medical field and in scientific research indicate continued growth for the digital image - processing system field and play an important role in the future <中文摘要> =不断降价和普及的硬件设备以及在商业、医学、科研等领域稳定涌现出的新的应用,使得图象处理领域一直保持持续发展的势头并将在未来发挥更为重要的作用。
Image measurement and analysis on - line and at high accuracy has been applied in many industrial filed widely . however , the general - purpose and some special - purpose image - processing system yield a lot of discommodity and insufficiency in particular applications . so the development of this task has its essential and practical significance 图象的在线和高精度的测量分析也越来越广泛的应用于工业的许多领域,而已经商业化的应用系统对特定应用场合有许多的不便和不足,因此,该课题的提出有其必要性和现实的意义。
The main contents of the thesis are shown as follows : presenting fundamental theories of statistic pattern recognition , discussing rgb ( red , green , blue ) color space , ohta color space , hsi ( hue , saturation , intensity ) color space and its converted color space , materials consistency in gray scale and the application in removing foreign bodies in tobacco flows , hence presenting recognition pattern based on " unit recognition " , designing sample machine for this purpose , which consists of material - providing system , optic system , image - grabbing system , real - time intelligent image - processing system and systems of automatically rejecting foreign bodies and self - diagnosis , analyzing and optimizing hard wares , offering concrete designs such as optic system and air - ejector driver circuit , presenting and realizing physical ram 本文的主要内容有:统计模式识别基础理论及它们在烟草异物识别中的应用;讨论了rgb ( red 、 green 、 blue )基础颜色空间、 ohta颜色空间、 hsi ( hue色调, saturation饱和度, intensity亮度)颜色空间及其变换空间、物料图像纹理、灰度均匀性等在烟草异物识别中的应用,并在此基础上提出了"基于判别单元颜色统计特性"的烟草在线异物识别模型,设计并研制了烟草在线异物实时识别与自动剔除系统原理样机,它由供料系统、光学系统、图像数据采集系统、实时智能图像处理系统、异物自动剔除系统以及自诊断系统等组成。