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 ) 摘要文章介紹了懷柔太陽觀測基地最近完成的一套實時高分辨太陽磁場觀測系統。
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> =不斷降價和普及的硬件設備以及在商業、醫學、科研等領域穩定涌現出的新的應用,使得圖象處理領域一直保持持續發展的勢頭并將在未來發揮更為重要的作用。
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 圖象的在線和高精度的測量分析也越來越廣泛的應用于工業的許多領域,而已經商業化的應用系統對特定應用場合有許多的不便和不足,因此,該課題的提出有其必要性和現實的意義。
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 本文的主要內容有:統計模式識別基礎理論及它們在煙草異物識別中的應用;討論了rgb ( red 、 green 、 blue )基礎顏色空間、 ohta顏色空間、 hsi ( hue色調, saturation飽和度, intensity亮度)顏色空間及其變換空間、物料圖像紋理、灰度均勻性等在煙草異物識別中的應用,并在此基礎上提出了"基于判別單元顏色統計特性"的煙草在線異物識別模型,設計并研制了煙草在線異物實時識別與自動剔除系統原理樣機,它由供料系統、光學系統、圖像數據采集系統、實時智能圖像處理系統、異物自動剔除系統以及自診斷系統等組成。