近年來由於犯罪率的攀升，使得治安方面的需求更加強烈，也因此世界各國皆把智慧型監控技術列為重要的研究課題。然而另一個問題也隨即產生，由於智慧型監控系統需與電腦結合，但是由於個人電腦(PC-Base)具有體積龐大、佔空間與高消耗功率等問題，而且要求高速處理時需要高價位的電腦組裝費用，因此若以個人電腦為系統的核心，則整個系統會變得大而無當。本研究主要發展一套智慧型監控系統，以ARM-Base嵌入式系統平台取代傳統個人電腦。使用嵌入式系統平台的主要優點如：成本低、體積小、省電…等優點，然而使用嵌入式系統平台發展即時智慧型監控系統必須克服處理器速度、記憶體空間不足…等問題，本研究嘗試以嵌入式平台結合前景分離演算法發展一套即時強健智慧型監控系統。
近幾年，前景分離演算法近來被大量討論與研究，如影像差異法、時間軸平均值法、時間軸中間值法、邊緣模型法…等，要如何精確快速分離前後背景是本研究的重點。在實作方面，採用Intel Xcale270處理器為前端處理中心，嵌入WinCE作業系統架起CCD 模組，結合前景分離演算法，做為日後智慧型監控系統在嵌入式平台發展的基礎。

The rise in crime rate recently makes the requirements of public security more strong, and therefore all the countries in the world take the Intelligent Video Surveillance and Monitoring (IVSM) technique into an important research topic. However, the IVSM system in combination with Personal Computer (PC) causes a problem, which is impractical, because PC is large and occupies a lot of space, and it consumes much power. In addition, more faster computational more expensive. Hence, it is inappropriate to use the PC as the core in IVSM system. This thesis uses ARM-based embedded system as the platform instead of traditional PC to develop an IVSM system. Embedded system platform has many advantages such as low-cost, small, low power consumption, etc. However, we still have to overcome the lower processor speed and inadequate memory space problem while deploying and IVSM system in embedded environment.
A lot of research has sufficiently discussed the foreground detection in recently years, such as temporal difference, temporal averaging, temporal median, and edge model, etc. We focus on how to detect the foreground precisely and quickly in this thesis. For implementation, we embed Intel Xcale270 processor in WinCE to set up a CCD (charge coupled device) module and subsequently combine with foreground detection as the foundation of developing IVSM system in embedded platform.

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