本研究成功開發出可於室內環境中使用之雲端健檢系統，將尿液檢測試劑放置於本研究所開發之比色板，使用自主開發之應用程式拍攝影像，並將該影像上傳至伺服器端進行雲端運算，於資料庫中記錄檢測結果，並將檢測結果傳送至手機應用程式，供使用者立即獲取尿液檢測試劑檢測結果。
本研究開發之雲端健檢系統，其應用程式建立於Android作業系統與iOS作業系統上，所使用之網頁伺服器為XAMPP，以PHP程式語言達成資料傳輸與管理之功能。影像處理程式則是以Python程式語言整合OpenCV開源程式庫撰寫，並使用到座標定位、映射轉換、色彩校正、HSV色彩空間中之顏色比對等概念。
為了確認色彩校正技術是否能消除不同相機間的色彩誤差，使尿液檢測試劑於不同光強度環境下亦能正確地進行顏色比對。本研究建立了一個能夠模擬特定光強度的封閉環境系統與一個直接放置於室內的開放系統進行檢測，實驗結果顯示本系統能消除相機裝置間的顏色誤差，並在室內的環境中能正常運作。

This research successfully developed a home health check system that can be used in an open indoor environment. The urine test strip is placed on the colorimetric plate developed by this research, and the image is taken using a smartphone application, and the image is uploaded to the server for cloud computing.
The application of the home health check system developed in this study is built on Android and iOS operating systems. Using XAMPP as a web server, and PHP programming language to achieve the function of data transfer and management. The image processing program is written in Python with the OpenCV open source library, and uses concepts such as coordinate positioning, perspective transformation, color calibration, and color comparing in HSV color space.
In order to confirm whether the color calibration technique can eliminate color errors between different cameras and enable correct color matching of urine detection strips in different light intensity environments. In this study, a closed environment system that can simulate a specific light intensity and an open system placed directly in the room were established for testing. The experimental results show that this system can eliminate the color error between camera devices and work properly.

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