本研究利用多元模型下的影像偵測與分析方式，偵測使用者的膚色並進一步判斷使用者膚色的色澤狀況，完成利用影像偵測系統達到判斷使用者的身體狀況與後續追蹤的目的。研究方法主要是建構多模態膚色機率模型進行機率相似度比對，藉此找到影像中膚色資訊並進行膚色特徵擷取。這個方法可以大幅提升系統擷取膚色區域的準確度。接著設計一套利用膚色像素值分佈判斷色澤狀況的公式，系統可以結合人臉偵測與辨識，追蹤同一使用者膚色的色澤狀況，並發出關切的問候訊息，即時與使用者進行人性化的互動，達到健康管理的應用。在191組測試影像中，實驗結果顯示系統在膚色區域偵測可以達到91.95%的準確度，而色澤狀況判定也可以達到84.8%的準確度，未來將可實際應用到電腦相關設備中。

In this paper, the multi-model probabilities for skin color detection are proposed to find the regions of skin color in images with human faces. It can deal with skin colors of different races. The captured skin-color information is further applied to determine the health condition of users by comparing with the pre-stored database. The system will be very useful in the integrated surveillance systems, which combined with face detection and face recognition techniques to track any registered user. In the experiments, the testing image database includes 191 image pairs. The results showed that the accuracy of skin color detection is 91.95% and the accuracy of the health condition is 84.8%. Both of them are approaching the status of real applications.