隨著電腦以及網路的快速發展,數位影像輸入設備逐漸在大眾生活中普及,數位影像的取得成本也大幅降低,因此使用人臉部特徵的各種應用 - 如身份認證、臉部表情捕捉系統等,都逐漸進入成熟期,在此臉部偵測扮演著一個很重要的角色,適當的人臉偵測演算法可以減低系統比對時間並增加驗證的準確性,進而得整體應用程式的效能獲得提昇。
本篇論文提出一個在彩色影像中將人臉特徵區域取出的方法,首先透過高斯模糊的前處理以及對色彩臨界值的比對,我們很容易將影像中符合皮膚色彩的區域劃分出來,再經由型態學的運算,排除掉不符合臉部大小、比例的部分；上述的兩個步驟可大幅降低影像中所需檢驗的面積,提高系統效率。得到可能的候選區域之後進行臉部驗證工作,首先依比例將候選區域切分為左眼、右眼及嘴巴三大區域,再經由適當的計算推演出各區域的特徵,考慮其色彩特性及相對的關係,符合先前所設定的條件者即為所要求之臉部圖像。

Due to the rapid growth of technologies for network and multimedia, digital input devices have become more and more popular, and the cost of the digital image is much lower now. Various applications which using facial features like personal identify and facial expression capture are coming to the mature period. However, face detection plays an important role in these issues. A good face detection algorithm could slash the computational time in verifying probable face candidates, and improve the comparing efficiency.
In this paper, we propose a face detection algorithm. In our method, after smoothed the picture to reduce thin color region effects, we can decide which regions are in the skin-tone scope by the color threshold, Morphology operations help us to exclude the parts which not fit in the right size and proportion. Then we divide the probable face candidate into three parts, and try to find the major objects in each divided area. Consider their color characteristic and position relations; we can get the correct face region.

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