近年來，人臉辨識技術已經被廣泛的利用在各方面並且取得不錯的成果。本論文提出一個完整的系統架構，根據使用者的搜尋選項例如整張人臉、眼睛、鼻子或是嘴巴來從資料庫中取出相似的人臉影像。在第一階段當中，系統擷取出人臉特徵，接著對其光源及大小做正規化，並且取出人臉特徵點。第二階段中，利用主成分分析以及人臉特徵相對關係從資料庫中搜尋出最相似的前三張人臉影像。實驗結果顯示出使用者可以根據其搜尋選項找到相似的影像，而人臉特徵相對關係可以彌補主成分分析容易受到光源影像的缺點。 Over the last decade, face recognition techniques are widely used in various fields and have significant results. This paper proposes a system framework that retrieves the target image from the database according to the option of the users: whole face, eyes, nose or mouth. At the first stage, the system extracts the facial features, normalizes the scale and illumination of the feature images. From the feature images, we take advantage of the characteristic that facial features are conceived to be illumination invariant to filter the skin color then obtain the facial feature points. At the second stage, the system uses principle component analysis (PCA) and correlation of facial features to retrieve the target images from the face database. The result shows that users can find the similar face image according to their search option, and correlation of facial features can overcome the characteristic that PCA is sensitive to change in illumination.
