隨科技的發展，不斷的走向便利的科技生活，安全性的議題值得重視。生物辨識是近年來相當受關注的研究，利用人體上生理或是行為特徵作為身分辨識的依據。
生物辨識發展日漸成熟，從利用人臉、指紋，甚至是虹膜辨識，皆是現在風行的生物辨識，本論文是一套採用手指靜脈作為特徵的辨識系統，手指靜脈雖然面積小特徵少但依然可以達到辨識效果。本機構設計考量到手指的曲線、指尖的擺放，機構成品降低位移、旋轉等因素造成的誤判。穿透式的燈光以及亮度正規化的調整，取得的較為清楚的靜脈影像。加速穩健特徵(Speeded Up Robust Features: SURF)是近幾年影像辨識研究中具有高辨識率的特徵， 雖然可得到良好的辨識效果，但針對龐大的資料庫而言，執行的時間過長是一個值得探討的議題。本論文利用的SURF特徵的相關資訊，建立了第二層的特徵標籤代表了特徵點區塊的高頻信息，第三層的特徵索引值代表了特徵點分布的位置信息，由第三層起頭，有效且快速的過濾掉85%比對影像，再由第二層、第一層SURF更多的細節準確的辨識出正確靜脈影像。

With the development of technology, Security of information becomes an important issue. Biometrics recognition is popular in recent years, Biometrics is of considerable research interest in recent years, it use humans face、iris、voice、fingerprint recognition, and the biometrics recognition mainstream become vein recognition.
This paper is set a recognition system by using finger vein. The characteristics of finger vein are small and portability. Nowadays, the issue we have to discussion is recognize immediately with big database. Although many recognition algorithms have the high recognition rate, but they always cost too much time. Our proposed encode the new feature by using SURF information. The method can reduce the execution time, decrease the dimensions of vector and keep the feature of the vein.
We calculate two distances to matching two images. First, computing the feature of second and third level by Hamming distance, it can filter the false candidates quickly. Second, SURF feature using Euclidean distance to determine each pattern vector matching or not. Using this method can retain the original characteristics, and have efficient recognition in the big databases.

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