生物辨識(Biometrics)在當社會扮演著越來越重要的角色。從提款機、門禁系統、筆記型電腦、以至於隨身碟，都可以見到生物辨識技術的應用。在生物辨識領域中，掌靜脈辨識技術是一個新興的研究重點。掌靜脈有著較指紋或掌紋更豐富的資訊，能得到良好的辨識率，其辨識率相若於使用虹膜技術的系統。加上其無法被仿造的優勢，漸漸成為科學家們矚目的焦點。由其成長幅度來看，可以期待掌靜脈辨識技術將取得與其他生物辨識技術分庭抗禮的市場份額。可惜的是，目前在國內，與掌靜脈相關的研究十分稀少。
本論文著眼於手掌靜脈紋理的辨識，利用尺度不變性特徵轉換（Scale Invariant Feature Transform，SIFT）將擷取的影像轉換為特徵點，再以這些特徵點計算相似度。尺度不變性特徵轉換得到的特徵點對於尺度改變與旋轉具有相當的抵抗力，也能抵抗部份的影像照度改變與雜點干擾。本系統的實驗結果顯示手掌紋理辨識相當理想，非常具有發展的潛力。

Biometrics is playing a more and more important role in modern society. From flash drives, notebooks, entrance guard systems to automatic teller machines, biometrics can be seen built-in applications within them.
Palm vein recognition is arguably a burgeoning research emphasis on biometrics. Palm vein image contains rich information for identifying and authenticating, and it provides nice and accurate recognition rate. With the vantage that it can not be fabricated, it is becoming a new star of biometrics. A highly-growing market share can be expected. However, in our country, it is a pity that researches about palm vein recognition are rare.
In our research, we focused on building a palm texture recognition system by using scale invariant feature transform. Scale invariant feature transform(SIFT) transforms captured palm vein images into distinctive feature points, and they can be compared and used for identifying people. The experimental result shows that it is ideal for being a biometrics system, and its future is promising.

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