手指靜脈對於每個人是獨一無二的特徵，所以手指靜脈的驗證就安全性和便利性而言，在當下是主要的一項生物辨識技術。在紅外線光的照射下，利用攝影機抓取手指的圖像，其中除了包含指靜脈圖像外，在陰暗處也存在著手指的肌肉、骨頭和組織。在這篇論文中，介紹了初步的程序來提升因攝影機產生雜訊而被降低的圖像品質，並且使用適當的門檻值除去背景不相關的資訊，來得到清晰的指靜脈圖像。最後，使用改進過的樣板匹配方法來做指靜脈辨識。實驗結果顯示出即使圖像品質並不夠好，但只要指靜脈圖像是清晰的，利用一些適當的方法來處理，便可以運用在人員識別方面。因此，它依然可達到100%的識別正確率。

Finger vein authentication can be a leading biometric technology nowadays in terms of security and convenience, since it introduces the features inside the human body. An image of a finger captured by the camera under the IR light transmission contains not only the vein pattern itself, but also shade produced by various thickness of the finger muscles, bones, and tissue networks surrounding the vein. In this paper, we introduce preliminary process to enhance the image quality worsened by light effect and noises produced by the camera and then segment the vein pattern by using adaptive threshold method. Finally, matched them using improved template matching. The experimental result shows that even the image quality is not good enough, but as long as our veins are clear, processed by using the methods in this paper, it still can be used as the means of personal identification. Hence it still can achieve up to 100% identification accuracy when we take our 1000 images in our database in to the matching scheme.

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