近年來，隨著經濟與科技的蓬勃發展，生物辨識技術開始大量的運用在許多的設備上，其中在手持設備中，最受歡迎的技術為指紋辨識技術，因此辨識率是生物辨識技術的重要因素。
本研究提出了一個新穎的兩階段式指紋辨識系統。首先，在第一階段之特徵點比對演算法中，本論文提出強健二進制不變特徵(Robust Binary Invariant Feature, RBIF)，利用自適應閥值的方式擷取適當數量的角點特徵資訊，並採用梯度方向校正讓特徵點具有抗旋轉能力，接著利用二元強健獨立基礎特徵對強健特徵點進行特徵描述。第二階段利用多重影像品質相似度評估(Multiple Image Quality Metrics, MIQM)對特徵匹配後的結果加以進行相似度的驗證，而用於評估的感興趣區域是直接採用匹配特徵點的區域做擷取，藉此降低運算複雜度。
實驗結果的部分，本論文利用公用資料庫(FVC 2000及 FVC2002)與實驗室的資料庫來個別進行測試，並與前人的方法比較。從結果可以看出，提出的兩階段式指紋辨識系統不論在辨識率或是處理速率都可得到較優的結果。

With latest technological advents, biometrics recognition is becoming ubiquitous to identify individuals based on pshyiological and behavioral charactersitics. Specifically, in handheld devices, the fingerprint recognition is prevalently adopted and thus identification rate plays a critical role for commercial deployments. This paper proposes a novel fingerprint recognition system, which is involved with a two-stage identification strategy. To begin with, the paper proposes a Robust Binary Invariant Feature (RBIF) utilising adaptive threshold strategy which extracts features from the accelerated segment test. To obtain the rotation-invariant feature points, the gradient orientation is calculated and utilized to unify angles of features. Subsequently, Multiple Image Quality Metrics (MIQM) are used to ensure the veracity after the feature matching. The Region of Interest (ROI) is immediately identified using the area of matching feature points, which contributes to computational complexity reduction. Experimental results confirms that the proposed fingerprint recognition system achieves a tip-top recognition rate than that of the former competitive schemes on public fingerprint datasets (FVC 2000, FVC2002) and the dataset we collected.

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