一 種 指 紋 分 類 之 研 究

Abstract

指紋分類為指紋系統提供了一種重要的索引機制. 一個正確的指紋分類能大大的降低尋找時間於一個大型的資料庫系統.本論文提出一種指紋分類的方法. 在我們提出的方法裡, 將指紋歸於五類, 即為Arch, left loop, right loop, whorl, and tented arch.本論文的方法的主要步驟有指紋圖像加強,方向矩陣的萃取,特徵點的萃取,分類. 最後我們共用了1900 枚姆指指紋做測試, 實驗結果得到88 % 的分類正確率.

Fingerprint classification provides an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce the fingerprint matching time for a large database. In this thesis, we present a new classification method for fingerprint images. In the proposed method, we classify fingerprints into five classes: arch, left loop, right loop, whorl, and tented arch. The major steps of this method include image enhancement, direction matrix extraction, singular points extraction and classification. Finally, we use the 1900 thumb fingerprints of NIST-4 database to evaluate the performance of the proposed method. The experimental result shows that we are able to achieve a classification accuracy of 88 percent (with 10% rejection).