目前指紋辨識是以軟體的方式來達成，其成本高、系統體積大且效率較不理想；如將指紋辨識的演算法以硬體的方式實現，以增加指紋辨識的效能，且減少指紋辨識器的成本與體積及增加使用的方便與時效。在本論文中，我們提出一個處理二值化圖形細線化的硬體架構，其將指紋圖像簡化為一個曲線圖，以利特徵抽取與圖案辨識，這種簡化可以透過取得區域的骨架(細線化)來完成。細線化因其能有效的簡化資料並增強物體特徵的抽取，我們針對即時細線化而設計一處理器，其為管線式影像細線化的架構，此處理器建立在一高度平行化的細線化演算法上。此一演算法利用3 X 3型罩對物體作細線化處理。此一架構被應用於超大型積體電路設計，對處理一張CIF format 352 x 288 (數位照相機的標準格式) 的二值化指紋圖像不超過0．05秒。另外本研究將設計出一個實用的高速指紋辨識環境 ( Evaluation Board ) 以利高速指紋辨識晶片設計與製作。由於指紋辨識的演算法相當複雜，如果直接把全部指紋辨識演算法轉換成硬體晶片化有其困難，必須先製作指紋影像讀取裝置，再製作為指紋辨識晶片而設計之專用的驗證暨發展環境系統及相關的軟體驅動程式，然後再把這些裝置的軟、硬體設備，整合成可獨立操作的指紋辨識系統，如此才能完整驗證我們所設計之指紋辨識晶片的功能及效能，然後將製作的指紋影像處理晶片與利用軟體設計的方法做一比較，以便進一步評估指紋辨識硬體化的效益。

Most fingerprint verification methods are implement in software, which have high cost, larger module and less efficiency. On the other hand, utilizing hardware chip design to implement the algorithm of fingerprint verification can increase the verification efficiency, reduce the cost and module size. In this thesis, we propose a special purpose VLSI architecture for binary image skeletonization. Skeletonizing is widely used in the preprocessing stage of pattern recognition operations, to compress data and to further support feature extraction in the subsequent stage. It normally reduces a digitized pattern to a skeleton such that all resulting branches are of only 1 pixel thickness. This pipelined dataflow architecture is based on a modified parallel skeletonizing algorithm that skeletonizes a 512 x 512 image a high degree parallelism. Our algorithm is mapped onto a single chip implementation for skeletoning a CIF format binary image within about 0.05 sec.
In this thesis, we propose a very powerful evaluation system for fingerprint verification system. The complete algorithm of fingerprint verification is quite complex, and it is difficult to implement the whole algorithm into a single chip; In order to testify the functions and efficiency of the chip we designed, it is necessary to build and integrate a complete finger verification system which includes a fingerprint image reader, a evaluation system specially designed for the fingerprint verification chip, and the relative software drivers. We compared the result images of the image processing chip to software processed images, and proposed the benefits of chip design to fingerprint verification.

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