人臉辨識系統，主要是以生物特徵來辨識個人身分。本論文以SOPC為基礎，使用二維離散小波轉換(2-D Discrete Wavelet Transform)，取出人臉影像的低頻係數，做為人臉影像特徵參數，以降低影像維度，增進人臉特徵與資料庫比對的速率。
Altera的SOPC (System On Programmable Chip)為一個FPGA，內含有一個軟核32-bit RISC處理器，可以輕易的加入自行定義的硬體模組與處理器結合。SOPC具有完善的硬體模組函式庫，良好撰寫C程式語言的使用者介面，具有硬體執行速度快的特性與軟體容易修改的特點，在開發上比ASIC具彈性，在消耗功率上比個人電腦低。二維離散小波轉換採用升級式機制(Lifting Base)濾波器做為人臉辨識系統的核心。升級式機制具有運算量小、容易以硬體實現的優點。用硬體描述語言撰寫升級式機制濾波器，與本系統結合，來縮短其運算時間，以達成即時辨識之目標。並以高度整合性的SOPC為實做平台，建立本系統。
本論文在SOPC FPGA平台上實做小波轉換之人臉辨識系統，最後針對一套61人的人臉資料庫中做測試，經實驗證實，本論文所開發的系統，可以得到極佳的辯識率。

The face recognition system is mainly developed for identifying personal identities based on biometrics information. Based on SOPC, our approach reduces the dimension of images by employs 2-D DWT to extract low frequency coefficients of face images as the features of face images. And therefore accelerates the speed of matching with database transactions.

Altera's FPGA based SOPC used in the thesis includes a soft-core 32-bit RISC micro-processor, user-defined hardware modules can be easily combined with the micro-processor. SOPC has advantages in several ways: 1) complete hardware module library, 2) friendly user interface for writing C code, 3) fast hardware execution speed, 4) software can be easily developed, 5) more flexible than ASIC for development and 6) lower power consumption than personal computers. The 2-D DWT employs a Lifting Base filter, which the computational complexity is low, for face recognition system. Achieving the goal of real-time recognition, we implement the lifting base filter by HDL and combine with our system for reduce the computational latency. The system is constructed on the SOPC platform, which of highly integrated system.

In the experiments, we implement 2-D DWT approach face recognition scheme into SOPC FPGA system, we use it to conduct a series of evaluation on a face database consisting of 61 persons. The result shows that recognition rate is good.

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