王勝德Wang, Sheng-De臺灣大學:電機工程學研究所詹雅婷Chan, Ya-TingYa-TingChan2010-07-012018-07-062010-07-012018-07-062009U0001-2201200901500800http://ntur.lib.ntu.edu.tw//handle/246246/188040人臉偵測在人臉辨識系統中為重要且首先必要的步驟，因此在系統上要求必須快速而準確。故近年來，已有許多有關人臉偵測的方法被提出，大部分都是基於演算法方面的改善，在硬體上的實現比較少見，故本論文引用的兩種膚色演算法實做在嵌入式開發版並加以改善來使整個系統硬體加速，並以型態學中的去雜訊法來使膚色區域更完整，並額外加上移動偵測，使系統能在個別的情況下，根據物體移動的程度來做即時性的人臉擷取Face detection is the first and a required step in a face recognition system. For real-time systems, the step should work quickly and accurately. Recently there have been numerous methods for human face detection proposed for real-time imaging systems. Among them, a class of methods is based on some color space features to detect face. However, few of them considered the implementation it for the hardware system. The thesis uses two widely used skin detection algorithms and aim to implement the algorithms in a hardware platform, which is an Altera FPGA embedded boards. The proposed face detection system makes use of noise removal methods to make the skin region more complete. In addition, the system also uses motion detection to help determine an object''s motion, which in turn is used as a condition to account for varying circumstances. The experiment results show that the proposed face detection can achieve the real-time face detection task with 60 frames per second.摘要 Ibstract II謝 III錄 IV目錄 VI目錄 VIII一章 序論 1.1 概述 1.2 研究動機 1.3 論文架構 1二章 文獻探討 2三章 影像擷取系統 3.1 系統架構 3.2 CMOS影像擷取模組介紹(CMOS Sensor Introduction) 4 3.2.1 CMOS影像擷取模組特性 5 3.2.2 CMOS影像擷取模組訊號 6.3 FPGA的Core 組成電路 6 3.3.1 CMOS影像資料截取(CMOS Sensor Data Capture ) 6 3.3.2 I2C結構( I2C Sensor Configuration) 7 3.3.3影像格式轉換(Bayer Color Pattern Data to 30-bit RGB) 9 3.3.4 多埠動態記憶體控制器(Multi-Port SDRAM Controller) 10 3.3.5 視頻圖像陣列控制器(VGA Controller) 11四章 膚色偵測及影像處理 15.1 膚色偵測演算法 15.2 NCC色彩空間膚色偵測 15 .2.1 NCC色彩膚色偵測硬體加速 17.3 YCrCb色彩空間膚色偵測 19.4 影像處理 20.4.1 膨脹(Dilation)與侵蝕(Erosion) 21 .4.2 Opening 與 Closing 23.4.3邊緣偵測(Edge detection) 24.4.4 影像處理之硬體實現方法 26五章 移動偵測及人臉擷取 31.1 移動偵測簡介 31.2 移動偵測 31.3 人臉擷取 34六章 實驗結果與數據探討 38.1 實驗說明 38.2 膚色偵測及影像處理結果 40.3 移動物體偵測方法 46.4 人臉擷取結果 47.5 數據分析與討論 49七章 結論與未來展望 52考文獻： 534209209 bytesapplication/pdfen-US人臉偵測Face detectionthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/188040/1/ntu-98-J95921048-1.pdf