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研究生： 周立笙
Li-sheng Chou
論文名稱： 整合即時手勢辨識的智慧型觸控控制器
Smart Touch Controller with Real-Time Gesture Recognition
指導教授： 陳慶瀚
Ching-Han Chen
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系在職專班
Executive Master of Computer Science & Information Engineering
畢業學年度： 99
語文別： 中文
論文頁數： 120
中文關鍵詞： 電阻式 、觸控面板 、控制器 、智慧型 、手勢 、觸控手勢 、觸控控制器 、觸控
外文關鍵詞： touch gesture, gesture, touch, smart, controller, resistive, touch panel, touch controller
相關次數： 點閱：11  下載：0 
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    • 在人機互動系統中，觸控手勢操作已成為新一代產品的必備功能。目前觸控手勢辨識主要透過後端中介軟體運算實現，這無疑加重系統工作負擔，非常不適合要求即時且資源有限的嵌入式系統使用。本研究提出一個即時手勢辨識演算法，首先對手勢操作的連續座標進行正規化處理，接著透過機率神經網路(Probability Neural Network, PNN)進行手勢辨識與分類，並將粒子群體最佳化(Particle Swarm Optimization, PSO)演算法應用於機率神經網路的平滑參數σ最佳化，改善手勢辨識率。我們以MIAT方法論將即時手勢辨識演算法全硬體化為一個智慧型觸控控制器，於FPGA平台進行硬體驗證。使用管線化(Pipeline)平行架構重新設計硬體電路以提高系統效能，並加入使用者自訂手勢功能及運用錨點概念來模擬實現多點觸控手勢功能。實驗結果顯示，此智慧型觸控控制器具有高效能、低功耗及高辨識率的特性，大幅簡化觸控應用系統設計，可適用於更小更省電的可攜式電子產品。

    In human-computer interaction systems, touch gestures have become the must-have feature of the new generation products. At present, touch gesture recognition is mainly implemented through the middleware of back-end system, which undoubtedly increase the system workload and is not suitable for real-time requirements and limited resources of embedded systems. This paper proposes a real-time gesture recognition algorithm. We first normalize the continuous coordinates of gestures, and then use Probability Neural Network (PNN) for gesture recognition and classification, and Particle Swarm Optimization (PSO) algorithm for PNN, which optimize the smoothing parameter σ, to improve the rate of gesture recognition. The algorithm is then synthesized into a smart touch controller by the MIAT hardware synthesis methodology and verified on a FPGA platform. We redesign the hardware circuit by using pipelined parallel architecture to improve system performance, add user-defined gestures and anchor point to simulate the multi-touch gestures. From the experiments, the smart touch controller has high performance, low power consumption and high recognition rate, and significantly simplifies the design of touch application system, which is applicable for smaller and more power saving portable electronic products.

    摘要 i Abstract ii 目錄 iii 圖目錄 vi 表目錄 ix 第一章 緒論 1 1.1 研究動機 1 1.2 研究內容與系統架構 2 1.3 論文架構 4 第二章 觸控原理與架構 6 2.1 觸控面板技術 7 2.1.1 電阻式觸控面板技術 7 2.1.2 表面電容式觸控面板技術 8 2.1.3 波動式觸控面板技術 9 2.1.4 投射電容式多點觸控技術 12 2.1.5 感測器陣列式多點觸控技術 13 2.1.6 電腦視覺式多點觸控技術 14 2.1.7 單點式觸控面板改良 17 2.2 觸控A/D轉換器 18 2.3 觸控軟體 19 2.4 觸控手勢 21 第三章 觸控手勢辨識演算法 26 3.1 觸控手勢訊號前處理 26 3.1.1異常座標點濾除 28 3.1.2座標尺度調整 29 3.1.3座標點插補 30 3.2 機率神經網路分類器 33 3.2.1貝式分類器(Bayes classifier)原理 34 3.2.2 Parzen視窗法 35 3.2.3 PNN分類器設計 37 3.3 PSO應用於PNN分類器最佳化 39 3.4手勢辨識演算法驗證實驗 43 3.4.1實驗環境 43 3.4.2建立觸控手勢驗證資料庫 45 3.4.3手勢辨識演算法 45 3.4.4實驗分析 51 第四章 智慧型觸控控制器設計 58 4.1 系統設計與高階合成方法論 58 4.1.1 IDEF0 59 4.1.2 GRAFCET 60 4.1.3合成規則 63 4.2 系統架構設計 66 4.3 UART通訊模組 68 4.4 觸控訊號前處理模組 72 4.4.1異常座標點濾除模組 72 4.4.2座標尺度調整模組 75 4.4.3座標點插補模組 78 4.5 機率神經網路分類器模組 81 4.5.1機率密度函數模組 81 4.5.2決策分類模組 84 4.6 管線化(Pipeline)系統架構設計 86 4.7自訂手勢與運用錨點之高階手勢 88 4.7.1 自訂手勢 89 4.7.2 運用錨點之高階手勢 91 第五章 系統整合驗證與實驗 95 5.1 實驗設備與開發環境 95 5.2智慧型觸控控制器實作與驗證 98 5.2.1 基本手勢辨識實驗 100 5.2.2高階手勢實驗 101 5.2.3整合應用實驗 103 5.3 系統效能分析 106 第六章 結論與未來研究方向 109 6.1 結論 109 6.2 未來研究方向 110 參考文獻 112 附錄 115

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