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研究生:江丞哲
研究生(外文):JIANG, CHENG-ZHE
論文名稱:適用於iOS裝置之交通限速號誌偵測與辨識系統
論文名稱(外文):A Traffic Speed Limit Signs Detection and Recognition System for iOS Devices
指導教授:陳慶永陳慶永引用關係
指導教授(外文):CHEN, CHING-YUNG
口試委員:李素玲曾建誠黃世勳陳慶永
口試委員(外文):LEE, SU-LINGTSENG, CHIEN-CHENGHUANG, SHIH-SHINHCHEN, CHING-YUNG
口試日期:2017-07-07
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:電腦與通訊工程系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:66
中文關鍵詞:交通號誌限速號誌
相關次數:
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  • 下載下載:6
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近年來,智慧型行動裝置 (如智慧型手機或是平板電腦) 在日常生活中已逐
漸普及。行動裝置內建的各種感測器使得開發能感知環境並且 (協助使用者) 採
取適當動作這樣的應用程式 (Apps) 變得可能且直接。尤其,有越來越多運行在
行動裝置上的 Apps 具備了多媒體處理能力和人工智慧 (例如:某些 Apps 被開
發用於在相片中或現實世界中偵測與辨識感興趣的目標物)。
將目標設定為透過 App 達成有智慧地提醒駕駛員該路段的限速,本篇論文
提出了一個基於影像處理之交通限速號誌偵測與辨識系統。該系統主要包含兩個
模組:限速號誌的偵測與限速號誌的辨識。第一個模組用於在具有複雜背景的影
像中偵測限速號誌以標示為感興趣區域,當中採用了一連串的影像處理技術包含
色彩空間轉換、顏色切割以及形狀偵測。對於偵測階段使用顏色和形狀作為特徵
的偵測結果會比單獨使用顏色特徵或是形狀特徵的偵測結果較佳。第二個模組則
將偵測到的感興趣區域做進一步的數字切割與數字分類處理以辨識限速資訊。
本論文設計了實驗證明所提出的系統可得到不錯的結果。此外,所提的系統
也以 iOS App 的方式實現於行動裝置上,透過行動裝置內建的後置鏡頭持續地
擷取車前景像作為所提系統的輸入。辨識得到的限速資訊則以 App 的 UI 介面呈
現在畫面中並輔以語音提示駕駛員。
Mobile devices, such as smart phones and tablet PCs, have recently become
popular in our daily life. Various kinds of sensors embedded in the mobile devices make
it possible and straightforward to develop Apps that can perceive the environment and
(help users) take actions appropriately. Specifically, more and more Apps that run on
mobile devices equip with abilities of multimedia processing and artificial intelligence
(e.g., some Apps are developed for detecting and/or recognizing targets of interest either
in a photo or in the real world).
Aiming on intelligently reminding drivers the speed limits of the road via an App,
this paper proposes a traffic speed limit signs detection and recognition system based
on image processing. The system consists of two main modules: traffic speed limit signs
detection and recognition. The first module, to detect the traffic speed limit signs as
regions of interest (ROIs) in an image with complex background, cascades several
image processing techniques such as color space conversion, color segmentation and
shape detection. It has been shown that both color space and shape features are adopted
can achieve better detection result than that with only color space or shape feature. In
the second module, the detected ROIs are further processed with character
segmentation and classification techniques to recognize the speed limit information. Some experimental results have been obtained to support the efficacy of the proposed
system. Moreover, the proposed system has also been implemented as an iOS App
which takes images continuously from the embedded rear camera as inputs to the
proposed system. In the App implementation, the recognized speed limit information is
presented through both UI and voice messages to remind the drivers.

摘要 ...........................................................................................................................................................I
Abstract ................................................................................................................................................... II
誌謝 ........................................................................................................................................................ IV
目錄 ......................................................................................................................................................... V
表目錄 ................................................................................................................................................. VIII
圖目錄 .................................................................................................................................................... IX
第一章 緒論 ............................................................................................................................................ 1
1.1 前言 ............................................................................................................................................... 1
1.2 研究動機與目的 ........................................................................................................................... 1
1.3 相關研究 ....................................................................................................................................... 2
1.4 困難與挑戰 ................................................................................................................................... 3
1.4.1 號誌影像品質........................................................................................................................ 4
1.4.2 環境因素 ............................................................................................................................... 4
1.5 論文架構 ....................................................................................................................................... 5
第二章 問題描述與系統架構 ................................................................................................................ 6
2.1 交通號誌分類 ............................................................................................................................... 6
2.2 問題描述 ....................................................................................................................................... 9
2.2.1 號誌相似特徵問題 ................................................................................................................ 9
2.2.2 複雜背景問題...................................................................................................................... 11
2.3 系統架構 ..................................................................................................................................... 13
2.3.1 系統架構 ............................................................................................................................. 13

2.3.2 iPhone 6 智慧型行動裝置 ................................................................................................... 15
第三章 交通限速號誌偵測與辨識 ...................................................................................................... 17
3.1 號誌偵測階段 ............................................................................................................................. 17
3.1.1 基於 HSV 色彩空間之 ROI 偵測 ...................................................................................... 18
3.1.2 基於 YCbCr 色彩空間之 ROI 偵測 .................................................................................. 21
3.1.3 ROI 交集修正 ...................................................................................................................... 23
3.1.4 尺寸大小濾波 ..................................................................................................................... 24
3.1.5 霍夫圓形轉換 ..................................................................................................................... 25
3.2 號誌辨識階段 ............................................................................................................................. 28
3.2.1 號誌二值化......................................................................................................................... 29
3.2.2 數字分割方法 ..................................................................................................................... 32
3.2.3 數字正規化與特徵 ............................................................................................................. 33
3.2.4 支持向量機 (Support Vector Machine, SVM) ................................................................... 33
第四章 實驗結果與 APP 實作 ............................................................................................................. 40
4.1 實驗環境 ..................................................................................................................................... 40
4.2 限速號誌資料庫 ......................................................................................................................... 40
4.2.1 資料蒐集 ............................................................................................................................ 41
4.2.2 GTSRB (German Traffic Sign Recognition Benchmark) .................................................... 44
4.2.3 整合資料庫......................................................................................................................... 45
4.3 實驗設計與結果 ......................................................................................................................... 46
4.3.1 偵測階段實驗結果 ............................................................................................................. 46
4.3.2 辨識階段實驗結果 ............................................................................................................. 48
4.3.3 號誌辨識比較 ..................................................................................................................... 56
4.4 APP 實作結果 ............................................................................................................................. 57

4.4.1 操作簡介與流程 ................................................................................................................. 57
4.4.2 APP 操作流程圖 ................................................................................................................. 58
4.4.3 APP 頁面截圖 ..................................................................................................................... 59
4.4.4 APP 限速號誌偵測與辨識之執行時間 .............................................................................. 61
第五章 結論 .......................................................................................................................................... 63
參考文獻 ................................................................................................................................................ 65


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mutually occluding traffic signs," International Conference on Control Automation and
Information Sciences (ICCAIS), Ho Chi Minh City, Vietnam ,Nov. 2012, pp. 120-125.
[2] A. Hechri, A. Mtibaa, "Automatic detection and recognition of road sign for driver assistance
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[5] Y. Gu, T. Yendo, M. Tehrani, T. Fujii, M. Tanimoto, "Traffic sign detection in dual-focal active
camera system," IEEE Intelligent Vehicles Symposium, Baden-Baden, Germany, Jun. 2011, pp.
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[6] Z. Malik, I. Siddiqi, "Detection and recognition of traffic signs from road scene images," Frontiers
of Information Technology (FIT), Islamabad, Pakistan, Dec. 2014, pp. 330-335.
[7] T. B. Minh, O. Ghita, P. F. Whelan, T. Hoang, V . Q. Truong, "A robust algorithm for detection and
classification of traffic signs in video data," International Conference on Control Automation and
Information Sciences (ICCAIS), Ho Chi Minh City, Vietnam, Nov. 2012, pp. 108 - 113.
[8] R. Takada, J. Katto, " Traffic sign recognition by distorted template matching," IEEE Global Conference on Consumer Electronics (GCCE), Tokyo, Japan, Oct. 2014, pp. 416 - 418.
[9] J. Torresen, J. W. B. and L. Sekanina. "Efficient recognition of speed limit signs," International
IEEE Conference on Intelligent Transportation Systems, Washington, WA, USA, Oct. 2004, pp.
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[10] A. Bargeton, F. Moutarde, F. Nashashibi, and B. Bradai.” Improving pan-European speed-limit
signs recognition with a new “global number segmentation” before digit recognition,”
International IEEE Conference on Intelligent Vehicles Symposium, Eindhoven, Netherlands, Jun.
2008, pp. 349-354 .
[11] HSV 色彩模型:https://zh.wikipedia.org/wiki/HSL 和 HSV 色彩空間
[12] P. V. C. Hough, A. Arbor, Mich .” Method and means for recognizing complex patterns,” United
States Atomic Energy Commission, Dec. 1962.
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COLT’ 92 Proceedings of the fifth annual workshop on Computational learning theory, 1992, pp.
144-152.
[14] GTSRB(German Traffic Sign Recognition Benchmark): http://benchmark.ini.rub.de/

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