臺灣博碩士論文加值系統

夜間監控變得越來越普及，而車牌辨識和人臉辨識是夜間監控的重要功能。然而夜間影像常常會因為光源不足、過曝以及逆光等情況變得不清楚，為了解決這些問題，我們使用多重亮度紅外線打光器來補助夜視攝影提供不同亮度的影像。由於多重亮度紅外線攝影會產生不同亮度的影像導致有不同結果，所以分析這些結果並整合為一即為本論文研究之目的。實驗結果顯示，多重亮度照明確實有助於提升夜間車牌辨識及人臉辨識的辨識率。

Nighttime video surveillance has become more and more popular. License plate recognition and face recognition are two important applications in nighttime video surveillance. However, nighttime videos are unclear due to insufficient illumination at far distance, overexposure at near distance and backlight situation. To solve these problems, we adopt a new multi-intensity infrared illuminator as a supportive light source to provide multiple illumination levels. Because there are imaging results with multiple intensities, analyzing and integrating these results is the purpose of this thesis. Experiment results show that multi-intensity infrared illumination can indeed improve the performance of license plate recognition and face recognition.

摘 要 iii
Abstract iv
Contents v
List of Figures vii
List of Tables xi
Chapter 1 Introduction - 1 -
1.1 Motivation - 1 -
1.2 Related work - 3 -
1.2.1 License Plate Recognition - 3 -
1.2.2 Face Detection - 5 -
1.2.3 Face Recognition - 9 -
1.2.4 Applications of Multi-Intensity IR Illuminator - 13 -
1.3 Organization of Thesis - 15 -
Chapter 2 License Plate Detection and Recognition - 16 -
2.1 License Plate Detection - 16 -
2.2 Character Segmentation - 19 -
2.3 Character Recognition - 21 -
2.4 Multiple-Intensity Results Integration - 23 -
Chapter 3 Face Detection and Recognition - 25 -
3.1 Face Detection - 25 -
3.2 Face Tracking - 27 -
3.3 Face Sequence Recognition - 30 -
3.4 Multi-Intensity Results Integration - 32 -
Chapter 4. Experiment Results - 36 -
4.1 License Plate Detection Result on Multiple Intensities - 36 -
4.2 License Plate Recognition Result on Multiple Intensities - 40 -
4.3 Face Detection Result on Multiple Intensities - 42 -
4.4 Face Recognition Results on Multiple Intensities - 46 -
Chapter 5 Conclusions and Future Works - 49 -
5.1 Conclusions - 49 -
5.2 Future works - 49 -
References - 50 -

[1] Y.-T. Chen, J.-H. Chuang, W.-C. Teng, H.-H. Lin, and H.-T. Chen, “Robust License Plate Detection in Nighttime Scenes Using Multiple Intensity IR-Illuminator,” International Symposium on Industrial Electronics, 2012.
[2] P.-A. Yao and J.-H. Chuang, “Nighttime Face Detection Using Multi-Intensity IR Illuminator,” MS Thesis, National Chiao Tung University, 2013.
[3] C. Arth, F. Limberger and H. Bischof, “Real-Time License Plate Recognition on an Embedded DSP-Platform,” International Conference on Computer Vision and Pattern Recognition, pp. 1-8, 2007.
[4] P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” International Conference on Computer Vision and Pattern Recognition, issue 1, pp. 511-518, 2001.
[5] A. Zidouri and M. Deriche, “Recognition of Arabic License Plates using NN,” First Workshops on Image Processing Theory, Tools and Applications, pp. 1-4, 2008.
[6] A. Rabee and I. Barhumi, “License Plate Detection and Recognition in Complex Scenes Using Mathematical Morphology and Support Vector Machines,” International Conference on Systems, Signals and Image Processing, pp. 59-62, 2014.
[7] P. Viola and M. Jones, “Robust Real-Time Face Detection,” International Journal of Computer Vision, volume 57, issue 2, pp. 137-154, 2004.
[8] J. Dowdalla, I. Pavlidisa and G. Bebisb, “Face Detection in the Near-IR Spectrum,” Image and Vision Computing, volume 21, issue 7, pp. 565-578, 2003.
[9] X. Zou, J. Kittler and K. Messer, “Accurate Face Localisation for Faces under Active Near-IR Illumination,” International Conference on Automatic Face and Gesture Recognition, volume 7, pp. 369-374, 2006.
[10] H. Cevikalp and B. Triggs, “Face Recognition Based on Image Sets,” International Conference on Computer Vision and Pattern Recognition, pp. 2567-2573, 2010.
[11] Z. Cui, S. Shan, H. Zhang, S. Lao and X. Chen, “Image Sets Alignment for Video-Based Face Recognition,” International Conference on Computer Vision and Pattern Recognition, pp. 2626-2633, 2012.
[12] Z. Cui, W. Li, D. Xu, S. Shan and X. Chen, “Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild,” International Conference on Computer Vision and Pattern Recognition, pp. 3554-3561, 2013.
[13] P. Zhu, W. Zuo, L. Zhang, S. C.-K. Shiu and D. Zhang, “Image Set-Based Collaborative Representation for Face Recognition,” IEEE Transactions on Information Forensics and Security, volume 9, issue 7, pp. 1120-1132, 2014.
[14] R. Lienhart, A. Kuranov and V. Pisarevsky, “Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection,” Pattern Recognition, pp. 297-304, 2003.
[15] M. Castrillón, O. Déniz, C. Guerra and M. Hernández, “ENCARA2: Real-Time Detection of Multiple Faces at Different Resolutions in Video Streams,” Journal of Visual Communication and Image Representation, pp. 130-140, 2007.
[16] C.-H. Chan, H.-T. Chen, W.-C. Teng, C.-W. Liu and J.-H. Chuang, “MI3: Multi-Intensity Infrared Illumination Video Database,” International Conference on Visual Communications and Image Processing, pp. 1-4, 2015.
[17] Y. Bediz and G. B. Akar, “View point tracking for 3D display systems,” European Signal Processing Conference, pp. 1-4, 2005.