[1] Lu Xiaobo, Zeng Weili,. Super-resolution reconstructionfor license plate images of moving vehicles [J]. Journal of Southeast University (English Edition), 2010, 26 (3): 457-460. [doi:10.3969/j.issn.1003-7985.2010.03.017]

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Super-resolution reconstructionfor license plate images of moving vehicles()

运动车辆车牌图像的超分辨率重建

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

26

Issue:

2010 3

Page:

457-460

Research Field:

Computer Science and Engineering

Publishing date:

2010-09-30

Info

Title:

Super-resolution reconstructionfor license plate images of moving vehicles

运动车辆车牌图像的超分辨率重建

Author(s):

Lu Xiaobo¹;  Zeng Weili²

¹ School of Automation, Southeast University, Nanjing 210096, China
² School of Transportation, Southeast University, Nanjing 210096, China

路小波¹;  曾维理²

¹东南大学自动化学院, 南京 210096; ²东南大学交通学院, 南京 210096

Keywords:

super-resolution;  residual gradient term;  residual data term;  license plate;  regularization

超分辨率;  梯度残差项;  数据残差项;  车牌;  正则性

PACS:

TP391.41

DOI:

10.3969/j.issn.1003-7985.2010.03.017

Abstract:

A novel reconstruction method to improve the recognition of license plate texts of moving vehicles in real traffic videos is proposed, which fuses complimentary information among low resolution(LR)images to yield a high resolution(HR)image. Based on the regularization super-resolution(SR)reconstruction schemes, this paper first introduces a residual gradient(RG)term as a new regularization term to improve the quality of the reconstructed image. Moreover, L₁ norm is used to measure the residual data(RD)term and the RG term in order to improve the robustness of the proposed method. Finally, the steepest descent method is exploited to solve the energy functional. Simulated and real acquired video sequence experiments show the effectiveness and practicability of the proposed method and demonstrate its superiority over the bi-cubic interpolation and discontinuity adaptive Markov random field(DAMRF)SR method in both signal to noise ratios(SNR)and visual effects.

为了改善实际交通环境中运动车辆车牌图像的质量, 提出一种新的超分辨率重建方法, 即通过融合低分辨率图像间的互补信息得到一幅高分辨率车牌图像.首先, 在超分辨率重建正则化框架下引入梯度残差项作为一个梯度强制项来改善重建图像的质量.其次, 为了提高重建算法的鲁棒性, 用L₁范数度量数据残差项和梯度残差项.最后, 用最速下降法求解相应的最小能量泛函.模拟和实际视频图像序列的实验结果验证了所提方法的有效性和实用性, 所提方法在重建图像的信噪比指标和视觉效果方面均优于双三次插值和DAMRF法.

References:

[1] Anagnostopoulos C N E, Anagnostopoulos I E, Psoroulas I D, et al. License plate recognition from still images and video sequences: a survey [J]. IEEE Transactions on Intelligent Transportation Systems, 2008, 9(3): 377-391.
[2] Takeda H, Milanfar P, Protter M, et al. Super-resolution without explicit subpixel motion estimation [J]. IEEE Transactions on Image Processing, 2009, 18(9): 1958-1975.
[3] Baker S, Kanade T. Limits on super-resolution and how to break them [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(9): 1167-1183.
[4] Farsiu S, Robinson D, Elad M, et al. Fast and robust multi-frame super-resolution [J]. IEEE Transactions on Image Processing, 2004, 3(10): 1327-1344.
[5] Farsiu S, Robinson D, Elad M, et al. Advances and challenges in super-resolution [J]. International Journal of Imaging Systems and Technology, 2004, 14(2): 47-57.
[6] Park S C, Park M K, Kang M G.. Super-resolution image reconstruction: a technical review[J]. IEEE Signal Processing Magazine, 2003, 1(5): 21-36.
[7] Huang T S, Tsai R Y. Multi-frame image restoration and registration [J]. Advances in Computer Vision and Image Processing, 1984, 1(2): 317-339.
[8] Chaudhuri S, Taur D R. High-resolution slow-motion sequencing—how to generate a slow-motion sequence from a bit stream [J]. IEEE Signal Processing Magazine, 2005, 22(2):16-24.
[9] Matan P, Elad M. Super resolution with probabilistic motion estimation [J]. IEEE Transactions on Image Processing, 2009, 18(8): 1899-1904.
[10] Suresh K V, Kumar G M, Rajagopalan H N. Super-resolution of license plates in real traffic videos [J]. IEEE Transactions on Intelligent Transportation Systems, 2007, 8(2): 321-331.

Memo

Memo:

Biography: Lu Xiaobo(1965—), male, doctor, professor, xblu@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.60972001), the National Key Technology R& D Program of China during the 11th Five-Year Plan Period(No.2009BAG13A06).
Citation: Lu Xiaobo, Zeng Weili.Super-resolution reconstruction for license plate images of moving vehicles[J].Journal of Southeast University(English Edition), 2010, 26(3):457-460.

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