田径运动员号码牌图像的号码识别

link管理

链接快照平台

输入网页链接，自动生成快照
标签化管理网页链接

相关文章推荐

高兴的山羊 · css实现网页内容180度翻转 – 不亦乐乎· 2 月前 ·

气宇轩昂的铅笔 · 中央海岸水手3-1纽卡斯尔喷气机取澳超4连胜 ...· 2 月前 ·

腼腆的打火机 · QoS | 行思錄 | Travel Coder· 2 月前 ·

逼格高的路灯 · 【读懂广东】何为梅州 - 广东省人民政府参事室网站· 3 月前 ·

没有腹肌的海豚 · 【转】【WPF】WPF ...· 3 月前 ·

摘要： 田径运动项目中通常拍摄得到大量的图像，如何快速获取特定运动员的图像成为普遍关注的问题.为了快速检索包含特定运动员的图像，本文提出了识别图像中运动员编号的方法，依据运动员编号的识别达到快速检索的目的.首先，采用DPM（DeformablePart Model）（可形变部件模型）进行人体检测，缩小搜索范围，接着按照运动员号码牌的先验知识，采用两种方式进行运动员号码牌定位，保障定位的可靠性；然后对定位出的号码牌进行字符分割；最后采用基于特征的BP（BackPropagation）神经网络的方法进行号码牌识别.实验结果表明，在运动员号码牌几乎无遮挡的情况下，使用本文提出的方法能有效地识别出完整号码牌；在运动员号码牌存在部分遮挡时，可以识别出未被遮挡部分的编号.本文提出的运动员号码牌识别方法为检索特定运动员图像提供了思路，大大减少了普遍采用的人工查找方式的工作量.

Abstract: A lot of images are usually photographed in the sports of track and field, and manual operation is a general method to retrieve image containing certain athletes. In order to quickly retrieve images containing a particular player, a method based on the number to identify a player is proposed. It firstly applied DPM (Deformable Part Model) algorithm to narrow the search scope of number plate. Secondly, according to the prior knowledge, the position of number plate can be located by considering two different ways to ensure the reliability. Thirdly, the characters of number plate are segmented by connected component analysis method. Finally, feature-based BP (Back Propagation) neural network is adopted to recognize the number plate. Experimental results show that the proposed method is efficient to identify the number plate of the players. The number plate recognition method provides a guideline of retrieving a specific player's images.

Key words: track and field sports, character segmentation, back propagation neural network, character recognition [1] EZAKI N, BULACU M, SCHOMAKER L. Text detection from natural scene images: Towards a system for visually impaired persons[C]//Proceedings of the 17th International Conference on Pattern Recognition. IEEE, 2004(2): 683-686.
[2] 杨靖. 运动员球衣号码研究[J]. 体育文化导刊, 2014, 9: 184-187.
[3] MESSELODI S, MODENA C M. Scene text recognition and tracking to identify athletes in sport videos[J]. Multimedia Tools and Applications, 2013, 63(2): 521-545.
[4] YE Q, HUANG Q, JIANG S, et al. Jersey number detection in sports video for athlete identification[C]//Proceedings of 2005 Visual Communications and Image Processing. International Society for Optics and Photonics. 2005: 1599-1606.
[5] JUNG K, KIM K I, JAIN A K. Text information extraction in images and video: a survey[J]. Pattern Recognition, 2004, 37(5): 977-997.
[6] MARIANO V Y, KASTURI R. Locating uniform-colored text in video frames[C]//Proceedings of the 15th International Conference on Pattern Recognition. IEEE, 2000(4): 539-542.
[7] SONG Y, LIU A, PANG L, et al. A novel image text extraction method based on k-means clustering[C]//Proceedings of the 7th IEEE/ACIS International Conference on Computer and Information Science. IEEE. 2008: 185-190.
[8] SHIVAKUMARA P, PHAN T Q, TAN C L. A Laplacian approach to multi-oriented text detection in video[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 412-419.
[9] KIM H K. Efficient automatic text location method and content-based indexing and structuring of video database[J]. Journal of Visual Communication and Image Representation, 1996, 7(4): 336-344.
[10] HUANG Z, LENG J. Text extraction in natural scenes using region-based method[J]. Journal of Digital Information Management, 2014, 12(4): 246-254.
[11] MAO W, CHUNG F, LAM K K M, et al. Hybrid Chinese/English text detection in images and video frames[C]//Proceedings of the 16th International Conference on Pattern Recognition. IEEE, 2002(3): 1015-1018.
[12] LEE C W, JUNG K, KIM H J. Automatic text detection and removal in video sequences[J]. Pattern Recognition Letters, 2003, 24(15): 2607-2623.
[13] CHEN X, YUILLE A L. Detecting and reading text in natural scenes[C]//Proceedings of 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2004(2): 366-373.
[14] ZHAO X, LIN K H, FU Y, et al. Text from corners: a novel approach to detect text and caption in videos[J]. IEEE Transactions on Image Processing, 2011, 20(3): 790-799.
[15] CHENG R, BAI Y. A novel approach for license plate slant correction, character segmentation and Chinese character recognition[J]. International Journal of Signal Processing Image Processing and Pattern Recognition, 2014, 7(1): 353-364.
[16] CHEN Z, CHANG F, LIU C. Chinese license plate recognition based on human vision attention mechanism[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2013, 27(8): 488-196.
[17] SULAIMAN N, JALANI S N H M, MUSTAFA M, et al. Development of automatic vehicle plate detection system[C]//Proceedings of the 3rd International Conference on System Engineering and Technology. IEEE, 2013: 130-135.
[18] 王兴玲. 最大类间方差车牌字符分割的模板匹配算法[J]. 计算机工程, 2006, 32(19): 193-195.
[19] 李文举, 梁德群, 王新年, 等. 质量退化的车牌字符分割方法[J]. 计算机辅助设计与图形学学报, 2004, 16(5): 697-700.
[20] KO M, KIM Y M. License plate surveillance system using weighted template matching[C]//Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop. IEEE, 2003: 269-274.
[21] 邓婷. 基于特征统计的车牌非汉字字符识别方法[J]. 广西师范学院学报 (自然科学版), 2009, 26(4): 88-92.
[22] FOR W, LEMAN K, ENG H L, et al. A multi-camera collaboration framework for real-time vehicle detection and license plate recognition on highways[C]//Proceedings of 2008 IEEE Intelligent Vehicles Symposium. IEEE, 2008: 192-197.
[23] ANAGNOSTOPOULOS C N E, ANAGNOSTOPOULOS I E, LOUMOS V, et al. A license plate-recognition algorithm for intelligent transportation system applications[J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(3): 377-392.
[24] 陈金辉. 静态图像行人检测算法研究 [D]. 上海: 华东理工大学, 2015.
[25] FELZENSZWALB P, MCALLESTER D, RAMANAN D. A discriminatively trained, multiscale, deformable part model[C]//Proceedings of 2008 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2008: 1-8.
[26] 朱双东, 张懿, 陆晓峰. 三角形交通标志的智能检测方法[J]. 中国图象图形学报, 2006, 11(8): 1127-1131.
[27] 王义兴, 黄凤岗, 韩金玉, 等. 基于颜色搭配与纹理特征的车牌定位方法[J]. 中国图象图形学报, 2009, 14(2): 303-308.
[28] 常巧红, 高满屯. 基于HSV色彩空间与数学形态学的车牌定位研究[J]. 图学学报, 2013, 34(4): 159-162.
[29] 向静波, 苏秀琴, 陆陶. 基于Contourlet变换和形态学的图像增强方法[J]. 光子学报, 2009, 38(l): 224-227.
[30] MILYAEV S, BARINOVA O, NOVIKOVA T, et al. Fast and accurate scene text understanding with image binarization and off-the-shelf OCR[J]. International Journal on Document Analysis and Recognition, 2015, 18(2): 169-182.
[31] 王建霞, 周万珍. 一种改进模板匹配的车牌字符识别方法[J]. 河北科技大学学报, 2010, 31(3): 236-239.