期刊文献+

基于自适应LBP的视频文本检测算法 被引量:1

Video Text Detection Algorithm Based on Adaptive LBP
下载PDF
导出
摘要 针对LBP算法自适应性弱及复杂度高的问题,提出一种基于自适应LBP算子的视频文本检测算法。该算法利用全局及局部的像素灰度均差决定自适应阈值大小,能最大限度去除复杂背景,自适应性较强。给出基于近似圆的掩模算法来覆盖多方向种子生长区,降低其复杂度。实验结果表明,该算法在复杂背景下能取得较高的检测率,具有良好的自适应性和实用性,复杂度较低。 Due to the problem of high complexity and lack of adaptability,an algorithm based on adaptive LBP for video text detection is put forward.The algorithm uses the divided difference of global and local pixel grey to determine the size of adaptive threshold.However,it,having strong adaptability,can maximize the removal of background.At the same time,to reduce the complexity,approximate round masking which simplifies the algorithm by covering multi-direction judgments is presented.Experimental results show that the proposed algorithm can detect characters accurately even in video with complex background,and it is of strong adaptability and good practicality,also has low complexity.
出处 《计算机工程》 CAS CSCD 北大核心 2011年第18期174-176,共3页 Computer Engineering
基金 青年教师科技创新扶持基金资助项目"压缩域视频流的文本信息快速识别"(531107040060)
关键词 字符检测 LBP算子 自适应阈值 种子像素 几何特性 character detection LBP operator adaptive threshold seed pixel geometrical properties
  • 相关文献

参考文献8

  • 1Phan T Q, Shivakumara P, Tan C L. A Laplacian Method for Video Text Detection[C]//Proc. of IEEE ICDAR’09. [S. l.]: IEEE Press, 2009: 66-70.
  • 2袁海东,马华东,黄晓冬.基于梯度与粗糙度的视频文本检测与定位[J].电子学报,2008,36(8):1660-1664. 被引量:9
  • 3Jun Ye, Huang Linlin, Hao Xiaoli. Neural Network Based Text Detection in Videos Using Local Binary Patterns[C]//Proc. of CJKPR’09. Nanjing, China: [s. n.], 2009: 916-920.
  • 4沈任道,黎绍发,江焯林.快速和准确的单色视频文本提取方法[J].计算机工程,2009,35(9):214-216. 被引量:1
  • 5Wong E K, Chen Minya. A New Robust Algorithm for Video Text Extraction[J]. Pattern Recognition, 2003, 36(6): 1397- 1406.
  • 6Ye Qixiang, Huang Qingming, Gao Wen, et al. Fast and Gobust Text Detection in Images and Video Frames[J]. Image and Vision Computing, 2005, 23(6): 565-576.
  • 7Lee C W, Jung K, Kim H J. Automatic Text Detection and Removal in Video Sequences[J]. Pattern Recognition Letters, 2003, 24(15): 2607-2623.
  • 8Ojala T, Pietikainen M, Harwood D. A Comparative Study of Texture Measures with Classification Based on Feature Distributions[J]. Pattern Recognition, 1996, 29(1): 51-59.

二级参考文献30

  • 1何家颖,黎绍发.一种基于形态运算的快速文字分割算法[J].计算机工程与科学,2005,27(9):64-65. 被引量:2
  • 2高丽,杨树元,夏杰,王诗俊,梁军利,李海强.基于标记的Watershed图像分割新算法[J].电子学报,2006,34(11):2018-2023. 被引量:34
  • 3Cai Min,Song Jiqiang,Lyu M R.A New Appronch for Video Text Demction[C]//Proc.of International Conference on Image Processing.Rochester,New York,USA:[s.n],2002:117-120.
  • 4Lienhart R,Wemicke A.Localizing and Segmenting Text in Images and Videos[J].IEEE Transactions on Circuits and Systems for Video Technology,2002,12(4):256-268.
  • 5Gllavata J.Ewerth R,Freisleben B.A Robust Algoathm for Text Detection in Images[C]//Proc.of lnmmational Symposium on Image and signal Processing and Analysis.Rome,Italy:[s.n.].2003:611-616.
  • 6Liu Chunmei,Wang Chunheng.Dai Ruwei.Text Detection in finales Based on Unsupervised Classification of Edge-based Features[C]//Proc.of International Conference on Document Analysis and Recognition.Seoul.Korea:[s.n.],2005:610-614.
  • 7Amarapur B,Patil N.Video Text Extraction from Images for Character Recognition[C]//Proc.of Canadian Conference on Electrical and Computer Engineering.Ottawa,Canada:[s.n.],2006:198-201.
  • 8Wang Rongrong,Jin Wanjun,Wu Lide.A Novel Video Caption Detection Approach Using Multi-frame Integration[C]//Proc.of International Conference on Pattern Recognition.Los Alamitos,CA,USA:[s.n.],2004:449-452.
  • 9Garcia C,Apostolidis X.Text Detection and Segmentation in Complex Color Images[C]//Proc.of IEEE International Conference on Acoustics,Speech,and signal Processing.Istanbul.Turkey:[s.n.],2000:2326-2329.
  • 10Lyu M R,Song Jiqiang,Cai Min.A Comprehensive Method for Multilingual Video Text Detection.Localization,and Extraction[J].IEEE Transactions on Circuits and Systems for Video Technology,2005,15(2):243-255.

共引文献8

同被引文献10

  • 1Yi Cheng Wei,Chang Hong Lin.A robust video text detection approach using SVM[J]. Expert Systems With Applications . 2012 (12)
  • 2Shivakumara, Palaiahnakote,Phan, Trung Quy,Tan, Chew Lim.A Laplacian approach to multi-oriented text detection in video. IEEE Transactions on Pattern Analysis and Machine Intelligence . 2011
  • 3Trung Q P,Palaiahnakote S,Chew L T.A Laplacian method for video text detection. IEEE International Conference on Document Analysis and Recognition . 2009
  • 4Yi, C.,Tian, Y.Localizing Text in Scene Images by Boundary Clustering, Stroke Segmentation, and String Fragment Classification. Image Processing, IEEE Transactions on . 2012
  • 5Palaiahnakote Shivakumara,Rushi Padhuman Sreedhar,Trung Quy Ph.Multioriented Video Scene Text Detection Through Bayesian Classification and Boundary Growing. IEEE Transactions on Circuits and Systems for Video Technology . 2012
  • 6Hua, Xian-Sheng,Wenyin, Liu,Zhang, Hong-Jiang.An Automatic Performance Evaluation Protocol for Video Text Detection Algorithms. IEEE Transactions on Circuits and Systems for Video Technology . 2004
  • 7Zhu C,Ouyang Y,Gao L,et al.An automatic video textdetection,localization and extraction approach. AdvancedI nternet Based Systems and Applications . 2009
  • 8袁海东,马华东,黄晓冬.基于梯度与粗糙度的视频文本检测与定位[J].电子学报,2008,36(8):1660-1664. 被引量:9
  • 9杨高波,吴潇,张兆扬,朱宁波.基于过渡像素的视频图像文本检测与定位[J].湖南大学学报(自然科学版),2011,38(6):69-74. 被引量:3
  • 10王文震.基于流形学习的视频中文文本检测算法[J].科技通报,2012,28(10):46-48. 被引量:11

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部