(54.173.237.152) 您好!臺灣時間:2019/02/22 21:58
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
本論文永久網址: 
line
研究生:林柏達
研究生(外文):Bo-Da Lin
論文名稱:複雜背景的影片中以時間-空間方法偵測與追蹤文字
論文名稱(外文):A Spatio-Temporal Approach for Video Text Detection and Tracking in Complex Background
指導教授:王元凱王元凱引用關係
指導教授(外文):Yuan-Kai Wang
學位類別:碩士
校院名稱:輔仁大學
系所名稱:電子工程學系
學門:工程學門
學類:電資工程學類
論文出版年:2007
畢業學年度:95
語文別:英文
論文頁數:65
中文關鍵詞:文字偵測文字追蹤複雜背景
外文關鍵詞:text detectiontext trackingcomplex background
相關次數:
  • 被引用被引用:0
  • 點閱點閱:521
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:25
  • 收藏至我的研究室書目清單書目收藏:0
摘要
影片中的環境常常會影響到文字偵測系統,而最大挑戰取決文字的顏色分布、文字的大小、呈現的方向、低對比的文字背景。本篇論文提出一個新穎的方法,不僅利用空間上的紋理分析更加了時間軸上的特性來試著解決文字偵測問題。利用三維小波轉換可以分離出在空間軸與時間軸上的高頻訊號與低頻訊號,整合其子頻訊號,利用統計分析方法找出文字上特徵的不同。高斯混合貝式網路依據著統計分析資訊來分辨出影片中的文字區域,而文字追蹤利用粒子過濾器(particle filter)來追蹤文字的特徵,我們是利用視窗邊緣方向統計(kernel edgeorientation histogram)當作追蹤文字的特徵。實驗影片環境為多變化的真實世界,包含場景中的文字,其系統性能會比較其他提出的方法,而實驗結果有良好的正確率在複雜背景裡。
Video text detection in unconstrained environment is a great challenge due to arbitrary color, size, orientation and low contrast of text and background. This paper proposes a novel method that not only utilizes texture analysis in spatial domain, but also incorporates temporal information in time domain, to tackle the challenging problem. A 3D wavelet transform is first proposed to filter out high and low frequencies in both spatial and temporal domain. Statistical feature of text are extracted from the filter sub-bands. A Gaussian mixture Bayesian network is derived to classify text regions through the statistical features. Text tracking is achieved by a modified particle filter, which tracks text feature of kernel edge orientation histogram. Experiments are
conducted on various real-world videos containing challenging scene text. Performance is compared with existing method. Experimental results are very encouraging and show that the method can detect arbitrary video text in complex background with high accuracy.
Contents
Abstract (in Chinese) i
Abstract ii
Acknowledgement (in Chinese) iii
Contents iv
List of tables v
List of figures vi
1. Introduction 1
2. Review of prior work 5
3. Texture feature extraction by spatio-temporal wavelet transform 8
3.1. Extraction of spatial and temporal characteristics 8
3.2. Texture features 18
3.3. Scale integration 20
4. Text detection with Bayesian network classifier 21
5. Particle-based text tracking 29
5.1. Kernel edge 31
5.2. Particle filter 35
6. Experimental result 41
6.1. Training illustration 42
6.2. Text detection and tracking 44
6.3. Performance 48
7. Conclusions 53
References 54
References
[1] H. Li, D. Doermann, and O. Kia, "Automatic text detection and tracking in digital video," IEEE Trans. Image Processing, vol. 9, pp. 147-156, JAN. 2000.
[2] J. Xi, X.-S. Hua, X.-R. Chen, L. Wenyin, and H.-J. Zhang, "A video text detection and recognition system," International Conference on Multimedia and Expo, pp. 87-876, AUG. 2001.
[3] R. Lienhart and A. Wernicke, "Localizing and segmenting text in images and videos," IEEE Trans. Circuits amd Systems for Video Technology, vol. 12, pp. 256-268, APR. 2002.
[4] X. Tang, X. Gao, J. Liu, and H. Zhang, "A spatial-temporal approach for video caption detection and recognition," IEEE Trans. Neural Nnetworks, vol. 13, pp. 961-971, JUL. 2002.
[5] K. I. Kim, k. Jung, and J. H. Kim, "Texture-based approach for text detection in images using support vector machines and continuously adaptive mean shift algorithm," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, pp. 1631-1639, DEC. 2003.
[6] K. Jung, K. I. Kim, and A. K. Jain, "Text information extraction in images and video : a survey," The Journal of the Pattern Recognition Society, vol. 37, pp. 977-997, 2004.
[7] S. Kumar, N. Khanna, S. Chaudhury, and S. D. Joshi, "Locating text in images using matched wavelets," International Conference on Document Analysis and Recognition, pp. 595- 599, 2005.
[8] C. Liu, C. Wang, and R. Dai, "Text detection in images based on unsupervised classification of edge-based features," International Conference on Document Analysis and Recognition, vol. 2, pp. 610- 614, 2005.
[9] Y. Liu, S. Goto, and T. Ikenaga, "A robust algorithm for text detection in color images," International Conference on Document Analysis and Recognition, pp. 399 - 405, 2005.
[10] T. Saoi, H. Goto, and H. Kobayashi, "Text detection in color scene images based on unsupervised clustering of multi-channel wavelet feature," International Conference on Document Analysis and Recognition, 2005.
[11] N.-F. Law and W.-C. Siu, "An efficient computational scheme for the two-dimensional overcomplete wavelet transform," IEEE Trans. Signal Processing, vol. 50, pp. 2806-2818, NOV. 2002.
[12] X.-S. Hua, L. Wenyin, and H.-J. Zhang, "An automatic performance evaluation protocol for video text detection algorithms," IEEE Trans. Circuits amd Systems for Video Technology, vol. 14, pp. 498-507, APR. 2004.
[13] D. Crandall, S. Antani, and R. Kasturi, "Extraction of special effects caption text events from digital video," International Journal on Document Analysis and Recognition, vol. 5, pp. 138-157, SEP. 2003.
[14] Q. Ye, Q. Huang, W. Gao, and D. Zhao, "Fast and robust text detection in images and video frames," Image and Vision Computing, vol. 23, pp. 565-576, JAN. 2005.
[15] J. Gllavata, R. Ewerth, and B. Freisleben, "Text detection in images based on unsupervised classification of high-frequency wavelet coefficients,"International Conference on Pattern Recognition, pp. 425-428, 2004.
[16] R. Wang, W. Jin, and L. Wu, "A novel video caption detection approach using multi-frame integration," International Conference on Pattern Recognition, pp. 449-452, 2004.
[17] M. R. Lyu, J. Song, and M. Cai, "A comprehensive method for multilingual video text detection, localization and extraction," IEEE Trans. Circuits and Systems for Video Technology, vol. 15, pp. 243-255, FEB. 2005.
[18] H. Shiratori, H. Goto, and H. Kobayashi, "An efficient text capture method for moving robots using DCT feature and text tracking," International Conference on Pattern Recognition, vol. 2, pp. 1050-1053, AUG. 2006.
[19] M. Acharyya and M. K. Kundu, "Document image segmentation using wavelet scale -space features," IEEE Trans. Circuits amd Systems for Video Technology, vol. 12, pp. 1117-1127, DEC. 2002.
[20] V. Wu, R. Manmatha, and E. M. Riseman, "Textfinder: an automatic system to detect and recognize text in images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, pp. 1224-1229, NOV. 1999.
[21] J.-P. Antoine, R. Murenzi, P. Vandergheybst, and S. T. Ali, Two-dimensional wavelets and their relatives, Cambridge, 2004.
[22] S.-J. Choi and J. W. Woods, "Motion-compensated 3-D subband coding of video," IEEE Trans. Image Processing, vol. 8, pp. 155-167, 1999.
[23] A. Wang, Z. Xiong, P. A. Chou, and S. Mehrotra, "Three-dimensional wavelet coding of video with global motion compensation " IEEE Computer Society Data Compression Conference, Snowbird, UT, MAR. 1999.
[24] B.-J. Kim, Z. Xiong, and W. A. Pearlman, "An embedded wavelet video coder using three-dimensional set partitioning in hierarchical trees (3D SPIHT)," IEEE Trans. Circuits amd Systems for Video Technology, vol. 10, pp. 1374-1387, AUG. 2000.
[25] H. Benoit-Cattin, A. Baskurt, F. Turjman, and R. Prost, "3D medical image coding using separable 3D wavelet decomposition and lattice vector quantization," Signal Processing, vol. 59, pp. 139-153, 1997.
[26] J. Nam and A. H. Tewfik, "Progressive resolution motion indexing of video object " IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 3701-3704, Seattle, WA, MAY 1998.
[27] M. A.-M. Salem and B. Meffert, "A Comparison between 2D and 3D wavelet based Segmentation for traffic monitoring systems," Third International conference on Intelligent Computing and Information Systems, pp. 329-334, Cairo, Egypt, MAR. 2007.
[28] F. A. Mujika, J.-P. Leduc, R. Murenzi, and a. M. J. T. Smith, "A new motion parameter estimation algorithm based on the continuous wavelet transform,"IEEE Trans. Image Processing, vol. 9, pp. 873-888, MAY 2004.
[29] T. J. Burns, S. K. Rogers, M. E. Oxley, and D. W. Ruck, "A wavelet multiresolution analysis for spatio-temporal signals," IEEE Trans. Aerospace Electronic Systems, vol. 32, pp. 628-649, APR. 1996.
[30] S. G. Mallat, "A throry for multiresolution signal decomposition: the wavelet representation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, pp. 674-692, JUL. 1989.
[31] J.-L. Starck, J. Fadili, and F. Murtagh, "The undecimated wavelet decomposition and its reconstruction," IEEE Trans. Image Processing, vol. 16, pp. 297-308,2007.
[32] R. R. Coifman and D. Donoho, "Translation-invariant denoising," in Wavelets and Statistics, vol. 103, pp. 125-150, A. Antonisdis, Ed. Berlin, German: Springer-Verlag, 1995.
[33] R. N. Strickland and H. I. Hahn, "Wavelet transform methods for object detection and recovery," IEEE Trans. Image Processing, vol. 6, pp. 724-735, MAY 1997.
[34] M. J. Shensa, "Discrete wavelet transform: Wedding the à trous and Mallat algorithms," IEEE Trans. Image Processing, vol. 40, pp. 2464-2482, OCT. 1992.
[35] K. Nummiaro, E. Koller-Meier, and L. V. Gool, "An adaptive color-based particle filter," Image and Vision Computing, pp. 99-110, 2002.
[36] Y. Zhong, A. K. Jain, and M.-P. Dubuisson-Jolly, "Object tracking using deformable templates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, pp. 544-549, MAY 2000.
[37] Y. Cheng, "Mean shift, mode seeking and clustering," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, pp. 790-799, AUG. 1995.
[38] S. Kamijo, Y. Matsushita, K. Ikeuchi, and M. Sakauchi, "An occlusion-robust tracking algorithm based on a spatiotemporal markov random field model,"Electronics and Communications in Japan vol. 86, pp. 73-86, JUN. 2003.
[39] M. Isard and A. Blake, "Condensation-conditional density propagation for visual tracking," International Journal of Computer Vision, vol. 29, pp. 5-28, MAR. 1998.
[40] M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online/nonlinear/non-Gaussian bayesian tracking," IEEE Trans. Signal Processing, vol. 50, pp. 174-188, FEB. 2002.
[41] F. Gustafsson, F. Gunnarsson, N. Bergman, U. Forssell, J. Jansson, R. Karlsson,
and P.-J. Nordlund, "Particle filters for positioning, navigation and tracking,"
IEEE Trans. Signal Processing, vol. 50, pp. 425-437, FEB. 2002.
[42] J. H. Kotecha and P. M. Djuric´, "Gaussian Particle Filtering," IEEE Trans.
Signal Processing, vol. 51, pp. 2592-2600, OCT. 2003.
[43] C. Chang and R. Ansari, "Kernel particle filter for visual tracking," IEEE Trans.
Signal Processing Letters, vol. 12, pp. 242-245, MAR. 2005.
[44] C. Rasmussen and G. D. Hager, "Probabilistic data association methods for tracking complex visual objects," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, pp. 560-578, JUN. 2001.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔