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International Journal of Automation and Computing 2018, Vol. 15 Issue (4) :454-461    DOI: 10.1007/s11633-015-0943-5
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MFSR: Maximum Feature Score Region-based Captions Locating in News Video Images
Zhi-Heng Wang, Chao Guo, Hong-Min Liu, Zhan-Qiang Huo
School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China
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Abstract For news video images, caption recognizing is a useful and important step for content understanding. Caption locating is usually the first step of caption recognizing and this paper proposes a simple but effective caption locating algorithm called maximum feature score region (MFSR) based method, which mainly consists of two stages: In the first stage, up/down boundaries are attained by turning to edge map projection. Then, maximum feature score region is defined and left/right boundaries are achieved by utilizing MFSR. Experiments show that the proposed MFSR based method has superior and robust performance on news video images of different types.
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KeywordsNews video images   captions recognizing   captions locating   content understanding   maximum feature score region (MFSR)     
Received: 2015-01-15; published: 2015-05-20
Corresponding Authors: Hong-Min Liu     Email: hongminliu@hpu.edu.cn
About author: Zhi-Heng Wang received the B.Sc.degree in mechatronic engineering from Beijing Institute of Technology,China in 2004, and the Ph.D.degree from the Institute of Automation,Chinese Academy of Sciences,China in 2009. E-mail:wzhenry@eyou.com;Chao Guo received the B.Sc.degree from Henan Polytechnic University,China in 2013.E-mail:xiaofuxing@126.com;Hong-Min Liu received the B.Sc.degree in electrical&information engineering from Xi'dian University,China in 2004, and her Ph.D.degree from the Institute of Electronics,Chinese Academy of Sciences, China in 2009.E-mail:hongminliu@hpu.edu.cn;Zhan-Qiang Huo received the B.Sc. degree in mathematics and applied mathematics from the Hebei Normal University of Science&Technology,China in 2003.E-mail:hzq@hpu.edu.cn
Cite this article:   
Zhi-Heng Wang, Chao Guo, Hong-Min Liu, Zhan-Qiang Huo. MFSR: Maximum Feature Score Region-based Captions Locating in News Video Images[J]. International Journal of Automation and Computing , vol. 15, no. 4, pp. 454-461, 2018.
URL:  
http://www.ijac.net/EN/10.1007/s11633-015-0943-5      或     http://www.ijac.net/EN/Y2018/V15/I4/454
 
[1] G.. Sahoo, T. Kumar, B. L. Raina, C. M. Bhatia. Text extraction and enhancement of binary images using cellular automata. International Journal of Automation and Computing, vol. 6, no. 3, pp. 254-260, 2009.
[2] S. Y. Yan, X. X. Xu, Q. S. Liu. Robust Text Detection in Natural Scenes Using Text Geometry and Visual Appearance. International Journal of Automation and Computing, vol. 11, no. 5, pp. 480-488, 2014.
[3] K. Jung, K. I. Kim, A. K. Jain. Text information extraction in images and video: a survey. Pattern Recognition, vol. 37, no. 5, pp. 977-997, 2004.
[4] P. Shivakumara, T. Q. Phan, C. L. Tan. Video text detection based on filters and edge features. In IEEE International Conference on Multimedia and Expo, New York, USA, pp. 514-517, 2009.
[5] Y. Wei, C. Lin. A robust video text detection approach using SVM. Expert Systems with Applications, vol. 12, no. 39, pp. 10832-10840, 2012.
[6] P. Shivakumara, W. Huang, T. Q. Phan, C. L. Tan. Accurate video text detection through classification of low and high contrast images. Pattern Recognition, vol. 6, no. 43, pp. 2165 2010.
[7] D. Chen, J.M. Odobez, H. Bourlard. Text detection and recognition in images and video frames. Pattern Recognition, vol. 37, no. 3, pp. 595-608, 2004.
[8] N. Dimitrova, H. Zhang, B. Shahraray, I. Sezan, T. Huang, A. Zakhor. Applications of video-content analysis and retrieval. Multimedia, IEEE, vol. 9, no. 3, pp. 43-55, 2002.
[9] M. R. Lyu, J. Song, M. Cai. A comprehensive method for multilingual video text detection, localization, and extraction. IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 2, pp. 243-255, 2005.
[10] D. Chen, J. M. Odobez, J. P. Thiran. A localization/verification scheme for finding text in images and video frames based on contrast independent features and machine learning methods. Signal Processing: Image Communication, vol. 3, no. 19, pp. 205-217, 2004.
[11] R. Liehart, A. Wernicke. Localizing and segmenting text in images and videos. IEEE Transactions on Circuits and Systems for Video Technology, vol. 4, no. 12, pp. 256-268, 2002.
[12] C. Jung, Q. Liu, J. Kim. A new approach for text segmentation using a stroke filter. Signal Processing, vol. 7, no. 88, pp. 1907-1916, 2008.
[13] M. Cai, J. Song, M.R. Lyu. A new approach for video text detection. IEEE International Conference on Image Processing, Rochester, New York, USA, pp. 117-120, 2002.
[14] J. C. Shim, C. Dorai, R. Bolle. Automatic text extraction from video for content-based annotation and retrieval. In: Proceedings of the International Conference on Pattern Recognition, Brisbane, Queensland, Australia, vol. 1, pp. 618-620, 1998.
[15] J. Yan, X. Gao. Detection and recognition of text superimposed in images base on layered method. Neurocomputing, vol. 134, no. 25, pp. 3-14, 2014.
[16] J. Yan, X. Gao. Chinese text location under complex background using Gabor filter and SVM. Neurocomputing, vol. 74, no. 17, pp. 2998-3008, 2011.
[17] D. Chen, K. Shearer, H. Bourlard. Text enhancement with asymmetric filter for video OCR. In: Proceedings of International Conference on Image Analysis and Processing, Palermo, Italy, pp. 192-197, 2001.
[18] M. Anthimopoulos, B. Gatos, I. Pratikakis. Multi-resolution text detection in video frames. In: International Conference on Computer Vision Theory and Applications, Barcelona, Spain, pp. 161-166, 2007.
[19] C. Shi, C. Wang, B. Xiao, Y. Zhang, S. Gao. Scene text detection using graph model built upon maximally stable extremal regions. Pattern Recognition Letters, vol. 34, no. 2, pp. 107-116, 2013.
[20] Q. Ye, Q. Huang, W. Gao, D. Zhao. Fast and robust text detection in images and video frames. Image and Vision Computing, vol. 23, no. 6, pp. 565-576, 2005.
[21] K. I. Kim, K. Jung, J. H. Kim. Texture-based approach for text detection in images using support vector machines and continuously adaptive mean shift algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1631-1639, 2003.
[22] M. Anthimopoulos, B. Gatos, I. Pratikakis. A two-stage scheme for text detection in video images. Image and Vision Computing, vol. 28, no. 9, pp. 1413-1426, 2010.
[23] H. Zhang, K. Zhao, Y. Z. Song, J. Guo, Text extraction from natural scene image: A survey. Neurocomputing, vol. 122, no. 25, pp. 310-323, 2013.
[24] H. Huang, P. Shi, L. W. Yang, A new method of caption location and segmentation in news video. In: International Congress on Image and Signal Processing, Dalian, China, pp. 365-369, 2014.
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