The Community for Technology Leaders
RSS Icon
Issue No.11 - November (2008 vol.30)
pp: 1913-1918
Shijian Lu , A*STAR, Singapore
Linlin Li , National University of Singapore, Singapore
Chew Lim Tan , National University of Singapore, Singapore
This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.
Image/video retrieval, Shape, Text processing, Document analysism, Document Capture, Document and Text Processing, Computing Methodologies, Shape, Vision and Scene Understanding, Artificial Intelligence
Shijian Lu, Linlin Li, Chew Lim Tan, "Document Image Retrieval through Word Shape Coding", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.30, no. 11, pp. 1913-1918, November 2008, doi:10.1109/TPAMI.2008.89
[1] N. Otsu, “A Threshold Selection Method from Graylevel Histogram,” IEEE Trans. Systems, Man, and Cybernetics, vol. 19, no. 1, pp. 62-66, 1979.
[2] O.D. Trier and T. Taxt, “Evaluation of Binarization Methods for Document Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 312-315, Mar. 1995.
[3] A.L. Spitz, “Determination of Script and Language Content of Document Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 3, pp. 235-245, Mar. 1997.
[4] S. Lu and C.L. Tan, “Script and Language Identification in Noisy and Degraded Document Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 1, pp. 14-24, Jan. 2008.
[5] S. Lu and C.L. Tan, “Retrieval of Machine-Printed Latin Documents through Word Shape Coding,” Pattern Recognition, vol. 41, no. 5, pp. 1816-1826, 2008.
[6] T. Nakayama, “Content-Oriented Categorization of Document Images,” Proc. Int'l Conf. Computational Linguistics (COLING '96), pp. 818-823, 1996.
[7] T. Nakayama, “Modeling Content Identification from Document Images,” Proc. Fourth Conf. Applied Natural Language Processing (ANLP '94), pp. 22-27, 1994.
[8] A.L. Spitz, “Using Character Shape Codes for Word Spotting in Document Images,” Shape, Structure and Pattern Recognition, pp. 382-389. World Scientific, 1995.
[9] A.F. Smeaton and A.L. Spitz, “Using Character Shape Coding for Information Retrieval,” Proc. Fourth Int'l Conf. Document Analysis and Recognition (ICDAR '97), pp. 974-978, 1997.
[10] Y. Lu and C.L. Tan, “Information Retrieval in Document Image Databases,” IEEE Trans. Knowledge and Data Eng., vol. 16, no. 11, pp. 1398-1410, Nov. 2004.
[11] C.L. Tan, W. Huang, Z. Yu, and Y. Xu, “Image Document Text Retrieval without OCR,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 838-844, June 2002.
[12] G. Salton, Introduction to Modern Information Retrieval. McGraw-Hill, 1983.
[13] / =1628877http:/ / clef/, 2008.
[14] http://www.nuance.comomnipage/, 2008.
[15] , 2008.
[16] M. Lew, N. Sebe, C. Djeraba, and R. Jain, “Content-Based Multimedia Information Retrieval: State-of-the-Art and Challenges,” ACM Trans. Multimedia Computing, Comm., and Applications, vol. 2, no. 1, pp. 1-19, 2006.
[17] Y. Yang and X. Liu, “A Re-Examination of Text Categorization Methods,” Proc. 22nd Ann. Int'l ACM Conf. Research and Development in Information Retrieval (SIGIR '99), vol. 42-49, 1999.
[18] S. Khoubyari and J.J. Hull, “Keyword Location in Noisy Document Image,” Proc. Second Ann. Symp. Document Analysis and Information Retrieval (SDAIR '93), pp. 217-231, 1993.
[19] F.R. Chen, D.S. Bloomberg, and L.D. Wilcox, “Spotting Phrases in Lines of Imaged Text,” Proc. SPIE Conf. Document Recognition II, pp. 256-269, 1995.
[20] T.M. Breuel, “The Future of Document Imaging in the Era of Electronic Documents,” Proc. Int'l Workshop Document Analysis, pp. 275-296, 2005.
[21] C.L. Tan, W. Huang, Z. Yu, and Y. Xu, “Text Retrieval from Document Images Based on Word Shape Analysis,” Applied Intelligence, vol. 18, no. 3, pp. 257-270, 2003.
17 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool