Abstract
Nowadays, Digital Libraries have become a widely used service to store and share both digital born documents and digital versions of works stored by traditional libraries. Document images are intrinsically non-structured and the structure and semantic of the digitized documents is in most part lost during the conversion. Several techniques related to the Document Image Analysis research area have been proposed in the past to deal with document image retrieval applications. In this chapter a survey about the more recent techniques applied in the field of recognition and retrieval of text and graphical documents is presented. In particular we describe techniques related to recognition-free approaches.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
- IEEE Computer Society
- Digital Library
- Document Image
- Dynamic Time Warping
- Scale Invariant Feature Transform
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Alajlan, N., Kamel, M.S., Freeman, G.H.: Geometry-based image retrieval in binary image databases. IEEE Trans. on Pattern Analysis and Machine Intelligence 30(6), 1003–1013 (2008)
Bai, S., Li, L., Tan, C.: Keyword spotting in document images through word shape coding. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 331–335. IEEE Computer Society Press, Los Alamitos (2009)
Balasubramanian, A., Meshesha, M., Jawahar, C.: Retrieval from document image collections. In: Proc. IAPR Int’l Workshop on Document Analysis Systems, pp. 1–12 (2006)
Banerjee, S., Harit, G., Chaudhury, S.: Word image based latent semantic indexing for conceptual querying in document image databases. In: Proc. Int’l Conf. on Document Analysis and Recognition, vol. 2, pp. 1208–1212. IEEE Computer Society Press, Los Alamitos (2007)
Barbu, E., Héroux, P., Adam, S., Trupin, É.: Using bags of symbols for automatic indexing of graphical document image databases. In: Proc. Int’l Workshop on Graphics Recognition, pp. 195–205 (2005)
Belaid, A., Turcan, I., Pierrel, J.M., Belaid, Y., Hadjamar, Y., Hadjamar, H.: Automatic indexing and reformulation of ancient dictionaries. In: Proc. Int’l Workshop on Document Image Analysis for Libraries, pp. 342–354. IEEE Computer Society Press, Washington, DC, USA (2004)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(4), 509–522 (2002)
Cao, H., Bhardwaj, A., Govindaraju, V.: Journal of Pattern Recognition 42(12), 3374
Cao, H., Govindaraju, V.: Vector model based indexing and retrieval of handwritten medical forms. In: Proc. Int’l Conf. on Document Analysis and Recognition, vol. 1, pp. 88–92 (2007)
Chellapilla, K., Piatt, J.: Redundant bit vectors for robust indexing and retrieval of electronic ink. In: Proc. Int’l Conf. on Document Analysis and Recognition, vol. 1, pp. 387–391 (2007)
Choisy, C.: Dynamic handwritten keyword spotting based on the NSHP-HMM. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 242–246. IEEE Computer Society Press, Washington, DC, USA (2007)
Curtis, J.D., Chen, E.: Keyword spotting via word shape recognition. In: Proc. SPIE - Document Recognition II, pp. 270–277 (1995)
Delalandre, M., Ogier, J.-M., Lladós, J.: A fast CBIR system of old ornamental letter. In: Liu, W., Lladós, J., Ogier, J.-M. (eds.) GREC 2007. LNCS, vol. 5046, pp. 135–144. Springer, Heidelberg (2008)
Doermann, D., Doermann, D.: The indexing and retrieval of document images: A survey. Computer Vision and Image Understanding 70, 287–298 (1998)
Fataicha, Y., Cheriet, M., Nie, Y., Suen, Y.: Retrieving poorly degraded OCR documents. International Journal of Document Analysis and Recognition 8(1), 1–9 (2006)
Fonseca, M.J., Ferreira, A., Jorge, J.A.: Generic shape classification for retrieval. In: Proc. Int’l Workshop on Graphics Recognition, pp. 291–299 (2005)
Gatos, B., Pratikakis, I.: Segmentation-free word spotting in historical printed documents. In: Proc. Int’l Conf. on Document Analysis and Recognition, p. 271. IEEE Computer Society Press, Los Alamitos (2009)
Gordo, A., Valveny, E.: A rotation invariant page layout descriptor for document classification and retrieval. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 481–485. IEEE Computer Society Press, Los Alamitos (2009)
Govindaraju, V., Cao, H., Bhardwaj, A.: Handwritten document retrieval strategies. In: Proc. of Workshop on Analytics for Noisy Unstructured Text Data, pp. 3–7. ACM, New York (2009)
Harris, Z.: Distributional structure. Word 10(23), 146–162 (1954)
Jain, A.K., Namboodiri, A.M.: Indexing and retrieval of on-line handwritten documents. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 655–659. IEEE Computer Society Press, Washington, DC, USA (2003)
Hu, J., Kashi, R., Wilfong, G.: Comparison and classification of documents based on layout similarity. Information Retrieval 2(2/3), 227–243 (2000)
Jones, G., Foote, J., Sparck Jones, K., Young, S.: Video mail retrieval: the effect of word spotting accuracy on precision. In: Int’l Conf. on Acoustics, Speech, and Signal Processing, vol. 1, pp. 309–312 (1995)
Journet, N., Ramel, J.Y., Mullot, R., Eglin, V.: A proposition of retrieval tools for historical document images libraries. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 1053–1057. IEEE Computer Society, Washington, DC, USA (2007)
Joutel, G., Eglin, V., Bres, S., Emptoz, H.: Curvelets based queries for CBIR application in handwriting collections. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 649–653. IEEE Computer Society Press, Washington, DC, USA (2007)
Karray, A., Ogier, J.M., Kanoun, S., Alimi, M.A.: An ancient graphic documents indexing method based on spatial similarity. In: Proc. Int’l Workshop on Graphics Recognition, pp. 126–134. Springer, Heidelberg (2008)
Kesidis, A., Galiotou, E., Gatos, B., Lampropoulos, A., Pratikakis, I., Manolessou, I., Ralli, A.: Accessing the content of greek historical documents. In: Proc. of Workshop on Analytics for Noisy Unstructured Text Data, pp. 55–62. ACM, New York (2009)
Khurshid, K., Faure, C., Vincent, N.: Fusion of word spotting and spatial information for figure caption retrieval in historical document images. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 266–270. IEEE Computer Society Press, Los Alamitos (2009)
Kise, K., Wuotang, Y., Matsumoto, K.: Document image retrieval based on 2D density distributions of terms with pseudo relevance feedback. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 488–492. IEEE Computer Society Press, Washington, DC, USA (2003)
Kogler, M., Lux, M.: Bag of visual words revisited: an exploratory study on robust image retrieval exploiting fuzzy codebooks. In: Proc. Int’l Workshop on Multimedia Data Mining, MDMKDD 2010, pp. 3:1–3:6. ACM, USA (2010)
Konidaris, T., Gatos, B., Ntzios, K., Pratikakis, I., Theodoridis, S., Perantonis, S.J.: Keyword-guided word spotting in historical printed documents using synthetic data and user feedback. International Journal of Document Analysis and Recognition 9(2), 167–177 (2007)
Latecki, L.J., Lakämper, R., Eckhardt, U.: Shape descriptors for non-rigid shapes with a single closed contour. In: IEEE Computer Society Conf. in Computer Vision and Pattern Recognition, pp. 424–429 (2000)
Leydier, Y., Lebourgeois, F., Emptoz, H.: Text search for medieval manuscript images. Journal of Pattern Recognition 40(12), 3552–3567 (2007)
Li, L., Lu, S.J., Tan, C.L.: A fast keyword-spotting technique. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 68–72. IEEE Computer Society, Washington, DC, USA (2007)
Liang, S., Sun, Z.: Sketch retrieval and relevance feedback with biased SVM classification. Pattern Recognition Letters 29(12), 1733–1741 (2008)
Licata, A., Psarrou, A., Kokla, V.: Revealing the visually unknown in ancient manuscripts with a similarity measure for IR-imaged inks. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 818–822. IEEE Computer Society Press, Los Alamitos (2009)
Llados, J., Sanchez, G.: Indexing historical documents by word shape signatures. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 362–366. IEEE Computer Society Press, Washington, DC, USA (2007)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)
Lu, S., Li, L., Tan, C.L.: Document image retrieval through word shape coding. IEEE Trans. on Pattern Analysis and Machine Intelligence 30(11), 1913–1918 (2008)
Lu, S., Tan, C.: Keyword spotting and retrieval of document images captured by a digital camera. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 994–998. IEEE Computer Society Press, Washington, DC, USA (2007)
Lu, S., Tan, C.L.: Retrieval of machine-printed latin documents through word shape coding. Journal of Pattern Recognition 41(5), 1816–1826 (2008)
Lu, Y., Zhang, L., Tan, C.L.: Retrieving imaged documents in digital libraries based on word image coding. In: Proc. Int’l Workshop on Document Image Analysis for Libraries, pp. 174–187. IEEE Computer Society Press, Washington, DC, USA (2004)
Manmatha, R., Han, C., Riseman, E.M.: Word spotting: A new approach to indexing handwriting. In: IEEE Computer Society Conf. in Computer Vision and Pattern Recognition, pp. 631–637. IEEE Computer Society, Los Alamitos (1996)
Marinai, S.: A Survey of Document Image Retrieval in Digital Libraries. In: Sulem, L.L. (ed.) Actes du 9ème Colloque International Francophone sur l’Ecrit et le Document, SDN 2006, pp. 193–198 (2006)
Marinai, S.: Text retrieval from early printed books. International Journal of Document Analysis and Recognition (2011); doi:10.1007/s10032-010-0146-0
Marinai, S., Faini, S., Marino, E., Soda, G.: Efficient word retrieval by means of SOM clustering and PCA. In: Bunke, H., Spitz, A.L. (eds.) DAS 2006. LNCS, vol. 3872, pp. 336–347. Springer, Heidelberg (2006)
Marinai, S., Gori, M., Soda, G.: Artificial neural networks for document analysis and recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 27(1), 23–35 (2005)
Marinai, S., Marino, E., Soda, G.: Layout based document image retrieval by means of XY tree reduction. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 432–436 (2005)
Marinai, S., Marino, E., Soda, G.: Font adaptive word indexing of modern printed documents. IEEE Trans. on Pattern Analysis and Machine Intelligence 28(8) (2006)
Marinai, S., Marino, E., Soda, G.: Tree clustering for layout-based document image retrieval. In: Proc. Int’l Workshop on Document Image Analysis for Libraries, pp. 243–251 (2006)
Marinai, S., Miotti, B., Soda, G.: Mathematical symbol indexing using topologically ordered clusters of shape contexts. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 1041–1045 (2009)
Marinai, S., Miotti, B., Soda, G.: Bag of characters and SOM clustering for script recognition and writer identification. In: Proc. Int’l Conf. on Pattern Recognition, pp. 2182–2185 (2010)
Meshesha, M., Jawahar, C.V.: Matching word images for content-based retrieval from printed document images. International Journal of Document Analysis and Recognition 11(1), 29–38 (2008)
Mitra, M., Chaudhuri, B.: Information retrieval from documents: A survey. Information Retrieval 2(2/3), 141–163 (2000)
Moghaddam, R., Cheriet, M.: Application of multi-level classifiers and clustering for automatic word spotting in historical document images. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 511–515. IEEE Computer Society Press, Los Alamitos (2009)
Nakai, T., Kise, K., Iwamura, M.: Real-time retrieval for images of documents in various languages using a web camera. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 146–150. IEEE Computer Society Press, Los Alamitos (2009)
Nguyen, T.O., Tabbone, S., Terrades, O.R.: Symbol descriptor based on shape context and vector model of information retrieval. In: Proc. IAPR Int’l Workshop on Document Analysis Systems, pp. 191–197. IEEE Computer Society, Washington, DC, USA (2008)
Perronnin, F.: Universal and adapted vocabularies for generic visual categorization. IEEE Trans. on Pattern Analysis and Machine Intelligence 30(7), 1243–1256 (2008)
Qureshi, R.J., Ramel, J.-Y., Barret, D., Cardot, H.: Spotting symbols in line drawing images using graph representations. In: Liu, W., Lladós, J., Ogier, J.-M. (eds.) GREC 2007. LNCS, vol. 5046, pp. 91–103. Springer, Heidelberg (2008)
Rath, T.M., Manmatha, R.: Features for word spotting in historical manuscripts. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 218–222. IEEE Computer Society Press, Washington, DC, USA (2003)
Rath, T.M., Manmatha, R.: Word spotting for historical documents. International Journal of Document Analysis and Recognition 9(2), 139–152 (2007)
Rodriguez, J.A., Perronnin, F.: Local gradient histogram features for word spotting in unconstrained handwritten documents. In: Proc. Int’l Conf. on Handwriting Recognition (2008)
Rodriguez-Serrano, J., Perronnin, F.: Handwritten word-image retrieval with synthesized typed queries. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 351–355. IEEE Computer Society Press, Los Alamitos (2009)
Rusiñol, M., Lladós, J.: Symbol spotting in technical drawings using vectorial signatures. In: Liu, W., Lladós, J. (eds.) GREC 2005. LNCS, vol. 3926, pp. 35–46. Springer, Heidelberg (2006)
Rusiñol, M., Lladós, J.: A region-based hashing approach for symbol spotting in technical documents. In: Liu, W., Lladós, J., Ogier, J.-M. (eds.) GREC 2007. LNCS, vol. 5046, pp. 104–113. Springer, Heidelberg (2008)
Rusiñol, M., Lladós, J.: Word and symbol spotting using spatial organization of local descriptors. In: Proc. IAPR Int’l Workshop on Document Analysis Systems, pp. 489–496. IEEE Computer Society Press, Washington, DC, USA (2008)
Rusiñol, M., Lladós, J.: Symbol Spotting in Digital Libraries: Focused Retrieval over Graphic-rich Document Collections. Springer, Heidelberg (2010)
Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18, 613–620 (1975)
Schomaker, L.: Retrieval of handwritten lines in historical documents. In: Proc. Int’l Conf. on Document Analysis and Recognition, vol. 2, pp. 594–598 (2007)
Sivic, J., Zisserman, A.: Video Google: A text retrieval approach to object matching in videos. In: Proc. Int’l Conf. on Computer Vision, vol. 2, pp. 1470–1477. IEEE Computer Society Press, Los Alamitos (2003)
Smeaton, A.F., Spitz, A.L.: Using character shape coding for information retrieval. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 974–978 (1997)
Super, B.J.: Retrieval from shape databases using chance probability functions and fixed correspondence. International Journal of Pattern Recognition and Artificial Intelligence 20(8), 1117–1138 (2006)
Tahmasebi, N., Niklas, K., Theuerkauf, T., Risse, T.: Using word sense discrimination on historic document collections. In: Proc. Joint Conf. on Digital Libraries, pp. 89–98. ACM, New York (2010)
Tan, G., Viard-Gaudin, C., Kot, A.: Information retrieval model for online handwritten script identification. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 336–340. IEEE Computer Society Press, Los Alamitos (2009)
Terasawa, K., Nagasaki, T., Kawashima, T.: Eigenspace method for text retrieval in historical documents. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 437–441 (2005)
Tzacheva, A., El-Sonbaty, Y., El-Kwae, E.A.: Document image matching using a maximal grid approach. In: Proc. SPIE Document Recognition and Retrieval IX, pp. 121–128 (2002)
Uttama, S., Loonis, P., Delalandre, M., Ogier, J.M.: Segmentation and retrieval of ancient graphic documents. In: Liu, W., Lladós, J. (eds.) GREC 2005. LNCS, vol. 3926, pp. 88–98. Springer, Heidelberg (2006)
Wan, G., Liu, Z.: Content-based information retrieval and digital libraries. Information Technology & Libraries 27, 41–47 (2008)
Waters, D., Garrett, J.: Preserving digital information. report of the task force on archiving of digital information. Tech. rep., The Commission on Preservation and Access (1996)
Wei, C.H., Li, Y., Chau, W.Y., Li, C.T.: Trademark image retrieval using synthetic features for describing global shape and interior structure. Journal of Pattern Recognition 42(3), 386–394 (2009)
Witten, I.H., Bainbridge, D.: How to Build a Digital Library. Elsevier Science Inc., New York (2002)
Wong, W.T., Shih, F.Y., Su, T.F.: Shape-based image retrieval using two-level similarity measures. International Journal of Pattern Recognition and Artificial Intelligence 21(6), 995–1015 (2007)
Zhang, B., Srihari, S., Huang, C.: Word image retrieval using binary features. In: SPIE, Document Recognition and Retrieval XI, pp. 45–53 (2004)
Zhang, W., Liu, W.: A new vectorial signature for quick symbol indexing, filtering and recognition. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 536–540. IEEE Computer Society Press, Washington, DC, USA (2007)
Zhang, Z., Jin, L., Ding, K., Gao, X.: Character-SIFT: a novel feature for offline handwritten chinese character recognition. In: Proc. Int’l Conf. on Document Analysis and Recognition, pp. 763–767. IEEE Computer Society Press, Los Alamitos (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Marinai, S., Miotti, B., Soda, G. (2011). Digital Libraries and Document Image Retrieval Techniques: A Survey. In: Biba, M., Xhafa, F. (eds) Learning Structure and Schemas from Documents. Studies in Computational Intelligence, vol 375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22913-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-22913-8_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22912-1
Online ISBN: 978-3-642-22913-8
eBook Packages: EngineeringEngineering (R0)