Semi-structured document image matching and recognition

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8658, Issue , 2013, Pages

  Augereau, Olivier ^a   Journet, Nicholas ^a   Domenger, Jean Philippe ^a  

^a UNIVERSITÉ DE BORDEAUX   (France)

Author keywords

document image matching; document image retrieval; geometric transformation estimation; interest points selection

Indexed keywords

DOCUMENT IMAGE MATCHING; DOCUMENT IMAGE RETRIEVAL; GEOMETRIC TRANSFORMATIONS; INTEREST POINTS SELECTION; LOCAL DISTORTION; RECOGNITION METHODS; REPETITIVE PATTERN; SEMI-STRUCTURED DOCUMENTS;

IMAGE MATCHING; IMAGE SEGMENTATION; MATHEMATICAL TRANSFORMATIONS; OBJECT RECOGNITION;

CHARACTER RECOGNITION;

EID: 84875839335     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2003911     Document Type: Conference Paper

References (24)

1. G. Yang, C. Stewart, M. Sofka, and C. Tsai, "Alignment of challenging image pairs: Refinement and region growing starting from a single keypoint correspondence," IEEE Trans. Pattern Anal. Machine Intell 23(11), pp. 1973-1989, 2007.
2. A. Psyllos, C. Anagnostopoulos, and E. Kayafas, "Vehicle logo recognition using a sift-based enhanced matching scheme," Intelligent Transportation Systems, IEEE Transactions on 11(2), pp. 322-328, 2010.
3. M. Brown and D. Lowe, "Automatic panoramic image stitching using invariant features," International Journal of Computer Vision 74(1), pp. 59-73, 2007.
4. D. Lowe, "Distinctive image features from scale-invariant keypoints," International journal of computer vision 60(2), pp. 91-110, 2004.
5. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-up robust features (surf)," Computer Vision and Image Understanding 110(3), pp. 346-359, 2008.
6. H. Uchiyama and H. Saito, "Augmenting text document by on-line learning of local arrangement of keypoints," in Mixed and Augmented Reality, 2009. ISMAR 2009. 8th IEEE International Symposium on, pp. 95-98, IEEE, 2009.
7. G. Agam, S. Argamon, O. Frieder, D. Grossman, and D. Lewis, "Content-based document image retrieval in complex document collections," in Proc. SPIE, 6500, pp. S1-12, 2007.
8. "Ocr, icr, omr and linguistic software." http://www.abbyy.com.
9. Y. Chiang and C. Knoblock, "Recognition of multi-oriented, multi-sized, and curved text," in Document Analysis and Recognition (ICDAR), 2011 International Conference on, pp. 1399-1403, IEEE, 2011.
10. C. Clausner, S. Pletschacher, and A. Antonacopoulos, "Scenario driven in-depth performance evaluation of document layout analysis methods," in Document Analysis and Recognition (ICDAR), 2011 International Conference on, pp. 1404-1408, IEEE, 2011.
11. A. Antonacopoulos, C. Clausner, C. Papadopoulos, and S. Pletschacher, "Historical document layout analysis competition," in Document Analysis and Recognition (ICDAR), 2011 International Conference on, pp. 1516-1520, IEEE, 2011.
12. K. Takeda, K. Kise, and M. Iwamura, "Real-time document image retrieval for a 10 million pages database with a memory efficient and stability improved llah," ICDAR, pp. 1054-1058, 2011.
13. J. Hull, B. Erol, J. Graham, Q. Ke, H. Kishi, J. Moraleda, and D. Van Olst, "Paper-based augmented reality," in Artificial Reality and Telexistence, 17th International Conference on, pp. 205-209, Ieee, 2007.
14. M. Rusinol and J. Lladós, "Logo spotting by a bag-of-words approach for document categorization," in 2009 10th International Conference on Document Analysis and Recognition, pp. 111-115, IEEE, 2009.
15. R. Jain and D. Doermann, "Logo retrieval in document images," in Document Analysis Systems (DAS), 2012 10th IAPR International Workshop on, pp. 135-139, IEEE, 2012.
16. D. Doermann, "The indexing and retrieval of document images: A survey," Computer Vision and Image Understanding 70(3), pp. 287-298, 1998.
17. M. Muja and D. Lowe, "Fast approximate nearest neighbors with automatic algorithm configuration," in International Conference on Computer Vision Theory and Applications (VISSAPP 09), 340, pp. 331-340, 2009.
18. M. Fischler and R. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM 24(6), pp. 381-395, 1981.
19. C. Silpa-Anan and R. Hartley, "Optimised kd-trees for fast image descriptor matching," Computer Vision and Pattern Recognition, pp. 1-8, 2008.
20. L. Juan and O. Gwun, "A comparison of sift, pca-sift and surf," International Journal of Image Processing (IJIP) 3(4), pp. 143-152, 2009.
21. T. Kanungo, R. Haralick, and I. Phillips, "Global and local document degradation models," in Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on, pp. 730-734, IEEE, 1993.
22. T. Nakai, K. Kise, and M. Iwamura, "Use of affine invariants in locally likely arrangement hashing for camera-based document image retrieval," Document Analysis Systems VII, pp. 541-552, 2006.
23. E. Valle and M. Cord, "Advanced Techniques in CBIR: Local Descriptors, Visual Dictionaries and Bags of Features," in Tutorials of the XXII Brazilian Symposium on Computer Graphics and Image Processing, pp. 72-78, IEEE, 2009.
24. R. Vieux, J. Benois-Pineau, and J. Domenger, "Content based image retrieval using bag-of-regions," Ad-vances in Multimedia Modeling, pp. 507-517, 2012.