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Erschienen in:
Adaptation Approaches in Unsupervised Learning: A Survey of the State-of-the-Art and Future Directions Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Combining Low-Level Features of Offline Questionnaires for Handwriting Identification

verfasst von : Dirk Siegmund, Tina Ebert, Naser Damer

Erschienen in: Image Analysis and Recognition

Verlag: Springer International Publishing

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Abstract

When using anonymous offline questionnaires for reviewing services or products it is often not guaranteed that a reviewer does this only once as intended. In this paper an applied combination of different features of handwritten characteristics and its fusion is presented to expose such manipulations. The presented approach covers the aspects of alignment normalization, segmentation, feature extraction, classification and fusion. Nine features from handwritten text, numbers and checkboxes are extracted and used to recognize hand-writer duplicates. The proposed method has been tested on a novel database containing pages of handwritten text produced by 1,734 writers. Furthermore we show that the unified biometric decision using a weighted sum combination rule can significantly improve writer identification performance even on low level features.

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Vorheriges Kapitel High-Frequency Spectral Energy Map Estimation Based Gait Analysis System Using a Depth Camera for Pathology Detection
Nächstes Kapitel Person Profiling Using Image and Facial Attributes Analyses on Unconstrained Images Retrieved from Online Sources
Literatur
1.
Abdl, B., Mohammed, K., Hashim, S.Z.M.: Handwriting identication: a direction review. In: 2009 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), pp. 459–463. IEEE (2009)
2.
Arora, H., Lee, S., Srihari, S.N., Cha, S.H.: Individuality of handwriting. J. Forensic Sci. 47(4), 1–17 (2002)
3.
Bay, H., Tuytelaars, T., Van Gool, L.: Surf: speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)CrossRef
4.
Bozinovic, R.M., Srihari, S.N.: O-line cursive script word recognition. IEEE Trans. Pattern Anal. Mach. Intell. 11(1), 68–83 (1989)CrossRef
5.
Cermeno, E., Mallor, S., Siguenza, J.A.: Offline handwriting segmentation for writer identication. In: 2014 International Symposium on Biometrics and Security Technologies (ISBAST), pp. 13–17. IEEE (2014)
6.
Damer, N., Opel, A., Nouak, A.: Biometric source weighting in multibiometric fusion: towards a generalized and robust solution. In: 22nd European Signal Processing Conference, EUSIPCO 2014, Lisbon, Portugal, 1–5 September 2014, pp. 1382–1386 (2014)
7.
Jain, R., Doermann, D.: Combining local features for offline writer identification. In: 2014 14th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 583–588. IEEE (2014)
8.
Kleber, F., Fiel, S., Diem, M., Sablatnig, R.: Cvl-database: An off-line database for writer retrieval, writer identication and word spotting. In: 2013 12th International Conference on Document Analysis and Recognition (ICDAR), pp. 560–564. IEEE (2013)
9.
Likforman-Sulem, L., Hanimyan, A., Faure, C.: A hough based algorithm for extracting text lines in handwritten documents. In: Proceedings of the Third International Conference on Document Analysis and Recognition, 1995, vol. 2, pp. 774–777. IEEE (1995)
10.
Louloudis, G., Gatos, B., Stamatopoulos, N., Papandreou, A.: Icdar 2013 competition on writer identication. In: 2013 12th International Conference on Document Analysis and Recognition (ICDAR), pp. 1397–1401, August 2013
11.
Marti, U.V., Bunke, H.: The iam-database: an english sentence database for offline handwriting recognition. Int. J. Doc. Anal. Recogn. 5(1), 39–46 (2002)CrossRefMATH
12.
Marti, U.V., Messerli, R., Bunke, H.: Writer identication using text line based features. In: Proceedings of Sixth International Conference on Document Analysis and Recognition, 2001, pp. 101–105. IEEE (2001)
13.
Schomaker, L., Bulacu, M.: Automatic writer identication using connected-component contours and edge-based features of uppercase western script. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 787–798 (2004)CrossRef
14.
Siddiqi, I., Vincent, N.: Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features. Pattern Recogn. 43(11), 3853–3865 (2010)CrossRefMATH
15.
Suen, C.Y., Nadal, C., Legault, R., Mai, T.A., Lam, L.: Computer recognition of unconstrained handwritten numerals. Proc. IEEE 80(7), 1162–1180 (1992)CrossRef
16.
Wang, D., Huang, Z., Lu, Y.: Text-independent writer recognition using modied texture and microstructure features. In: 2014 International Conference on Progress in Informatics and Computing (PIC), pp. 75–78. IEEE (2014)
17.
Wilkinson, R.A., Geist, J., Janet, S., Grother, P., Burges, C.J., Creecy, R., Hammond, B., Hull, J.J., Larsen, N., Vogl, T.P., et al.: Therst census optical character recognition system conference, vol. 184. US Department of Commerce, National Institute of Standards and Technology (1992)
18.
Wu, X., Tang, Y., Bu, W.: Offline text-independent writer identication based on scale invariant feature transform. IEEE Trans. Inf. Forensics Secur. 9(3), 526–536 (2014)CrossRef
19.
Metadaten
Titel
Combining Low-Level Features of Offline Questionnaires for Handwriting Identification
verfasst von
Dirk Siegmund
Tina Ebert
Naser Damer
Copyright-Jahr
2016
Buch
Image Analysis and Recognition

Print ISBN: 978-3-319-41500-0

Electronic ISBN: 978-3-319-41501-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-41501-7_6