Abstract
Academic institutions such as universities and technical colleges usually employ paper-based examinations and reports to evaluate the academic performance of students. Consequently, teachers expend considerable time and energy in the marking of such paper-based examinations. We are developing an automatic paper marking system geared towards reducing this paper-marking burden on teachers. To execute paper marking, handwritten character lines are extracted from examination papers, and then characters on those lines are recognized. In this paper, we primarily discuss how the character line is extracted from handwritten examination papers without ruled lines. The extraction of character lines from non-ruled papers is difficult because of the writing characteristic of students. Further, extraction accuracy is an important factor in character recognition performance. Conventional character line extraction algorithms for printed documents perform poorly on this problem. Furthermore, most proposed methods conduct tests using document images that include only character lines. In this paper we develop a less time-consuming algorithm for this task.
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References
Adachi, Y., Yoshikawa, T., Tsuruoka, S.: Character string segmentation using thinning algorithm from handwritten document image (in Japanese), Technical report of IEICE (The Institute of Electronics Information and Communication Engineers), PRMU98-208, pp. 121–126 (1999)
Tsuruoka, S., Kimura, F., Yoshimura, M., Yokoi, S., Miyake, Y.: Thinning algorithms for digital pictures and their application to hand-printed character recognition. Trans. Inst. Electron. Inf. Commun. Eng. (IEICE) Inf. Syst. J66-D(5), 525–532 (1983)
Hirabayashi, K., Tsuruoka, S., Kawanaka, H., Takase, H., Ozaki, T.: Character line segmentation from blackboard image using hough transform. In: Proceedings of Mie Section of the Society of Instrument and Control Engineers (SICE-Mie), pp. B11-1–B11-4 (2008)
Louloudisa, G., Gatosb, B., Pratikakisb, I., Halatsisa, C.: Text line detection in handwritten documents. Pattern Recogn. 41, 3758–3772 (2008)
Chaudhuri, B.B., Bera, S.: Handwritten text line identification In: Indian Scripts, 10th International Conference on Document Analysis and Recognition, pp. 636–640 (2009)
Yin, F., Liu, C.L.: A variational bayes method for handwritten text line segmentation. In: 10th International Conference on Document Analysis and Recognition, pp. 436–440 (2009)
Yin, F., Liu, C.L.: Handwritten text extraction based on minimum spanning tree clustering. In: International Conference on Wavelet Analysis and Pattern Recognition, pp. 1123–1128 (2007)
Khayyat, M., Lam, L., Suen, C.Y., Yin, F., Liu, C.L.: Arabic handwritten text line extraction by applying an adaptive mask to morphological dilation. In: 10th IAPR International Workshop on Document Analysis Systems, pp. 100–104 (2012)
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Premachandra, C., Goto, K., Tsuruoka, S., Kawanaka, H., Takase, H. (2015). Speedy Character Line Detection Algorithm Using Image Block-Based Histogram Analysis. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_53
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DOI: https://doi.org/10.1007/978-3-319-20801-5_53
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