|
|
|
| A Fast and Applicable Detection of Scattered Chinese Italic Characters |
| XIA Yong1,2, XIAO BaiHua1, WANG ChunHeng1, DAI RuWei1 |
1.Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080
2.Software School, Harbin Institute of Technology Weihai, Weihai 264209 |
|
|
|
|
Abstract Various algorithms of detecting italic characters are introduced and analyzed in detail. An algorithm of vertical and horizontal weighted normalized comparison is presented, which can find Chinese italic characters scattered in the documents rapidly by enlarging the differences of image features between normal and italic characters. Three collections, including character, string and document, are used to evaluate the algorithm. Various algorithms of detecting italic characters are tested and compared based on these collections. The experimental results demonstrate the proposed method is effective and applicable.
|
|
Received: 31 December 2006
|
|
|
|
|
|
[1] Ding Yimei, Okada M, Kimura F, et al. Application of Slant Correction to Handwritten Japanese Address Recognition // Proc of the 6th International Conference on Document Analysis and Recognition. Seattle, USA, 2001: 670674
[2] Ding Yimei, Kimura F, Miyake Y, et al. Slant Estimation for Handwritten Words by Directionally Refined Chain Code // Proc of the 7th International Workshop on Frontiers in Handwritten Recognition. Amsterdam, Netherlands, 2000: 5362
[3] Ding Yimei, Ohyama W, Kimura F, et al. Local Slant Estimation for Handwritten English Words // Proc of the 9th International Workshop on Frontiers in Handwritten Recognition. Kokubunji, Japan, 2004: 328333
[4] Simoncini L, Kovacs Z M. A System for Reading USA Census'90 HandWritten Fields // Proc of the 3rd International Conference on Document Analysis and Recognition. Montreal, Canada, 1995, Ⅰ: 8691
[5] Nicchiotti G, Scagliola C. Generalised Projections: A Tool for Cursive Character Normalization // Proc of 5th International Conference on Document Analysis and Recognition. Bangalore, India, 1999: 729733
[6] Ballesteros J, Travieso C M, Alonso J B, et al. Slant Estimation of Handwritten Characters by Means of Zernike Moments. Electronics Letters, 2005, 41(20): 11101112
[7] Kavallieratou E, Fakotakis N, Kokkinakis G. Slant Estimation Algorithm for OCR System. Pattern Recognition, 2001, 34(12): 25152522
[8] Zhang Li, Lu Yue, Tan C L. Italic Font Recognition Using Stroke Pattern Analysis on Wavelet Decomposed Word Images // Proc of the 17th International Conference on Pattern Recognition. Cambridge, UK, 2004, Ⅳ: 835838
[9] Bozinovic R M, Srihari S N. OffLine Cursive Script Word Recognition. IEEE Trans on Pattern Analysis and Machine Intelligence, 1989, 11(1): 6883
[10] Fan K C, Huang C H, Chuang T C. Italic Detection and Rectification. Journal of Information Science and Engineering, 2005, 23(2): 530533
[11] Li Yun, Naoi S, Cheriet M, et al. A Segmentation Method for Touching Italic Characters // Proc of the 17th International Conference on Pattern Recognition. Cambridge, UK, 2004, Ⅱ: 594597
[12] Su Liang. Restoration and Segmentation of Machine Printed Documents. Ph.D Dissertation. Windsor, Canada: University of Windsor. Department of Electrical Engineering, 1996: 9295
[13] Sun Changming, Si Deyi. Skew and Slant Correction for Document Images Using Gradient Direction // Proc of the 4th International Conference on Document Analysis and Recognition. Ulm, Germany, 1997, Ⅰ: 170174
[14] Chaudhuri B B, Garain U. Automatic Detection of Italic Bold and AllCapital Words in Document Images // Proc of the 14th International Conference on Pattern Recognition. Brisbane, Australia, 1998, Ⅰ: 610612 |
|
|
|
2007, Vol. 20 
