Text line processing for high-confidence skew detection in image documents

Author(s):  
Daniel Rosner ◽  
Costin-Anton Boiangiu ◽  
Alexandru Stefanescu ◽  
Nicolae Tapus ◽  
Alexandra Olteanu
Author(s):  
Joost van Beusekom ◽  
Faisal Shafait ◽  
Thomas M. Breuel
Keyword(s):  

1997 ◽  
Vol 30 (9) ◽  
pp. 1505-1519 ◽  
Author(s):  
B. Gatos ◽  
N. Papamarkos ◽  
C. Chamzas

Author(s):  
M. Ramanan

Skew detection and correction of a scanned document is a very important step in Optical Character Recognition because skew of scanned document is reducing the accuracy of text line approach for skew detection and correction to calculate the skew angle on multi-script scanned document using Radon transform, Hough transform, Harries corner, Wiener filter and smearing algorithm. In this paper, a proposed approach is compared existing skew detection and correction techniques for printed documents having different scripts: English, Tamil, Sinhala and mixed-script. A proposed hybrid method is tested on 160 documents. The overall testing results is 90.62% for skew detection and correction.


2008 ◽  
Vol 08 (01) ◽  
pp. 47-59
Author(s):  
A. V. N. MANJUNATH ◽  
K. G. HEMANTHA ◽  
S. NOUSHATH

In this paper, we propose a novel skew estimation technique for binary document images based on Boundary Growing Method (BGM), thinning and moments. BGM helps in extracting the text line blocks from the document. Thinning1 is performed to fit the best line for extracted text line blocks. Further, skew is computed for thinned line using second order moments. Several experiments have been conducted on various types of documents such as documents containing south Indian languages, English documents, journals, text with picture, noisy images, and document with different fonts and resolutions, to reveal the robustness of the proposed method. Based on the experimental results we have realized that the proposed method outperforms existing methods both in terms of mean and standard deviation.


2010 ◽  
Author(s):  
Laura Mickes ◽  
Vivian Hwe ◽  
John T. Wixted
Keyword(s):  

2012 ◽  
Vol 38 (11) ◽  
pp. 1751
Author(s):  
Lin-Zi YIN ◽  
Yong-Gang LI ◽  
Chun-Hua YANG ◽  
Wei-Hua GUI

2013 ◽  
Vol 98 (2) ◽  
pp. E364-E369 ◽  
Author(s):  
Nishant Agrawal ◽  
Yuchen Jiao ◽  
Mark Sausen ◽  
Rebecca Leary ◽  
Chetan Bettegowda ◽  
...  

Abstract Context: Medullary thyroid cancer (MTC) is a rare thyroid cancer that can occur sporadically or as part of a hereditary syndrome. Objective: To explore the genetic origin of MTC, we sequenced the protein coding exons of approximately 21,000 genes in 17 sporadic MTCs. Patients and Design: We sequenced the exomes of 17 sporadic MTCs and validated the frequency of all recurrently mutated genes and other genes of interest in an independent cohort of 40 MTCs comprised of both sporadic and hereditary MTC. Results: We discovered 305 high-confidence mutations in the 17 sporadic MTCs in the discovery phase, or approximately 17.9 somatic mutations per tumor. Mutations in RET, HRAS, and KRAS genes were identified as the principal driver mutations in MTC. All of the other additional somatic mutations, including mutations in spliceosome and DNA repair pathways, were not recurrent in additional tumors. Tumors without RET, HRAS, or KRAS mutations appeared to have significantly fewer mutations overall in protein coding exons. Conclusions: Approximately 90% of MTCs had mutually exclusive mutations in RET, HRAS, and KRAS, suggesting that RET and RAS are the predominant driver pathways in MTC. Relatively few mutations overall and no commonly recurrent driver mutations other than RET, HRAS, and KRAS were seen in the MTC exome.


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