A Robust Line Segmentation Algorithm for Arabic Printed Text with Diacritics

2017 ◽  
Vol 2017 (13) ◽  
pp. 42-47 ◽  
Author(s):  
Muna Ayesh ◽  
Khader Mohammad ◽  
Aziz Qaroush ◽  
Sos Agaian ◽  
Mahdi Washha
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Saud Malik ◽  
Ahthasham Sajid ◽  
Arshad Ahmad ◽  
Ahmad Almogren ◽  
Bashir Hayat ◽  
...  

Segmentation of cursive text remains the challenging phase in the recognition of text. In OCR systems, the recognition accuracy of text is directly dependent on the quality of segmentation. In cursive text OCR systems, the segmentation of handwritten Urdu language text is a complex task because of the context sensitivity and diagonality of the text. This paper presents a line segmentation algorithm for Urdu handwritten and printed text and subsequently to ligatures. In the proposed technique, the counting pixel approach is employed for modified header and baseline detection, in which the system first removes the skewness of the text page, and then the page is converted into lines and ligatures. The algorithm is evaluated on manually generated Urdu printed and handwritten dataset. The proposed algorithm is tested separately on handwritten and printed text, showing 96.7% and 98.3% line accuracy, respectively. Furthermore, the proposed line segmentation algorithm correctly extracts the lines when tested on Arabic text.


2002 ◽  
Vol 35 (1) ◽  
pp. 139-144 ◽  
Author(s):  
S. Charbonnier ◽  
G. Becq ◽  
L. Biot ◽  
P.Y. Carry ◽  
J.P. Perdrix

2007 ◽  
Vol 20 (2) ◽  
pp. 171-182 ◽  
Author(s):  
Zaidi Razak ◽  
Khansa Zulkiflee ◽  
Rosli Salleh ◽  
Mashkuri Yaacob ◽  
Emran Mohd Tamil

2013 ◽  
Vol 427-429 ◽  
pp. 1489-1492
Author(s):  
Fang Wang

It is all kinds of data monitoring for ICU that are very important, on the one hand, it can provide reliable reference for medical personnel, so that they can care for critical patients in time, on the other hand, it also can avoid bringing trouble which is caused by instrument to severe patients. Through the mining technology of time series data ,this paper uses online segmentation algorithm of time series, establishing continuous monitoring data model for ICU and creating a time series Table, from the data of which, it can quickly extract monitoring data, and do real-time analysis. On this basis, this paper also puts forward an evaluation method for on-line segmentation algorithm performance , and also puts forward a kind of algorithm to speed up the time sequence segmentation recursion method, which can quickly extract the key components in the data, so as to accelerate the analysis on continuous monitoring data . Finally, through the continuous monitoring and analysis on the pressure of the severe patients who are inserted artificial airway balloon, this paper tests the reliability of the algorithm, and through the analysis and comparison with the data, it proves the quickness of algorithm, and provides a theoretical basis for analysis on continuous monitoring data for ICU.


2020 ◽  
Author(s):  
Yasmine Afifah ◽  
Augustinus Sujono ◽  
Chico Hermanu Brillianto Apribowo

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