DocumentCode
1930738
Title
Algorithm for Identifying Writing Stroke and Direction
Author
Chea, Neo Chin ; Ming, Eileen Su Lee ; Khalid, Puspa Inayat ; Fai, Yeong Che
Author_Institution
Fac. of Electr. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear
2012
fDate
25-27 Sept. 2012
Firstpage
94
Lastpage
98
Abstract
Handwriting difficulty is a type of learning disability that may not be detected easily and its diagnosis requires special qualification and experience. Therefore, a new evaluation method is proposed to assist in detecting handwriting problems. This method uses computerized handwriting assessment based on the identification of errors in stroke type, sequences, and direction when forming Latin alphabets. This paper discusses an algorithm to identify type and direction of stroke based on xy-coordinate inputs. The algorithm starts with classification of input into three categories of stroke patterns, which are simple straight line, complex straight line, and curve line. The type and direction of stroke will then be determined by analysis of relationship between consecutive point and also angle difference between points. The algorithm works well in classification and identification involving straight line inputs, while improvements are needed in analyzing curve lines and complex lines involving smooth corner.
Keywords
handwriting recognition; medical computing; medical disorders; Latin alphabets; computerized handwriting assessment; handwriting difficulty; learning disability; stroke patterns; writing direction identification; writing stroke identification; xy-coordinate inputs; Algorithm design and analysis; Classification algorithms; Clocks; Handwriting recognition; Heuristic algorithms; Shape; Writing; handwriting assessment; handwriting difficulty; stroke recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on
Conference_Location
Kuantan
ISSN
2166-8531
Print_ISBN
978-1-4673-3113-5
Type
conf
DOI
10.1109/CIMSim.2012.54
Filename
6338052
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