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Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features

Lim , Lam Ghai and Yahya, Norashikin and Badarol Hisham, Suhaila (2014) Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features. In: International Conference on Control System, Computing & Engineering (ICCSCE) 2014, 28-30 Nov 2014, Penang, Malaysia.

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Abstract

Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a person to manually type in the marks into a spreadsheet. This method is found to be time consuming, not cost effective and prone to human mistakes. Thus, a number recognition system is developed using local binary pattern (LBP) technique to extract and convert students' identity numbers and handwritten marks on assessment forms into a spreadsheet. The training data contain three sets of LBP values for each digit. The recognition rate of handwritten digits using LBP is about 50% because LBP could not fully describe the structure of the digits. Instead, LBP is useful in term of scaling the digits `0 to 9' from the highest to the lowest similarity score as compared with the sample using chi square distance. The recognition rate can be greatly improved to about 95% by verifying the ranking of chi square distance with the salient structural features of digits.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:handwritten recognition, local binary pattern, chi square distance, structural feature
Subjects:T Technology > T Technology (General)
Academic Subject One:Academic Department - Electrical And Electronics - Instrumentation and Control - Intelligent System - Imaging in intelligent surveillance systems
Departments / MOR / COE:Departments > Electrical & Electronic Engineering
ID Code:11689
Deposited By: Suhaila Badarol Hisham
Deposited On:08 Sep 2015 03:52
Last Modified:08 Sep 2015 03:52

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