Automatic Assessment Mark Entry System Using Local Binary Pattern (LBP) and Salient Structural Features

Lim , Lam Ghai and Hisham, Suhaila Badarol and Yahya, Norashikin (2014) Automatic Assessment Mark Entry System Using Local Binary Pattern (LBP) and Salient Structural Features. In: 4th IEEE International Conference on Control Systems, Computing and Engineering (ICCSCE 2014), 28-30 November, Penang.

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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)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Academic Subject One:Image Processing
Academic Subject Two:Pattern Recognition
Academic Subject Three:Feature Extrcation
Departments / MOR / COE:Departments > Electrical & Electronic Engineering
ID Code:11502
Deposited By: Ms Norashikin Yahya
Deposited On:28 Apr 2015 02:54
Last Modified:28 Apr 2015 02:54

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