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

Ghai, L.L. and Hisham, S.B. and Yahya, N. (2014) Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features. In: UNSPECIFIED.

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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. © 2014 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 1
Uncontrolled Keywords: Character recognition; Cost effectiveness; Spreadsheets, Automatic assessment; Chi Square distance; Fundamental research; Handwritten recognition; Local binary patterns; Number recognition; Off-line handwritten; Structural feature, Pattern recognition systems
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 25 Mar 2022 09:05
Last Modified: 25 Mar 2022 09:05

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