A Novel Method for Persian Handwritten Digit Recognition Using Support Vector Machine

Majlesi Journal of Electrical Engineering

مقاله 8، دوره 12، شماره 3، آذر 2018، صفحه 63-67   

نوع مقاله: Review Article

نویسندگان

Mojtaba Mohammadpoor^{* 1}؛ Abbas Mehdizadeh²؛ Hava Alizadeh Noghabi³

¹Electrical and Computer Engineering Department, University of Gonabad, Gonabad, Iran,

²Department of Electrical and Computer Engineering, University of Gonabad, Gonabad

³Department of Computing, Nilai University, Negeri Sembilan

چکیده

Handwritten digit recognition has got a special role in different applications in the field of digital recognition including; handwritten address detection, check, and document. Persian handwritten digits classification has been facing difficulties due to different handwritten styles, inter-class similarities, and intra-class differences.  In this paper, a novel method for detecting Persian handwritten digits is presented. In the proposed method, a combination of Histogram of Oriented Gradients (HOG), 4-side profiles of the digit image, and some horizontal and vertical samples was used and the dimension of the feature vector was reduced using Principal Component Analysis (PCA). The proposed method applied to the HODA database, and Support Vector Machine (SVM) was used in the classification step. Results revealed that the detection accuracy of such method has 99% accuracy with an adequate rate due to existing unacceptable samples in the database, therefore, the proposed method could improve the outcomes compared to other existing methods.

کلیدواژه‌ها

Histogram of oriented gradients (HOG)؛ Principle component analysis (PCA)؛ Support vector machine (SVM)

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