期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：12
页码：1-6
出版社：Science and Information Society (SAI)
摘要：In this paper, an offline holistic handwritten
Arabic text recognition system based on Principal Component
Analysis (PCA) and Support Vector Machine (SVM) classifiers is
proposed. The proposed system consists of three primary stages:
preliminary processing, feature extraction using PCA, and
classification using the polynomial, linear, and Gaussian SVM
classifiers. In this proposed system, text skeleton is first extracted
and the images of the text are normalized into uniform size for
extraction of the global features of the Arabic words using PCA.
Recognition performance of this proposed system was evaluated
on version 2 of the IFN/ENIT database of handwritten Arabic
text using the polynomial, linear, and Gaussian SVM classifiers.
The classification results of the proposed system were compared
with the results produced by a benchmark. TRS that is
depending on the Discrete Cosine Transform (DCT) method
using numerous normalization sizes of Arabic text images. The
experimental testing results support the effectiveness of the
proposed system in holistic recognition of the handwritten Arabic
text.
关键词：Handwritten Arabic text; holistic recognition;
principal component analysis; support vector machines
