Abstract

The text extraction from the natural scene image is still a cumbersome task to perform. This paper presents a novel contribution and suggests the solution for cursive scene text analysis notably recognition of Arabic scene text appeared in the unconstrained environment. The hierarchical sub-sampling technique is adapted to investigate the potential through sub-sampling the window size of the given scene text sample. The deep learning architecture is presented by considering the complexity of the Arabic script. The conducted experiments present 96.81% accuracy at the character level. The comparison of the Arabic scene text with handwritten and printed data is outlined as well.

How to Cite
BIN AHMED, ZAINAB MALIK, MUHAMMAD IMRAN RAZZAK, RUBIYAH YUSOF, Saad. Sub-sampling Approach for Unconstrained Arabic Scene Text Analysis by Implicit Segmentation based Deep Learning Classifier. Global Journal of Computer Science and Technology, [S.l.], mar. 2019. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/1803>. Date accessed: 21 apr. 2019.