Two Decades of Bengali Handwritten Digit Recognition: A Survey
A.B.M. Ashikur Rahman, Md. Bakhtiar Hasan, Sabbir Ahmed, Tasnim Ahmed,, Md. Hamjajul Ashmafee, Mohammad Ridwan Kabir, Md. Hasanul Kabir

TL;DR
This survey reviews twenty years of research on Bengali handwritten digit recognition, analyzing datasets, methods, challenges, and applications to guide future advancements in the field.
Contribution
It provides a comprehensive analysis of Bengali HDR challenges, datasets, approaches, and real-life applications, filling a gap in existing literature.
Findings
Analysis of two decades of datasets and methods
Identification of key challenges in Bengali HDR
Discussion of application-specific studies
Abstract
Handwritten Digit Recognition (HDR) is one of the most challenging tasks in the domain of Optical Character Recognition (OCR). Irrespective of language, there are some inherent challenges of HDR, which mostly arise due to the variations in writing styles across individuals, writing medium and environment, inability to maintain the same strokes while writing any digit repeatedly, etc. In addition to that, the structural complexities of the digits of a particular language may lead to ambiguous scenarios of HDR. Over the years, researchers have developed numerous offline and online HDR pipelines, where different image processing techniques are combined with traditional Machine Learning (ML)-based and/or Deep Learning (DL)-based architectures. Although evidence of extensive review studies on HDR exists in the literature for languages, such as English, Arabic, Indian, Farsi, Chinese, etc.,…
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Image Processing and 3D Reconstruction · Vehicle License Plate Recognition
