Abstract
Computer vision (CV) refers to the study of the computer simulation of human visual science. Major task of CV is to collect images (or video) so that they could be used for analysis, gathering information, and making decisions or judgements. CV has greatly progressed and developed in the past few decades. In recent years, deep learning (DL) approaches have won several contests in pattern recognition and machine learning. (DL) dramatically improved the state-of-the-art in visual object recognition, object detection, handwritten recognition and many other domains. Handwritten recognition technique is one of this tasks that targeted to extract the text from documents or another images type. In contrast to the English domain, there are a limited works on the Arabic language that achieved satisfactory results, Due to the Arabic language cursive nature that induces many technical difficulties. This paper highlighted the pre-processing and binarization methods that have been used in the literature along with proposed numerous directions for developing. We review the various current deep learning approaches and tools used for Arabic handwritten recognition (AHWR), identified challenges along this line of this research, and gives several recommendations including a framework based (DL) that is particularly applicable for dealing with cursive nature languages.
Highlights
This Image recognition is considered a major research direction in the computer vision field
Unlike the Chinese and Latin domain, off-line techniques for Arabic Handwritten Recognition (AHWR) are not well-developed yet, because the cursive nature of the language gives rise to numerous technical difficulties (Khémiri, Kacem, & Belaïd, 2014; [2])
This paper aims to accommodate a review of (AHWR) task by exploring the methods that have been used in the previous works
Summary
This Image recognition is considered a major research direction in the computer vision field. The researchers need to determine the problem areas that need to be examined in order to design adaptability and give it better features, which would enhance system performance as well. This part of the image recognition system is meant for a specific identification task. HMM-based printed Arabic text recognition is presented by [10] for various scenarios This is a procedure for partitioning the sliding window adaptively into cells. As proposed by [14], there can be a two-recognizer system, based on multi-stream HMM, for the offline recognition of an Arabic handwritten Tunisian city name. Explain the deep learning algorithms and applications in a deferent domain, followed by a review on its application on (AHWR) recent works
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