Abstract
Objectives: This research presents a model for Urdu Handwritten Character Recognition via images using various Machine Learning and Deep Learning Techniques. The main objective of this research is to provide comparative study on Urdu Handwritten Characters from images dataset. Methods/Statistical analysis: In this research paper, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) algorithm, Multi-Layer Perceptron (MLP), Concurrent Neural Network (CNN), Recurrent Neural Network (RNN) and Random Forest Algorithm (RF) have been implemented in order to evaluate most suitable technique for Urdu Handwritten Characters Recognition via images. Findings: Ample amount of research work has been carried out on English Language but it is clearly shown through the conducted literature review that very lesser amount of work has been done on Urdu Handwritten Characters Recognition using images. Furthermore, It has been analyzed from this research that CNN models are most efficient compared to RF, SVM and MLP as to produce reliable results in terms of optimal accuracy. Therefore, using the CNN model is a viable choice to recognize Urdu handwritten characters from the images. And proposed study provides significant contribution in automatic learning of Urdu handwritten Characters. Keywords: Urdu Handwritten Characters; Machine Learning; Deep Learning; Urdu Character Recognition
Highlights
The automatic handwritten text recognition via images is considered one of the most difficult tasks in pattern recognition research areas
Chhajro et al / Indian Journal of Science and Technology 2020;13(17):1746–1754. It is being spoken in other countries like Afghanistan, India, Bangladesh or some other languages include the literature of Urdu. When it comes to Urdu handwritten text so the research has been carried out to a very small extent and the very first script was published in 2004 which is Optical Character Recognition
Label was there for each hand written characters because machine learning supervised models has been applied for training and testing purpose in this research study
Summary
The automatic handwritten text recognition via images is considered one of the most difficult tasks in pattern recognition research areas. Chhajro et al / Indian Journal of Science and Technology 2020;13(17):1746–1754 It is being spoken in other countries like Afghanistan, India, Bangladesh or some other languages include the literature of Urdu. When it comes to Urdu handwritten text so the research has been carried out to a very small extent and the very first script was published in 2004 which is Optical Character Recognition. Urdu handwritten text recognition using image is so called ICR (Intelligent Character Recognition)(1–7). For printed text which is called OCR (Optical Character Recognition) so there are few available systems which can be used but only for printed text and not for handwritten. Machine learning algorithms used are Support Vector Machine (SVM) and K-nearest neighbor algorithm whereas the deep learning algorithms used are Multi-Layer Perceptron (MLP), Random Forest, Concurrent/Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN)(1,8)
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