Isolated Arabic handwritten words recognition using EHD and HOG methods

Abstract

<span>Handwriting recognition is a growing field of study in computer vision, artificial intelligence and pattern recognition technology aimed to recognizing texts and handwritings of hefty amount of produced official documents and paper works by institutes or governments. Using computer to distinguish and make these documents accessible and approachable is the goal of these efforts. Moreover, recognition of text has accomplished practically a major progress in many domains such as security sector and e-government structure and more. A system for recognition text’s handwriting was presented here relied on edge histogram descriptor (EHD), histogram of orientated gradients (HOG) features extraction and support vector machine (SVM) as a classifier is proposed in this paper. HOG and EHD give an optimal features of the Arabic hand-written text by extracting the directional properties of the text. Besides that, SVM is a most common machine learning classifier that obtaining an essential classification results within various kernel functions. The experimental evaluation is carried out for Arabic handwritten images from IESK-ArDB database using HOG, EHD features and proposed work provides 85% recognition rate.</span>

Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients

“…Using an RGB image format as input, the system described in study 19 achieved a 99.3% identification rate using Optical Character Recognition (OCR) applied to handwritten Arabic (Indian) digits; where found to be effective after multiple stages including filtering, thinning, segmentation, feature extraction, and classification. Research paper 20 A Convolutional Neural Network is comprised of multiple hidden layers, an input layer, and an output layer. The hidden layers encompass a multitude of layers, including the convolutional layer, which is founded on a mathematical function known as convolution.…”

An approach to analysis of arabic text documents into text lines, words, and characters

“…For extraction of words, in literature, most of the approaches given employ a certain measure of the distance between connecting successive elements and establish a threshold for classifying the gaps between words (between-words space) and linked constituents (between-words space) from the same word (withinword space) [13]. To establish an appropriate threshold [14] suggested an approach based on the magnitude of the gaps, the method classified the gaps among connected components into three sets.…”