System of Automatic Recognition of Video Text Amazigh based on the Random Forest

Y. Rachidi
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Abstract

In this paper; we introduce a system of automatic recognition of Video Text Amazigh based on the Random Forest. After doing some pretreatments on the video and picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the convolutional neural network (CNN) and the Random Forest method. We carried out the experiments with a database containing 3300 samples collected from different writers. The experimental results show that our proposed OCR system is very efficient and provides good recognition accuracy rate of handwriting characters images acquired via Video camera phone.
基于随机森林的视频文本自动识别系统
在本文中;介绍了一种基于随机森林的视频文本自动识别系统。在对视频和图片进行预处理后,将文本分割成行,然后分割成字符。在特征提取阶段,我们将输入数据表示为原语向量。这些特征与像素的密度有关,并从二值图像中提取出来。在分类阶段,我们研究了两种不同分类器类型的四种分类方法,即卷积神经网络(CNN)和随机森林方法。我们在一个包含3300个来自不同作者的样本的数据库中进行了实验。实验结果表明,本文提出的OCR系统对手机摄像头采集的手写字符图像具有较高的识别准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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