Neural network based optical character recognition system

N. Dojčinović, I. Mihajlovic, J. Joković, V. Markovic, B. Milovanovic
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引用次数: 6

Abstract

This paper presents an application of a neural network in the optical character recognition (OCR) system. It introduces general architecture of modern OCR systems, discussing each module in detail. Specific contribution of this paper is novelty of the character extraction and segmentation, by considering them as image features. MSER (Maximally Stable Extremal Regions) feature detector is applied, discussing numerical and practical restrictions for character segmentation and recognition. The neural network is trained for character recognition and applied on the appropriate example.
基于神经网络的光学字符识别系统
介绍了神经网络在光学字符识别(OCR)系统中的应用。介绍了现代OCR系统的总体结构,并对各个模块进行了详细的讨论。本文的具体贡献在于将字符提取和分割作为图像特征进行了创新。应用最大稳定极值区域(MSER)特征检测器,讨论了字符分割和识别的数值和实际限制。对神经网络进行字符识别训练,并应用于相应的实例。
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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