An intelligent framework of illumination effects elimination for Car License Plate character segmentation

J. G. Park
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引用次数: 7

Abstract

In computer vision, Automatic Car License Plate Recognition is popular research area. Many methods for Car License Plate Recognition has been developed, however, a car license plate which is degraded by illumination or dirt effects may yield false recognition because degradation elements interfere character segmentation. Although many researches for reducing degradation effects on a car license plate are established, research for degradation of various illumination effects is insufficient. This paper introduces an intelligent framework that outlines character of car license plate which is degraded by various illumination effects. Our framework shows robustness for outlining character of car license plate image under various lightning or illumination effects.
车牌字符分割中照明效果消除的智能框架
在计算机视觉中,车牌自动识别是一个热门的研究领域。目前已经开发了许多车牌识别方法,但由于车牌受到光照或污物的影响,车牌的退化因素会干扰字符分割,导致车牌识别错误。虽然对降低车牌的退化效应进行了很多研究,但对各种照明效应的退化研究还不够。本文介绍了一种智能框架,该框架能够对受光照影响而退化的车牌特征进行识别。该框架对各种闪电或光照效果下的车牌图像轮廓特征具有鲁棒性。
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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