Recognition method of license plate for black box video using Apache Kafka

Seonghu Hong, Sang-Won Jung, Chang-Sung Jeong
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引用次数: 2

Abstract

With the increase in the number of images from various channels such as a vehicle's black box, CCTV and drone, the amount of data related to the vehicles and the traffic situations is also explosively increasing. Also, the greatly increased image data analysis is further emphasizing the importance of large-scale image data processing. In this regard, this study proposed and designed a distribution system using Kafka. For high-speed processing of data, black box image frames were distributed to several nodes using Kafka, a real-time message distribution processing system. Moreover, by setting the frame of black box image as input to each node, the localization of car license plates through image processing, and segmented character recognition were explored.
基于Apache Kafka的黑箱视频车牌识别方法
随着车辆黑匣子、闭路电视和无人机等各种渠道的图像数量的增加,与车辆和交通状况相关的数据量也在爆炸式增长。同时,大量增加的图像数据分析也进一步强调了大规模图像数据处理的重要性。为此,本研究提出并设计了一个基于Kafka的分布式系统。为了实现数据的高速处理,使用实时消息分发处理系统Kafka将黑箱图像帧分发到多个节点。此外,通过设置黑箱图像的帧作为每个节点的输入,探索通过图像处理实现车牌定位和字符分割识别。
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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