基于更快R-CNN和特征金字塔网络的菲律宾车牌检测与分类

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ) Pub Date : 2019-11-01 DOI:10.1109/HNICEM48295.2019.9072754

Allysa Kate M. Brillantes, Ciprian D. Billones, Mari Christine E. Amon, C. Cero, John Anthony C. Jose, R. Billones, E. Dadios

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引用次数: 3

摘要

人工智能(AI)图像和视频处理技术的进步，使车牌自动识别(ALPR)系统在执法和智能交通系统(ITS)中的作用变得更加重要。然而，由于菲律宾车牌的不同变化，这种系统在菲律宾的适应一直是一个挑战。本文提出了一种基于神经网络的菲律宾车牌格式检测与分类模型。该方法将车牌分为四类:1981年、2003年、2014年和其他系列。

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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Philippine License Plate Detection and Classification using Faster R-CNN and Feature Pyramid Network

The advancement of image and video processing using Artificial Intelligence (AI) have brought more significance to the role of Automatic License Plate Recognition (ALPR) systems in law enforcement and intelligent transport systems (ITS). However, the adaptation of such a system in the Philippines has been a challenge due to the different variations of Philippine license plates. In this paper, a neural network-based model for the detection and classification of different Philippine license plate formats is proposed. The proposed method classifies license plates into four categories — 1981, 2003, 2014, and other series.

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来源期刊

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )

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