Indian Vehicle Number-Plate Recognition using Single Shot Detection and OCR

Sparsh Jain, Rishikesh Rathi, R. Chaurasiya
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引用次数: 6

Abstract

Increasing number of vehicles on the streets has made it very difficult to track every vehicle, which has resulted into exponential rise in violation of traffic rules. It is very difficult to manually keep track of all the vehicles and keep them in check. Due to human limitations, intelligent and smart monitoring has become a topic of discussion. For every vehicle to be acknowledged, number-plate detection is very necessary. However, many vehicles in a single image and varying lighting conditions present challenges to automatic number-plat recognition systems. Varying shapes and sizes of characters on number-plate presents additional difficulties in Indian context. To address these issues, this work proposes to employ inception version 3 (v3) model for classification of number plates form input images. The study then proposes to employ single shot detection (SSD), which is one of the best available architecture to detect multiple objects at once, resulting in faster and more accurate detection. At a later stage, each character in the number plate is recognized by Tesseract optical character recognition (OCR) engine. The experimental results presented in the study validates the effectiveness of the proposed work.
使用单发检测和OCR的印度车牌识别
街道上车辆的增加使得追踪每一辆车变得非常困难,这导致违反交通规则的情况呈指数级上升。手动跟踪所有车辆并对其进行检查是非常困难的。由于人类的局限性,智能化、智能化监控成为人们讨论的话题。对于每一辆车来说,车牌检测是非常必要的。然而,单一图像中的许多车辆和不同的照明条件对自动车牌识别系统提出了挑战。车牌上不同形状和大小的字符在印度语境中带来了额外的困难。为了解决这些问题,本工作建议采用inception版本3 (v3)模型对输入图像中的车牌进行分类。然后,本研究提出采用单镜头检测(SSD),这是一次检测多个目标的最佳架构之一,从而实现更快,更准确的检测。在后期,号牌中的每个字符被Tesseract光学字符识别(OCR)引擎识别。实验结果验证了所提工作的有效性。
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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