Automatic Car Plate Recognition System
碩士 === 國立交通大學 === 電控工程研究所 === 105 === Car plate recognition system is widely used in all aspects of life, such as parking lot management system and highway toll collection. However, existing recognition systems are limited by image processing. To recognize car plates instantly, extra sensors are in...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2016
|
Online Access: | http://ndltd.ncl.edu.tw/handle/qafkj5 |
id |
ndltd-TW-105NCTU5449001 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-105NCTU54490012019-05-15T23:09:03Z http://ndltd.ncl.edu.tw/handle/qafkj5 Automatic Car Plate Recognition System 自動化車牌辨識系統 Zeng, Shi-Hao 曾士豪 碩士 國立交通大學 電控工程研究所 105 Car plate recognition system is widely used in all aspects of life, such as parking lot management system and highway toll collection. However, existing recognition systems are limited by image processing. To recognize car plates instantly, extra sensors are installed on most of systems, or a region of interest is defined on single lane. Our aims of research are to process surveillance video directly without additional devices, and to achieve multi-lane recognition in real time. By principal component analysis, we can separate the cars from the background, therefore plenty of processing time has been saved. We also develop the robust recognition module based on different samples, which are influenced by environmental factors such as reflection, dirt and shadow. The module implements plate segmentation by Sobel edge detector and Gaussian filter, analyzes connected component in plate to segment characters and uses support vector machine to recognize characters. In the last chapter, we examine the system with a high-definition video. The result show that our system can recognize the simulation video in real time, and the overall rate of success is 91.35%. Jou, Chi-Cheng 周志成 2016 學位論文 ; thesis 56 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立交通大學 === 電控工程研究所 === 105 === Car plate recognition system is widely used in all aspects of life, such as parking lot management system and highway toll collection. However, existing recognition systems are limited by image processing. To recognize car plates instantly, extra sensors are installed on most of systems, or a region of interest is defined on single lane.
Our aims of research are to process surveillance video directly without additional devices, and to achieve multi-lane recognition in real time. By principal component analysis, we can separate the cars from the background, therefore plenty of processing time has been saved. We also develop the robust recognition module based on different samples, which are influenced by environmental factors such as reflection, dirt and shadow. The module implements plate segmentation by Sobel edge detector and Gaussian filter, analyzes connected component in plate to segment characters and uses support vector machine to recognize characters.
In the last chapter, we examine the system with a high-definition video. The result show that our system can recognize the simulation video in real time, and the overall rate of success is 91.35%.
|
author2 |
Jou, Chi-Cheng |
author_facet |
Jou, Chi-Cheng Zeng, Shi-Hao 曾士豪 |
author |
Zeng, Shi-Hao 曾士豪 |
spellingShingle |
Zeng, Shi-Hao 曾士豪 Automatic Car Plate Recognition System |
author_sort |
Zeng, Shi-Hao |
title |
Automatic Car Plate Recognition System |
title_short |
Automatic Car Plate Recognition System |
title_full |
Automatic Car Plate Recognition System |
title_fullStr |
Automatic Car Plate Recognition System |
title_full_unstemmed |
Automatic Car Plate Recognition System |
title_sort |
automatic car plate recognition system |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/qafkj5 |
work_keys_str_mv |
AT zengshihao automaticcarplaterecognitionsystem AT céngshìháo automaticcarplaterecognitionsystem AT zengshihao zìdònghuàchēpáibiànshíxìtǒng AT céngshìháo zìdònghuàchēpáibiànshíxìtǒng |
_version_ |
1719140947658276864 |