License Plate Recognition Based on Neural Network Algorithm to Improve Research

2013 ◽  
Vol 860-863 ◽  
pp. 2892-2897 ◽  
Author(s):  
De Yong Liu ◽  
Hong Song ◽  
Quan Pan
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Bp Neural Network ◽  
High Speed ◽  
Recognition Rate ◽  
Training Transfer ◽  
License Plate ◽  
License Plate Recognition ◽  
The Real ◽  
Time Performance

with the development of intelligent transportation technology, which all countries are suitable for their own license plate recognition system is developed. But because of the CCD camera Angle problem will make license plate image tilt; Segmentation after do not match the characters in size and character discontinuity, led to license plate recognition rate is not high, speed slow, reduce the real-time performance of the system. In order to improve the rate of convergence, the recognition rate presents a license plate recognition algorithm based on BP neural network. First put the image correction, segmentation of character normalization processing and eliminate the unfavorable factors, then puts forward characteristics of characters input for training the BP neural network. By setting the network weights and training transfer function, improved algorithm to improve the recognition rate of the system, as well as the real-time performance.

A BACK PROPAGATION BASED REAL-TIME LICENSE PLATE RECOGNITION SYSTEM

2008 ◽  
Vol 22 (02) ◽  
pp. 233-251 ◽  
Author(s):  
YO-PING HUANG ◽  
TSUN-WEI CHANG ◽  
YEN-REN CHEN ◽  
FRODE EIKA SANDNES
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Recognition Rate ◽  
Back Propagation ◽  
Recognition System ◽  
Back Propagation Neural Network ◽  
License Plate ◽  
License Plate Recognition ◽  
Video Frames ◽  
Parking Lot

License plate recognition systems have been used extensively for many applications including parking lot management, tollgate monitoring, and for the investigation of stolen vehicles. Most researches focus on static systems, which require a clear and level image to be taken of the license plate. However, the acquisition of images that can be successfully analyzed relies on both the location and movement of the target vehicle and the clarity of the environment. Moreover, only few studies have addressed the problems associated with instant car image processing. In view of these problems, a real-time license plate recognition system is proposed that recognizes the video frames taken from existing surveillance cameras. The proposed system finds the location of the license plate using projection analysis, and the characters are identified using a back propagation neural network. The strategy achieves a recognition rate of 85.8% and almost 100% after the neural network has been retrained using the erroneously recognized characters, respectively.

License Plate Fault-Tolerant Characters Recognition Algorithm Based on Color Segmentation and BP Neural Network

2013 ◽  
Vol 411-414 ◽  
pp. 1281-1286
Author(s):  
Xiao Chun Wang ◽  
Guo Wei Yang ◽  
Yang Yang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Fault Tolerant ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Color Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Shape Information ◽  
Location Algorithm

According to the license plate recognition problem, this paper did the research about license plate location and characters recognition. It proposed two new algorithms, they separately are license location algorithm based on color segmentation and fault-tolerant characters recognition algorithm based on BP neural network. In the pre-processing stage, it proposed image enhancement algorithm which could make the image more easily analyzed by computer. In the location stage, it made utilization of color and shape information, and then proposed location algorithm. In the recognition stage, it fully made the consideration of characters fault-tolerant, and then made the use of improved BP neural network to recognize characters. Experiments show that the special license plate fault-tolerant characters recognition algorithm is more accurate than the original license plate recognition methods, and its recognition rate has been improved greatly.

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Recognition Rate ◽  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
License Plate Recognition ◽  
Image Pixels

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

scholarly journals A Method of License Plate Recognition Based on BP Neural Network with Median Filtering

2019 ◽  
Vol 1229 ◽  
pp. 012033
Author(s):  
Miaomiao Li ◽  
Zhenjiang Miao ◽  
Jiaji Wang ◽  
Shengbo Wang ◽  
Yuanhao Zhang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
License Plate ◽  
License Plate Recognition ◽  
Median Filtering

A Recognition Method of License Plate Number Based on BP Neural Network

2014 ◽  
Vol 596 ◽  
pp. 422-426
Author(s):  
Bing Xiang Liu ◽  
Yan Hua Huang ◽  
Xu Dong Wu ◽  
Ying Xi Li
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Simulation Experiment ◽  
Processing Technique ◽  
Automatic Recognition ◽  
License Plate ◽  
License Plate Recognition ◽  
Recognition Method ◽  
Previous Period ◽  
Neural Network Algorithm

According to the current technological deficiency of license plate recognition, this paper uses digital graphic processing technique and BP Neural Network algorithm fusion to achieve automatic recognition of license plate. Input the image settled in the previous period in the trained BP neural network to obtain the final license plate character through simulation. The validity and feasibility of the algorithm can be verified through the simulation experiment of standard license plate image.

Sign in / Sign up

Export Citation Format

Share Document