انجام پروژه متلب | متلبی

کد مقاله g27

عنوان اصلی مقاله :

 OCR-based Chassis-Number Recognition using Artificial Neural Network 

تشخیص کاراکترهای شاسی اتومبیل با استفاده از شبکه های عصبی چند لایه

سال ارائه:  2009       نوع مقاله: IEEE                  گزارش فارسی: دارد 

کلید واژه : شبکه عصبی، پردازش تصویر  Vehicle Identification Number (VIN); Optical Character Recognition (OCR); Artificial Neural Network (ANN), پروژه متلب , شبیه سازی با متلب ,

Abstract— The automatic detection and recognition of
car number plates has become an important application of
artificial vision systems. Since the license plates can be replaced,
stolen or simply tampered with, they are not the ultimate
answer for vehicle identification. The objective is to develop
a system whereby vehicle identification number (VIN) or
vehicle chassis number is digitally photographed, and then
identified electronically by segmenting the characters from the
embossed VIN. In this paper we present a novel algorithm
for vehicle chassis number identification based on optical
character recognition (OCR) using artificial neural network. The
algorithm is tested on over thousand vehicle images of different
ambient illumination. While capturing these images, the VIN
was kept in-focus, while the angle of view and the distance
from the vehicle varied according to the experimental setup.
These images were subjected to pre-processing which comprises
of some standard image processing algorithms. The resultant
images were then fed to the proposed OCR system. The OCR
system is a three-layer artificial neural network (ANN) with
topology 504-600-10. The major achievement of this work is the
rate of correct identification, which is 95.49% with zero false
identification.
Index Terms: Vehicle Identification Number (VIN); Optical
Character Recognition (OCR); Artificial Neural Network (ANN).

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