Andere Kunden interessierten sich auch für
![A Robust Method for Detection and Localization of License Plate]( "A Robust Method for Detection and Localization of License Plate")
A Robust Method for Detection and Localization of License Plate26,99 €![Template Matching Techniques in Computer Vision]( "Template Matching Techniques in Computer Vision")
Template Matching Techniques in Computer Vision149,99 €![Image Error Concealment Technique Using Boundary Matching Algorithm]( "Image Error Concealment Technique Using Boundary Matching Algorithm")
Image Error Concealment Technique Using Boundary Matching Algorithm23,99 €![Number Plate Recognition Using an Improved Segmentation]( "Number Plate Recognition Using an Improved Segmentation")
Number Plate Recognition Using an Improved Segmentation36,99 €![Design and Simulation of RF MEMS Switched Parallel Plate Capacitors]( "Design and Simulation of RF MEMS Switched Parallel Plate Capacitors")
Design and Simulation of RF MEMS Switched Parallel Plate Capacitors32,99 €![Car Parking Using Puzzling Logic With Code Lock System]( "Car Parking Using Puzzling Logic With Code Lock System")
Car Parking Using Puzzling Logic With Code Lock System26,99 €![Tunable Ferroelectric Matching Networks implemented into High Power RF Amplifiers for High Dynamic and Wideband Efficiency]( "Tunable Ferroelectric Matching Networks implemented into High Power RF Amplifiers for High Dynamic and Wideband Efficiency")
Tunable Ferroelectric Matching Networks implemented into High Power RF Amplifiers for High Dynamic and Wideband Efficiency51,80 €
The Car License Plate Recognition (CLPR) system is one of the important factors in the intelligent traffic engineering field. There are many researches on this topic whether handwritten character recognition, typewritten character recognition or other pattern recognition. CLPR is developed to recognise the car license plate with the implementation of Digital Image Processing (DIP) and Template Matching Algorithm (TMA) approach by using the MATLAB software. This project works on the offline input images collected by using digital camera. The method of this project is based on template matching where a character is identified by analysing its shape and the current input character is compared to each template to find either an exact match, or the template with the closest representation of the input character. Experimental results have shown the relatively high accuracy of the develop CLPR on a 100 sample image of car license plate.