scholarly journals Revolution by using Optical Character Recognition Technique to Identify Registered Number Plate

2019 ◽  
Vol 8 (10) ◽  
pp. 1185-1188
Keyword(s):  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
Recognition Algorithm ◽  
Research Topic ◽  
Binary Mask ◽  
Segmentation Method ◽  
Optical Character ◽  
Small Parts ◽  
Recognition Technique

From past few years, the most interesting research topic is ANPR which registration of vehicles by their number plates. The purpose of this system is used for identifying number plate of numerous automobile. From automobile images, only number plate is extracted using binary mask method. And Optical Character Recognition (OCR) technique will be done with segmentation method. In segmentation, the numbers or characters on number plate are separated into small parts which is used to recognize using template matching in optical character recognition algorithm. As a result, the recognized number plate will be displayed. Also the result of this number plate is registered or not registered number plate will be displayed as a result.

scholarly journals Vision-Based Parking Entry Control System

2018 ◽  
Vol 17 (2) ◽  
pp. 30-34
Author(s):  
Ahmad Ridhwan Wahap ◽  
Shahrulnafiin Saharudin
Keyword(s):  
Control Systems ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Intelligent Transportation System ◽  
Vision System ◽  
Intelligent Transportation ◽  
Vehicle Owner ◽  
Optical Character ◽  
Counting Algorithms ◽  
Recognition Technique

Vision-based control systems are very promising in the Intelligent Transportation System (ITS). This paper proposes a system that use the vision system to control vehicle entry at the bridge gate at a certain facility. The system detects the presence of the car and captures the front car image to proceed to plate recognition process. Vehicle plate region is extracted using the size filtering, image thresholding and object counting algorithms. Optical character recognition technique is used in the recognition module. The result from the recognition module is then compared to the record in the database for information like the vehicle owner name, type of car, etc. The overall system is implemented and simulated in LabVIEW and the performance of recognition is tested on the real image. The system can successfully detect and recognize the plate number with minimum error.

scholarly journals PENGENALAN WARNA BERBASIS ANDROID MENGGUNAKAN METODE TEMPLATE MATCHING

Compiler ◽  
2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Indra Hading Kurniawan ◽  
Nurcahyani Dewi Retnowati
Keyword(s):  
Success Rate ◽  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
Matching Method ◽  
Color Recognition ◽  
Final Project ◽  
Optical Character ◽  
Simple Implementation ◽  
Image Object

Template matching method is a simple and widely used method to recognize patterns. The weakness of this algorithm is the limited model that will be used as a template as a comparison in the database such as shape, size, and orientation. The Extraction Feature algorithm addresses the problem of template models such as the shape, size, and orientation that exist in the matching template algorithm by mapping the characteristics of the image object to be recognized. Optical character recognition is used to translate characters into digital images into text formats. Its simple implementation makes the template matching method widely used. In this final project discusses the introduction of color in an image to be detected color, this color recognition is not fully successful because of the influence of lightness. The workings of this application take picture is by taking a picture and then the application identifies the color of any existing and will issue results in the form of text percent, with a success rate of 15% and 85% failure when detecting a color.

Effects of Ambient Light, Camcorder Settings, and Automated License Plate Reader Settings on Plate Transcription Rates

2002 ◽  
Vol 1804 (1) ◽  
pp. 56-61 ◽  
Author(s):  
Michael Plotnikov ◽  
Paul W. Shuldiner
Keyword(s):  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
License Plate ◽  
Ambient Light ◽  
Light Conditions ◽  
Video Images ◽  
Optical Character ◽  
Plate Reader

The ability of an automated license plate reading (ALPR) system to convert video images of license plates into computer records depends on many factors. Of these, two are readily controlled by the operator: the quality of the video images captured in the field and the internal settings of the ALPR used to transcribe these images. A third factor, the light conditions under which the license plate images are acquired, is less easily managed, especially when camcorders are used in the field under ambient light conditions. A set of experiments was conducted to test the effects of ambient light conditions, video camcorder adjustments, and internal ALPR settings on the percent of correct reads attained by a specific type of ALPR, one whose optical character recognition process is based on template matching. Images of rear license plates were collected under four ambient light conditions: overcast with no shadows, and full sunlight with the sun in front of the camcorder, behind the camcorder, and orthogonal to the line of sight. Three camcorder exposure settings were tested. Two of the settings made use of the camcorder’s internal light meter, and the third relied solely on operator judgment. The license plates read ranged from 41% to 72%, depending most strongly on ambient light conditions. In all cases, careful adjustment of the ALPR led to significantly improved read rates over those obtained by using the manufacturer’s recommended default settings. Exposure settings based on the operator’s judgment worked best in all instances.

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