scholarly journals The Study of Plate Number Recognition for Parking Security System

2020 ◽  
Vol 1 (3) ◽  
pp. 100-107
Author(s):  
Shakeeb M.A.N. Abdul Samad ◽  
Fahri Heltha ◽  
M. Faliq
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Moving Average ◽  
Recognition System ◽  
Binary Image ◽  
Connected Components ◽  
Horizontal Projection ◽  
Bar Code ◽  
Plate Number ◽  
Number Recognition

Car Plate Number Recognition System is an important platform that can be used to identify a car vehicle identity. The Recognition System is based on image processing techniques and computer vision. A webcam is used to capture an image of the car plate number from different distance, and the identification is conducted through  four processes of stages: Image Acquisition Pre-processing, Extraction, Segmentation, and Character Recognition. The Acquisition Pre-processing stage is extracted the region of interest of the image. The image is captured by live video of the webcam, then converted to grayscale and binary image. The Extraction stage is extracted the plate number characters from binary image using a connected components method. In the Segmentation stage is done by implementing horizontal projection as well as moving average filter. Lastly, in the Character Recognition, is used to identify the segmented characters of the plate number using optical character recognition. The proposed method is worked well for Malaysian's private cars plate number, and can be implemented in car park system to increase level of security of the system by confirming the bar code of the parking ticket and the plate number of the car at the incoming and outgoing gates.

Offline OCR System for Machine-Printed Turkish Using Template Matching

2011 ◽  
Vol 341-342 ◽  
pp. 565-569 ◽  
Author(s):  
Ahmed Dena Rafaa ◽  
Jan Nordin
Keyword(s):  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
Noise Removal ◽  
Connected Components ◽  
Successful Implementation ◽  
Horizontal Projection ◽  
Text Documents ◽  
Image File ◽  
Result Show

One of the most important application these days in Pattern Recognition (PR) is Optical Character recognition (OCR) which is a system used to convert scanned printed or handwritten image files into machine readable and editable format such as text documents. The main motivation behind this study is to build an OCR system for offline machine-printed Turkish characters to convert any image file into a readable and editable format. This OCR system started from preprocessing step to convert the image file into a binary format with less noise to be ready for recognition. The preprocessing step includes digitization, binarization, thresholding, and noise removal. Next, horizontal projection method is used for line detection and word allocation and 8-connected neighbors’ schema is used to extract characters as a set of connected components. Then, the Template matching method is utilized to implement the matching process between the segmented characters and the template set stored in OCR database in order to recognize the text. Unlike other approaches, template matching takes shorter time and does not require sample training but it is not able to recognize some letters with similar shape or combined letters, for this reason, this OCR system combines both the template matching and the size feature of the segmented characters to achieve accurate results. Finally, upon a successful implementation of the OCR, the recognized patterns are displayed in notepad as readable and editable text. The Turkish machine-printed database consists of a list of 630 names of cities in Turkey written by using Arial font with different sizes in uppercase, lowercase and capitalizes the first character for each word. The proposed OCR’s result show that the accuracy of the system is from 96% to 100%.

scholarly journals Vehicle Number Plate Recognition using Micro Processor

2019 ◽  
Vol 8 (12) ◽  
pp. 3682-3684
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition System ◽  
Processing Technology ◽  
License Plate ◽  
Text Format ◽  
Optical Character ◽  
Plate Number ◽  
Image Processing Technology

An automatic license number plate recognition system that uses image processing technology for identifying the written characters and numbers on the vehicle’ license plate. The system can be used in highly secured areas to provide more safety, and can be used in parking, traffic, and other places to monitor all vehicle’s number plate in a predefined area. The character is recognized by the OCR technology that is optical character recognition system. It generates the vehicle’s license plate number in a text format. The recognized number from the license plate then can be used to retrieve more information about the vehicle and the owner.

scholarly journals Unconstrained Handwritten Text Line Segmentation for Kannada Language

2019 ◽  
Vol 8 (12) ◽  
pp. 953-956
Keyword(s):  
Character Recognition ◽  
Recognition System ◽  
Text Line ◽  
Connected Component ◽  
Horizontal Projection ◽  
Text Documents ◽  
Handwritten Text ◽  
Kannada Language ◽  
System Separation ◽  
Line Segmentation

Segmentation is division of something into smaller parts and one of the Component of character recognition system. Separation of characters, words and lines are done in Segmentation from text documents. character recognition is a process which allows computers to recognize written or printed characters such as numbers or letters and to change them into a form that the computer can use. the accuracy of OCR system is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. The main aim of this paper is to find out the various text line segmentations are Projection profiles, Weighted Bucket Method. Proposed method is horizontal projection profile and connected component method on Handwritten Kannada language. These methods are used for experimentation and finally comparing their accuracy and results.

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