• Corpus ID: 14082137

Bangla automatic number plate recognition system using artificial neural network

@inproceedings{Joarder2012BanglaAN,
  title={Bangla automatic number plate recognition system using artificial neural network},
  author={Md. Mahbubul Alam Joarder and Khaled Mahmud and Ahmed Tasnuva and Mohsina Kawser and Bulbul Ahamed},
  year={2012}
}
asian-transactions.org
22 Citations
Highly Influential Citations
1
Background Citations
11
Methods Citations
9

22 Citations

Bangla Digital Number Plate Recognition using Template Matching for Higher Accuracy and Less Time Complexity

The proposed method of Bangla number plate recognition is more effective to extract the license plate region, the recognition rate and time required is also improved then some other studies done earlier.

License Plate Detection and Recognition System based on Morphological Approach and Feed-Forward Neural Network

A new algorithm for detecting Bangla license plate detection and recognizing characters and digits with the help of back-propagation feed-forward neural networks is introduced.

Nigerian Vehicle License Plate Recognition System using Artificial Neural Network

Results showed that plates without blur and stain were most accurately extracted and recognized while satisfactory results were also obtained for the others.

Nigerian Vehicle License Plate Recognition System using Artificial Neural Network

Results showed that plates without blur and stain were most accurately extracted and recognized while satisfactory results were also obtained for the others.

Automatic License Plate Recognition System for Bangla License Plates using Convolutional Neural Network

An automatic license plate recognition system that can detect and recognize Bangla license plates from an image of vehicles and uses a convolutional neural network model for this.

License plate detection and character recognition system for commercial vehicles based on morphological approach and template matching

  • A. C. RoyM. HossenDebashis Nag
  • Computer Science
    2016 3rd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT)
  • 2016
A boundary based contour algorithm, area and aspect ratio have been proposed to track down the license plate in the vehicle region and template matching has been used for recognizing the characters and the digits of the Bangla license plate.

An automated system to detect and recognize vehicle license plates of Bangladesh

An automated system to detect and recognize Retro Reflective license plates in Bangladesh using two different Convolutional Neural Network to classify digits and letters and Tesseract OCR for district names is presented.

An Automatic Traffic Rules Violation Detection and Number Plate Recognition System for Bangladesh

This research proposes a digitalized traffic controlling system in Bangladesh that consists of two major parts which are traffic rules violation detection and number plate recognition which is based on machine learning, deep learning, and computer vision technology.

Automatic Bengali number plate reader

The proposed automatic number plate recognition (ANPR) system involves image pre-processing and morphological operation followed by edge detection, regional localization and character segmentation to identify the Bengali characters in the number plate efficiently as well as with less computational complexity.

Deep Learning-Based Bangladeshi License Plate Recognition System

This paper has proposed an end- to-end license plate recognition system for Bangladeshi vehicles that has achieved 97.5% accuracy and built a diversified dataset with 2000 images where it has tried to capture the environmental factors.

References

SHOWING 1-8 OF 8 REFERENCES

Automatic License Plate Recognition System Based on Color Image Processing

The experiment performed by program based on aforementioned algorithms indicates that the LPR system based on color image processing is quite quick and accurate.

Learning-based approach for license plate recognition

  • K. K. KimK. KimJ. KimH. J. Kim
  • Computer Science
    Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501)
  • 2000
Presents a learning-based approach for the construction of a license-plate recognition system that has shown the following performances on average: car detection rate 100%, segmentation rate 97.5%, and character recognition rate about 97.2%.

Building an Automatic Vehicle License-Plate Recognition System

In VLP segmentation module, an efficient boundary line-based method combining the Hough transform and Contour algorithm is proposed which optimizes speed and accuracy in processing images taken from various positions.

An efficient method of license plate location

Color Texture-Based Object Detection: An Application to License Plate Localization

A novel color texture-based method for object detection in images that produces robust and efficient LP detection as time-consuming color texture analyses for less relevant pixels are restricted, leaving only a small part of the input image to be analyzed.

Two Neural Networks for License Number Plates Recognition

Vector quantization for license-plate location and image coding

A novel method based on vector quantization (VQ) to process vehicle images that makes it possible to perform superior picture compression for archival purposes and to support effective location at the same time.

License Plate Character Segmentation Based on the Gabor Transform and Vector Quantization

A novel algorithm for license plate detection and license plate character segmentation problems by using the Gabor transform in detection and local vector quantization in segmentation is presented.