Brazilian License Plate Detection Using Histogram of Oriented Gradients and Sliding Windows
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TLDR
A sliding window approach based on Histogram of Oriented Gradients (HOG) features is used for Brazilian license plate detection, which consists in scanning the whole image in a multiscale fashion such that the license plate is located precisely.Abstract:
Due to the increasingly need for automatic traffic monitoring, vehicle license plate detection is of high interest to perform automatic toll collection, traffic law enforcement, parking lot access control, among others. In this paper, a sliding window approach based on Histogram of Oriented Gradients (HOG) features is used for Brazilian license plate detection. This approach consists in scanning the whole image in a multiscale fashion such that the license plate is located precisely. The main contribution of this work consists in a deep study of the best setup for HOG descriptors on the detection of Brazilian license plates, in which HOG have never been applied before. We also demonstrate the reliability of this method ensured by a recall higher than 98% (with a precision higher than 78%) in a publicly available data set.read more
Citations
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Proceedings ArticleDOI
Real-Time Brazilian License Plate Detection and Recognition Using Deep Convolutional Neural Networks
TL;DR: This work proposed an end-to-end DL-ALPR system for Brazilian license plates based on state-of-the-art Convolutional Neural Network architectures and was able to correctly detect and recognize all seven characters of a license plate in 63.18% of the test set.
Journal ArticleDOI
Real-time license plate detection and recognition using deep convolutional neural networks
TL;DR: This work presents an end-to-end ALPR method based on a hierarchical Convolutional Neural Network, and shows that the augmentation process significantly increases the recognition rate.
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Benchmark for License Plate Character Segmentation
TL;DR: In this article, the authors proposed a novel benchmark composed of a dataset designed to focus specifically on the character segmentation step of the ALPR within an evaluation protocol, which is composed of 2,000 Brazilian license plates consisting of 14,000 alphanumeric symbols and their corresponding bounding box annotations.
Proceedings ArticleDOI
Real Time Indian License Plate Detection using Deep Neural Networks and Optical Character Recognition using LSTM Tesseract
Jaskirat Singh,Bharat Bhushan +1 more
TL;DR: The goal of this paper is to design a robust technique for License Plate Detection in the images using deep neural networks, Pre-process the detected license plates and perform License Plate Recognition (LPR) using LSTMTesseract OCR Engine and achieve robust results.
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Self-Supervised Collaborative Multi-Network for Fine-Grained Visual Categorization of Tomato Diseases
TL;DR: This work proposes a novel model, which consists of 3 networks, including a Location network, a Feedback network, and a Classification network, named LFC-Net, which achieves the most advanced performance in the tomato dataset, with accuracy up to 99.7%.
References
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