# Improving Warped Planar Object Detection Network For Automatic License Plate Recognition

Source: [Improving Warped Planar Object Detection Network For Automatic License Plate Recognition](<https://www.sota2.com/research/paper/68fa6e2a1e209131cea3e423>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:19:28.634Z

Authors: Nguyen Dinh Tra, Nguyen Cong Tri, Phan Duy Hung

Published: 2022-12-14T07:22:44.000Z

## Abstract

This paper aims to improve the Warping Planer Object Detection Network (WPOD-Net) using feature engineering to increase accuracy. What problems are solved using the Warping Object Detection Network using feature engineering? More specifically, we think that it makes sense to add knowledge about edges in the image to enhance the information for determining the license plate contour of the original WPOD-Net model. The Sobel filter has been selected experimentally and acts as a Convolutional Neural Network layer, the edge information is combined with the old information of the original network to create the final embedding vector. The proposed model was compared with the original model on a set of data that we collected for evaluation. The results are evaluated through the Quadrilateral Intersection over Union value and demonstrate that the model has a significant improvement in performance.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2212.07066>)

[PDF](<https://arxiv.org/pdf/2212.07066.pdf>)