SIFT-ResNet Synergy for Accurate Scene Word Detection in Complex Scenarios

Riadh Harizi, Rim Walha, Rim Walha, Fadoua Drira

2024

Abstract

Scene text detection is of growing importance due to its various applications. Deep learning-based systems have proven effective in detecting horizontal text in natural scene images. However, they encounter difficulties when confronted with oriented and curved text. To tackle this issue, our study introduces a hybrid scene text detector that combines selective search with SIFT-based keypoint density analysis and a deep learning training architecture framework. More precisely, we investigated SIFT keypoints to identify important areas in an image for precise word localization. Then, we fine-tuned these areas with a deep learning-powered bounding box regressor. This combination ensured accurate word boundary alignment and enhancing word detection efficiency. We evaluated our method on benchmark datasets, including ICDAR2013, ICDAR2015, and SVT, comparing it with established state-of-the-art scene text detectors. The results underscore the strong performance of our scene text detector when dealing with complex scenarios.

Paper Citation

in Harvard Style

Harizi R., Walha R. and Drira F. (2024). SIFT-ResNet Synergy for Accurate Scene Word Detection in Complex Scenarios. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 980-987. DOI: 10.5220/0012426200003636

in Bibtex Style

@conference{icaart24,
author={Riadh Harizi and Rim Walha and Fadoua Drira},
title={SIFT-ResNet Synergy for Accurate Scene Word Detection in Complex Scenarios},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={980-987},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012426200003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - SIFT-ResNet Synergy for Accurate Scene Word Detection in Complex Scenarios
SN - 978-989-758-680-4
AU - Harizi R.
AU - Walha R.
AU - Drira F.
PY - 2024
SP - 980
EP - 987
DO - 10.5220/0012426200003636
PB - SciTePress