Das, Soumi and Shivakumara, Palaiahnakote and Pal, Umapada and Ramachandra, Raghavendra (2023) Gaussian Kernels Based Network for Multiple License Plate Number Detection in Day-Night Images. In: Document Analysis and Recognition - ICDAR 2023, Pt V, 21-26 August 2023, San Jose, California.
Full text not available from this repository.Abstract
Detecting multiple license plate numbers is crucial for vehicle tracking and re-identification. The reliable detection of multiple license plate numbers requires addressing the challenges like image defocusing and varying environmental conditions like illumination, sunlight, shadows, weather conditions etc. This paper aims to develop a new approach for multiple license plate number detection of different vehicles in day and night scenarios. The proposed work segments the vehicle region containing license plate numbers based on a multi-column convolutional neural network and iterative clustering to reduce the background challenges and the presence of multiple vehicles. To address challenges of font contrast variations and text-like objects in the background, the proposed work introduces the Gaussian kernels that represent a text pixel distribution to integrate with a proposed deep learning model for detection, Experimental results on benchmark datasets of day and night license plate number show that the proposed model is effective and outperforms the existing methods.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | IDEAS-Technology Innovation Hub grant, Indian Statistical Institute, Kolkata, India |
| Additional Information: | 17th International Conference on Document Analysis and Recognition (ICDAR), San Jose, CA, AUG 21-26, 2023 |
| Uncontrolled Keywords: | Text detection; Vehicle detection; Text segmentation; Deep learning; Gaussian kernels; Multiple license plate number detection |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 16 Jan 2025 08:05 |
| Last Modified: | 16 Jan 2025 08:05 |
| URI: | http://eprints.um.edu.my/id/eprint/47678 |
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