August 17, 2025CogITo Smart JournalOpen Access

Advancing Parking Systems: A Performance Comparison of MobileNet and Canny in License Plate Detection

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MobileNet achieves a character error rate of 18.8%, substantially better than Canny's 50.96%.
The study tests 13 license plate samples to evaluate segmentation performance in an automated system.
Both MobileNet and Canny were implemented in a web-based application using Python and HTML/CSS.
Findings suggest a shift towards deep learning-based methods for improved license plate recognition efficiency.

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Comparison of segmentation methods indicates MobileNet outperforms Canny in license plate detection accuracy.

Husain et al. (2025) studied this question.

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