Mohammed Albekairi1, Radhia Khdhir2,*, Amina Magdich3, Somia Asklany4,*, Ghulam Abbas5, Amr Yousef 6,7
CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3607-3644, 2025, DOI:10.32604/cmes.2025.069681
- 30 September 2025
Abstract License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation, which lead to pixel displacements. This article introduces a Displacement Region Recognition Method (DR2M) to address such a problem. This method operates on displaced features compared to the training input observed throughout definite time frames. The technique focuses on detecting features that remain relatively stable under haze, using a frame-based analysis to isolate edges minimally affected by visual noise. The edge detection failures are identified using a bilateral neural network through displaced feature training. The training converges bilaterally… More >