Bio Inspired Approach on Automatic License Plate Recognition Technique

• Mahalakshmi , S ^[1] ; Dheeba , J ^[2]
  1. [1] Research Scholar, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore.India
  2. [2] Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore.India
• Localización: Salud, Ciencia y Tecnología - Serie de Conferencias, ISSN-e 2953-4860, Nº. 3, 2024 (Ejemplar dedicado a: Salud, Ciencia y Tecnología - Serie de Conferencias)
• Idioma: inglés
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• Resumen

  • With increasing range of vehicles in our day-to-day life, managing conveyance is one among the main problem faced by urban areas. Automatic Number Plate Recognition (ANPR) technology may be a tool that is applied to good cities in parking management systems and toll booths on highways to beat this downside. ANPR is employed to localize the license plates then extracting the text from the image, segmented each character and recognize the characters. Various localisation algorithms, segmentation and character recognition algorithms were used to complete the process. The primary objective of our research is to develop a model for number plate identification utilizing bio inspired neural network model and compare with existing neural network models based on different illumination, tilted images blurred and shaded conditions. In this research, we used spiked neural network, a third-generation neural network model, to construct an automatic number plate recognition model inspired by biotechnology. The model shows 70% accuracy in normal images. The model would be tested for neuromorphic data sets for SNN model to enhance the SNN performance