LICENSE PLATE DETECTION METHOD

Since the technology was discovered with the automobile, this advancement in computer vision detection technology has slowly become part of the intelligent traffic management system. This technology can be used to divide vehicle images into different parts and outline specific regions for further identification across many systems. It is also highly applied in intelligent traffic management and video surveillance for automobiles among other applications. This paper introduces a new state-of-the-art License Plate Detection system using the CV2 Algorithm. Existing approaches have been highly prone to substantial sensitivity of the changes in illumination, not well defined and rather complex backgrounds themselves together with the plates which deterd recognition. Generally, the proposed future system is expected to exhibit high accuracy improvement and the cost of recognition for the present system may offset the problems that the current system has. All these considerations are taken into account when designing the proposed system. The proposed system based on CV2 Algorithm is supposed to exhibit considerable efficiency and robustness in handling noisy data. In this context, we gave our working model the analytical results to prove that our proposed model is much more beyond the current system since it uses the Python programming language.