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License Plate Detection Methods Based on OpenCV

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License Plate Detection Methods Based on OpenCV

License Plate Detection Methods Based on OpenCV

Mrs. M. Reddi Durga Sree

(Assistant Professor)

Computer Science and Engineering

Guru Nanak Institutions Technical Campus

Telangana, India

reddidurgasree@gmail.com

P. Akash

Computer Science and Engineering

(Internet Of Things)

Guru Nanak Institutions Technical Campus

Telangana, India

 akashparepalli@gmail.com
Challa Akhil

Computer Science and Engineering

(Internet Of Things)

Guru Nanak Institutions Technical Campus

Telangana, India

Challa.akhil243@gmail.com
K . Hrisheek Raj

Computer Science and Engineering

(Internet Of Things)

Guru Nanak Institutions Technical Campus

Telangana, India

Saikarna234@gmail.com

ABSTRACT---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.

 KEYWORDS--- OpenCV2 Algorithm, OCR (Optical Character Recognition system), Automatic license plate recognition (ALPR), BINARIZATION, Gray threshold (GT), EDGE DETECTION, NUMBER PLATE LOCALIZATION, DESKEWING, SPYDER3.

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