Master'sOpen Access

Vehicle license plate recognition system based on artificial intelligence

Is this your thesis?

This record came from a bulk archive import. If it’s yours, link it to your profile.

2022
0 views
0 downloads

Abstract (EN)

Artificial intelligence is to computers or machines to bring the skills of thinking, making sense, making decisions, learning and producing solutions, which are unique to human intelligence. Vehicle license plate recognition systems are systems that are generally used for provide control and security. These systems are created using methods such as artificial intelligence, machine learning, artificial neural networks, deep learning, image processing. The purpose of this study recognize the license plates in campus by using artificial intelligence and image processing techniques. These system made is an application developed for foreign and domestic plates in rectangular size. Vehicle license plate recognition system created consists of 3 main stages. In the first stage, which is the detection of the license plate region, gray level transformation, bilateral filtering, canny filtering and contour processes were applied to the vehicle images. For cutting stage of plate region was applied masking method. The last stage is the recognition of license plate characters. The characters were transformed into text by using the pytesseract algorithm. For the creation of the system, Raspberry Pi 4 single board computer was used as hardware and Python programming language was used as software. The first two stage of the system were found to be 100% successful and the third stage 91.82% successful. The system was generally successful and the results of each stage were explained with images.

Author

Aslı Göde

How to Cite

Aslı Göde (Master Thesis). Vehicle license plate recognition system based on artificial intelligence, 2022, Osmaniye Korkut Ata University.

License

Tüm Hakları Saklıdır

This work is shared under the specified license terms.

More theses from Osmaniye Korkut Ata University