Kumaran, Vignes (2018) Automatic Number Plate Recognition By Using Matlab. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted)
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Abstract
Usually, surveillance system is used for security purposes and monitoring systems. This surveillance system is also used for home security, traffic monitoring and at ATM security. Human activity detection and tracking has increased in usage due to decreasing cost of video surveillance camera. Moreover, automated systems had been designed for numerous detection tasks, but the task of detecting illegally parked vehicles has been left for human operators of surveillance system. Automatic Number Plate Recognition (ANPR) system is an image processing technology that identifies the vehicle by tracking its number plate without direct human involvement and it is widely used in Intelligent Transportation System (ITS). In this project, extraction and recognition of vehicle number plate from an image is done by using MATLAB. The image of the vehicle is captured by using camera and the image is sent to MATLAB by using Raspberry Pi 3. Besides, this project presents an approach based on morphological operation and Sobel edge detection method. Then, the approach is simplified to segmentation of all the characters in the number plate by using bounding box method. The segmented character on the plate has been extracted and recognized by using template images of alphanumeric character. Furthermore, new algorithm in MATLAB has been used to extract the vehicle number plate in various luminance condition. The system able to detect vehicle number plate at 95% success rate.
| Item Type: | Monograph (Project Report) |
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| Subjects: | T Technology T Technology > TK Electrical Engineering. Electronics. Nuclear Engineering |
| Divisions: | Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering) > Monograph |
| Depositing User: | Mr Engku Shahidil Engku Ab Rahman |
| Date Deposited: | 06 Jul 2022 07:18 |
| Last Modified: | 06 Jul 2022 07:18 |
| URI: | http://eprints.usm.my/id/eprint/53307 |
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