Intelligent parking guidance system of image recognition using HAAR cascade classifier / Abdul Rahman Mohamad Rom

• Main Author: Mohamad Rom, Abdul Rahman
• Format: Thesis
• Language: English
• Published: 2020
• Subjects: Electronic Computers. Computer Science; Remote sensing; Detectors. Sensors. Sensor networks
• Online Access: http://ir.uitm.edu.my/id/eprint/35661/1/35661.pdf; http://ir.uitm.edu.my/id/eprint/35661/

Being able to find and navigate the way to a suitable vacant parking space in today’s crowded urban landscape can be stressful and takes too much of time. As a solution, a Parking Guidance System (PGS) is needed to ease the burden of finding the vacant parking. In this technological world, there are a lot of familiar PGS such as sensors system or RFID. But, in this study the Parking Guidance System (PGS) used the image recognition approach which contain an added value to the system because the Parking Guidance System (PGS) is capable to capture the image of the parking. Thus, the user not only can view the data of the parking, but can re-assure the occupancy status of the parking by viewing the latest image of the parking. In term of object detection techniques, this system was implemented by using HAAR Cascade Classifier (HCC) which famously known of its capabilities to perform rapid detection. This project follows the Iterative methodology which famously known to produce a system with fast delivery. The functional and accuracy testing have been conducted for the purpose of the correctness of the system and also the accuracy of the model. The result of accuracy testing shows that this system is capable to accurately detecting the occupancy status of the parking at the rate of 97.14% under the condition of good lighting. Meanwhile, 100% of the system is functional as required in the functional requirement. The significance of this project is to ease the burden of the student in UiTM Jasin to find a vacant parking. This system can also store the data of the parking, which could be used for the future work, such as predicting the parking and also parking data visualization.