<![CDATA[Vehicle license plate detection is an essential component in modern parking management, particularly in institutional areas like PLN Mabar, which necessitate fast and accurate identification systems. This study focuses on applying the Canny Edge Detection method to accurately identify the edges of vehicle license plates under specific environmental settings, specifically lighting conditions of 100–115 lux and a camera height of 40 cm, evaluated across various threshold levels. Widely regarded as an optimal edge detection algorithm, the Canny Edge method offers significant advantages, including high-precision edge detection, robust noise interference minimization, and the generation of clear object boundaries. The research findings demonstrate that this method delivers excellent performance for vehicle detection in parking facilities when operating under controlled lighting and camera parameters. Specifically, the test results reveal that within a threshold range of 50 to 500, the system achieves a flawless 100% detection accuracy. This highlights the method's effectiveness in capturing crucial object edges under the tested conditions. Conversely, increasing the threshold beyond 500 leads to a gradual decline in system accuracy, dropping to 20% at a threshold of 900–1000. This decline indicates that excessively high threshold values cause the system to discard vital contours necessary for accurate detection. Ultimately, the system successfully detects license plate edges with a high success rate and stable processing times, proving its viability for practical implementation within the vehicle identification system at the PLN Mabar parking area.]]>
