Identification of Parking Lot Status Using Circle Blob Detection

Information on the availability of parking spaces, especially in large parking areas, is needed by parking users. This information will help users in terms of saving search time, effort, and fuel (money). Currently, parking space detection methods are divided into image detection and non-image detection methods. Non-image detection is not completely good, even some of its implementations require demolition of roads or buildings. In addition, the maintenance required for non-image detection can be more expensive, so the image detection method was chosen in this study. The system is designed by first converting the image into the HSV color space. The conversion image is then given the CLAHE process on channel V of HSV. The next step is to transform the image dimensions with perspective transformation in the area which is the parking lot slots. The transformed image covers the parking slots that will be detected. Then, from the transformation image, the status of each parking lot slot is detected by utilizing the auxiliary circle in each slot. The results of this process are then shown as the availability information for parking space users. The results of the identification trial of this system showed a great success rate of 99.28%.