## 1 Introduction  
The advancements of science and technology, coupled with the rapid improvement in the standard of living, have resulted in higher demand for intelligent vehicles. One such demand aspect of intelligent vehicles is the Automatic Parking System (APS). As a result of rapid developments in most cities around the world, parking spaces are becoming narrower, and parking a vehicle without the guidance of a third party is becoming quite problematic and takes too much time to accomplish even with a parking guide. However, with the rapid development of APS technology, this task will be accomplished with ease and with minimal time needed without a parking guide. This system uses sensors or cameras to assess the parking situation and automatically adjust the angle of the steering device to accomplish a successful parking process [1, 2].  
APS that use sensors like ultrasonic radar sensors to find parking spaces have the advantage of high-speed data processing and long detection distance, free from the influence of light. However, ultrasonic radar cannot distinguish the types of obstacles, and it is easy to misjudge when the ultrasonic radar scans low barriers or potholes on the ground [3, 4].  
In addition to the ultrasonic radar, the parking space can also be recognized by the use of camera vision. The advantage of the camera is that it can acquire a large amount of data about the surrounding environment and can detect inclined objects. However, it is greatly influenced by the surrounding environment, and the accuracy of the recognized obstacles on the ground is low in situations where the color of the obstacles is similar to the color of the ground. Additionally, monocular cameras cannot recognize the size of objects, and binocular cameras are more expensive and the algorithms more complex [5; 6; 7; 8].  
Another technology that APS uses for parking space recognition is the LiDAR sensing system. This technology was originally developed and used by the military. It detects the distance of the surrounding environment by launching a multi-beam pulsed laser rotating 360 degrees, and it can also draw a 3D map. However, as a result of the high cost of this technology, LiDAR with a low wire harness is used in vehicles, which comes with a decrease in resolution, making it susceptible to producing blind spots and resulting in safety concerns [9; 10; 11].  
The multi-sensor fusion technique for APS as proposed by many researchers is to overcome the above shortcomings of the other technologies. However, the high cost of this technology coupled with the fact that it has not sufficiently matured hinder its adoption [12; 13; 14]. Additionally, the theory of parking space recognition rarely considers the general situation of the obstacles in the parking space, which can lead to inaccurate obstacle identification [15].  
In order to solve the above challenges, a new parking space recognition scheme is proposed in this paper. A laser transmitter is added to the vision sensor system. A chessboard effect laser grid is presented on the ground by a laser emitter mounted on the vehicle, and the shape of the laser grid will change when there are obstacles on the ground. After these changes are captured by the camera, through image processing, the laser mesh region is taken as the region of interest. This method can effectively identify parking spaces and obstacles in parking spaces and significantly improve the recognition rate of sufficient parking spaces.