This paper proposes an image-based 3D object-model-based car detection algorithm. We first use a 3D car template to fit and rotate the detected image blob and recombine the image blob. We then detect the horizontal edge features of that image blob and project them to the vertical line to obtain the histogram of the edge features. Lastly, we use the support vector machine to train the car model and use it to recognize the objects in the fixed parking spaces and the moving objects in the parking lot. Experimental results show 98% recognition rate in the parking space and 88% for the verification of the moving objects.