A Method of Parking Space Detection Based on Image Segmentation and LBP

This paper proposes a novel parking spaces detection algorithm which is based on image segmentation and local binary pattern. The vehicles are usually contains a lot of compositions, while the vacant parking spaces´ composition is relatively small. According to this characteristic, we segment the parking image. To judge whether each parking area has a large number of small split or not, can achieve the detection of the parking stalls. In this paper, we improve the Mean Shift algorithm and achieve the accurate segmentation result. This proposed method was tested on indoor and outdoor parking lots. The result confirmed the efficiency of the proposed method, with the detection rate being over 97%. But, this method fails to detect non-vehicle objects and when the Vehicle color and ground color is very similar. So we the introduce the texture features, use LBP (local binary pattern) to extract the parking texture feature. Using the complementary between features and ultimately to achieve accurate detection.