Abstract:

In the process of automatic parking， the parking space image taken by the fisheye camera on the vehicle is dark due to the low light environment and the parking space information is fuzzy， which makes it impossible to detect the parking space. In this paper， an image enhancement algorithm of parking space line is designed， which combines limited contrast adaptive histogram equalization （CLAHE） and improved single-scale Retinex （SSR）. Firstly， the image distortion of fisheye camera is rectified and converted to generate a bird's eye view. Then， the bird's-eye view is preprocessed by the CLAHE algorithm， which optimizes the calculation process of mapping function. Then， a single-scale Retinex algorithm based on iterative block filtering to estimate incident components is used to enhance the image. After filtering and morphological processing， the image is grayed based on the bright channel prior， and the final enhancement result is obtained. In this paper， multiple sets of videos of actual parking process captured by one-sided fisheye camera in low-light scenes are collected， and single-frame image in the process of passing through parking space is intercepted as data input， and a basic parking space detection algorithm is used to detect the enhancement result. The experiment shows that the number of video frames that can detect parking spaces after enhancement exceeds 90%， with only 38 ms of the processing time of single-frame image enhancement algorithm.

Key words: automatic parking, low illumination, parking space line enhancement, parking space detection