An improved method of RHT to localize circle applied in Intelligent Transportation System

Intelligent Transportation System (ITS) is an application of modern information technology in the field of traffic that has attracted worldwide attention. Seat belt recognition is a relatively new orientation in ITS. In order to correctly identify the seat belt, under the premise of localized vehicle window, this paper explores to extract the centerline of the steering wheel as the feature, which provides reference for the localization of seat belt. But it is very difficult to find accurate location of the steering wheel’ centerline using luminance or color, because of the fuzzy image of vehicle window which has been obtained in a random environment. This paper explores to carry out canny edge detection, and then to use Randomized Hough Transform (RHT) to find the centerline of the steering wheel. However, RHT has a great of computation and memory consumption, which has prohibited its wider use from a large extent. This paper proposes a novel method called ‘Local Randomized Hough Transportation (LRHT)’. Experimental result shows that not only complexity but also efficiency has been greatly improved