Identification of poor visibility conditions in urban settings

Street lighting provides a number of benefits. It can be used to promote security in urban areas and to increase the quality of life. Street light also provides safety for drivers, riders and pedestrians. In this paper, a machine vision system is proposed to identify the variations in the lighting of the road. The objective of this paper is to monitor the variations in the average intensity of the light on the road. The video data was acquired of night time road conditions and frames were extracted from video data. Several image processing techniques such as adaptive histogram equalization and morphological operations were performed on the images and the average intensity of the street light on each frame was computed. In this study, the variation in average intensity values are found to be useful in identifying the low lighting conditions on the road. The preliminary results clearly indicate the variations in the light falling on the road during night time.