Obstacle Detection from Still Images using Improved Background Subtraction Method

Background/Objectives: We propose an approach that aims at improving the current method of obstacle detection so as to improve efficiency, detection rate and running time. Methods/Statistical Analysis: Background subtraction is a technique used in obstacle detection to find out the area of hindrances for traversal or navigation. In this technique two consecutive frame of video is taken for differencing and resultant giving the area in which obstacle is identified. Findings: The current technique has some limitations working under high intensity and change of illumination. We propose a hybrid approach which include merging of gamma correction with background subtraction. This method reduces the level of illumination and works well at different weather conditions. Our proposed method is useful in detection of area of changing objects and would be useful in video surveillance applications.