A New Approach of Moving Object Detection Using Background Subtraction Method

Moving object detection has introduced a new challenging horizon in the era of image processing. The main challenge to detect moving objects in all environments because of the complex background. This paper proposes a method that detects a moving object more accurately in almost all the environments. Background subtraction is used in our proposed method for detecting moving objects where the Sauvola algorithm is used on a subtracted image for binary conversion. Median filtering and boundary labeling are used to increase the accuracy of moving object detection. Finally, a morphological operation is performed in our proposed method for detecting the moving object. We tested our proposed method on Wallflower datasets and compare the results of moving object detection on the basis of recall, precision and F-measure with other existing methods. Our proposed method attained successful results for detecting the moving object.