Abstract
Abstract. Background subtraction-based techniques of moving object detection are very common in computer vision programs. Each technique of background subtraction employs image thresholding algorithms. Different thresholding methods generate varying threshold values that provide dissimilar moving object detection results. A majority of background subtraction techniques use grey images which reduce the computational cost but statistics-based image thresholding methods do not consider the spatial distribution of pixels. In this study, authors have developed a background subtraction technique using Lab colour space and used spatial correlations for image thresholding. Four thresholding methods using spatial correlation are developed by computing the difference between opposite colour pairs of background and foreground frames. Out of 9 indoor and outdoor scenes, the object is detected successfully in 7 scenes whereas existing background subtraction technique using grey images with commonly used thresholding methods detected moving objects in 1–5 scenes. Shape and boundaries of detected objects are also better defined using the developed technique.
Highlights
A moving object is extracted from video frames using moving object detection techniques
Moving object detection results are affected by the image threshold value used in extracting the moving object from a camera scene
Different image thresholding techniques give different threshold values which result in the detection of moving objects at various levels
Summary
A moving object is extracted from video frames using moving object detection techniques. Backgroundbased techniques use static background and detect the moving object by processing it with the incoming frame (Piccardi, 2004). Image thresholding is an integral part of moving object detection as it is used with every technique to extract moving object out of noisy frames (McIvor, 2000; Sezgin & Sankur, 2004). Different methods provide different threshold values which result into varying outputs for moving object detection. This research paper is focused on the improvement of a background subtraction technique by incorporating colour bands of opposite colour pairs and introducing image thresholding using spatial segmentation. Output from grey image based moving object detection technique using existing automatic image thresholding is compared with results from Lab colour space background subtraction using spatial correlation based automatic image thresholding
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