Volume XLII-2/W12
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 173-177, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-173-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W12, 173-177, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W12-173-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 May 2019

09 May 2019

MOVING OBJECT DETECTION USING SPATIAL CORRELATION IN LAB COLOUR SPACE

A. Roshan and Y. Zhang A. Roshan and Y. Zhang
  • Department of Geodesy and Geomatics Engineering, University of New Brunswick Fredericton, New Brunswick, Canada

Keywords: Moving Object Detection, Background Subtraction, Lab Colour Space, Spatial Correlation

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.