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Accurately generating an alarm for a moving door is a precondition for tracking, recognizing and segmenting objects or
people entering or exiting the door. The challenge of generating an alarm when a door event occurs is difficult when
dealing with complex doors, moving cameras, objects moving or an obscured entrance of the door, together with the
presence of varying illumination conditions such as a door-way light being switched on. In this paper, we propose an
effective method of tracking the door motion using edge-map information contained within a localised region at the top
of the door. The region is located where the top edge of the door displaces every time the door is opened or closed. The
proposed algorithm uses the edge-map information to detect the moving corner in the small windowed area with the help
of a Harris corner detector. The moving corner detected in the selected region gives an exact coordinate of the door
corner in motion, thus helping in generating an alarm to signify that the door is being opened or closed. Additionally, due
to the prior selection of the small region, the proposed method nullifies the adverse effects mentioned above and helps
prevent different objects that move in front of the door affecting its efficient tracking. The proposed overall method also
generates an alarm to signify whether the door was displaced to provide entry or exit. To do this, an active contour
orientation is computed to estimate the direction of motion of objects in the door area when an event occurs. This
information is used to distinguish between objects and entities entering or exiting the door. A Hough transform is applied
on a specific region in the frame to detect a line, which is used to perform error correction to the selected windows. The
detected line coordinates are used to nullify the effects of a moving camera platform, thus improving the robustness of
the results. The developed algorithm has been tested on all the Door Zone video sequences contained with the United
Kingdom Home Office i-LIDs dataset, with promising results.
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