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Title |
Motion Detection based on multi frame video under Surveillance System |
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Author |
Brajesh Patel, Neelam Patel |
| Citation |
Vol. 12 No. 3 pp. 100-107 |
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Abstract |
In this paper a series of algorithm has been formed to track the feature of motion detection under surveillance system. In the proposed work a pixel variant plays a vital role in detection of moving object of a particular clip. If there is a little bit motion in a frame then it is detected very easily by calculating pixel variance. This algorithm detects the zero variation only when there is no motion in a real-time video sequence. It is simple and easier for motion detection in the fames of moving object having Avi file. In this work we enhanced the efficiency of moving object detection in a current pair of frame by implementing pixel base displacement algorithm in the frame of object as the current and previous. There are different levels at which tracking can be performed. At the highest level, the whole body is detected without paying attention to the details of the posture and limbs. At a lower level, the posture and limbs are tracked. At an even lower level, one or two parts of the body (such as hands) are tracked. Most of the existing algorithms for moving object detection assume that the illumination in a scene remains constant. Unfortunately, this assumption is not valid, especially in outdoor environment. To resolve the problem of our existing methods (Simple Differencing method and Shading Model Method), we introduced an improvement “illumination compensation coefficient Ki” that makes it work well even when there is a moving object detected in the scene. In this work we present a new, illumination independent method for moving object detection in outdoor environment. We also used median value of the observed region instead of mean value in calculating the variance in proposed method because the comparison is faster than addition and division. It is shown in experimental results, this method is superior to other techniques if the illumination is allowed to vary. This paper answered the crucial question regarding the detection of moving object and suggests the requirement of surveillances in the terms of security and in high tech world. Our selection criteria are directly based on the definition of Motion detection and tracking algorithms which explains the experimental performance of motion detection in a frame generated by real-time video & clips. This is usually analyzing the difference of two successive frames with the help of pixel variance. Software .net is used for the accomplishment of task. The purpose of surveillance is to provide more information of moving object by tracking its motion in multi frames at any work places as banking, cinema hall, shopping mall, offices and structural work. From the experimental data we can explain the change in pixel variant means that changes had occurred from the current frame to previous frame. |
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Keywords |
Pixel Variance, Threshold Value, Segmentation of Frames, Moving Object Detection, Surveillance System |
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