Introduction:
Moving object detection from videos is among the most difficult task in different areas of
computer vision applications. Among the traditional object detection methods, researchers conclude that Background
Subtraction method carried out better in aspects of execution time and output quality.
Mehtod:
Visual background extractor is a renowned algorithm in Background Subtraction method for detecting moving
object in various applications. In the recent years, lots of work has been carried out to improve the existing Visual
Background extractor algorithm.
Result:
After investigating many state of art techniques and finding out the research gaps, this paper presents an improved
background subtraction technique based on morphological operation and 2D median filter for detecting moving object
which reduces the noise in the output video and also enhances its accuracy at a very limited additional cost. Experimental
results in several benchmark datasets confirmed the superiority of the proposed method over the state-of-the-art object
detection methods.
Conclusion:
In this article, a method has been proposed for moving object detection where the quality of the output object
is enhanced and good accuracy is achieved. This method provide with accurate experimental results, which helps in
efficient object detection. The proposed technique also deals with Visual Background extractor Algorithm along with the
Image Enhancement Procedure like Morphological and 2-D Filtering at a limited additional cost
Discussion:
This article worked on certain specific field, like noise reduction and image enhancement of output images of
the existing ViBe Algorithm. The technique proposed in this article will be beneficial for various computer vision
applications like video surveillance, road condition monitoring, airport safety, human activity analysis, monitoring marine
border for security purpose etc.
Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
