Moving and immovable object in video processing using intuitionistic fuzzy logic

Abandoned object discovery using tracking based approaches are often become unpredictable in complex surveillance videos due to noise, occlusions, lighting changes, and other factors. This proposed paper presents a new structure to strongly and proficiently detect abandoned objects based on background subtraction. In this proposed system, the background is modelled by Gaussian mixture. In order to hold complex situations, numerous enhancements are implemented for noise removal, rapid lighting transform adaptation, fragment reduction, and maintaining a stable update rate for video streams with different frame rates. In order to substantiate this proposed approach the object detection method using Intuitionistic logic based on block matching techniques has been used. The experimental results obtained were tested on benchmark video sequences. The obtained results are very promising in terms of robustness and effectiveness.