Moving Object Detection Using Optical Flow and Fuzzy Algorithm

Ajay Suri, Sudhir Kumar Sharma and Dileep Kumar Yadav

The moving object detection is vast and complex domain of computer vision many algorithms and methodologies has been contemplated and implemented and many are in ongoing process. The static or dynamic object tracking has been revolutionized the surveillance and tracking system. This paper focuses on hybrid methodologies which conspire conventional algorithms along with proposed commuted concept for moving object tracking .The paper has proposed a collaborative holistic approach along with recent work pros and cons in related field .Fuzzy c mean cluster approach has been applied along with optical flow to reduce the classification error. Dynamic threshold & bounding box approach has been contemplated in the work to detect the moving object with dynamic parameters .In order to get better accuracy and reduce the complexity the generated output has been gone through with morphological operation in order to detect exactly the framed object in moving position .Primarily it has been analyzed existing work and our aim is to reduce classification error reduce mixing of data pixels like in existing work and finally to get better accuracy by combining the dimensions of algorithms.

Volume 11 | 11-Special Issue

Pages: 840-847

DOI: 10.5373/JARDCS/V11SP11/20193105