Underwater Video Processing for Detecting and Tracking Moving Object
Srividya M. S.1, Hemavathy R.2, Shobha G.3
1Srividya M. S., Student, Information Technology, G.H.Raisoni Institute of Engineering & Technology, Pune, India.
2Hemavathy R., Student, Information Technology, G.H. Raisoni Institute of Engineering & Technology, Pune, India.
3Shobha G., Student, Information Technology, G.H. Raisoni Institute of Engineering & Technology, Pune, India
Manuscript received on June 25, 2014. | Revised Manuscript received on July 03, 2014. | Manuscript published on July 05, 2014. | PP: 13-17 | Volume-4, Issue-3, July 2014. | Retrieval Number: C2268074314 /2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we present a vision system capable of analyzing underwater videos for detecting and tracking moving object. The video processing system consists of three subsystems, the video texture analysis, object detection and tracking modules. Moving object detection is based on adaptive Gaussian mixture model. The tracking was carried out by the application of the Kalman algorithm that enables the tracking of objects. Unlike existing method, our approach provides a reliable method inwhich the moving object is detected in unconstrained environments and under several scenarios (murky water, algae on camera lens, moving plants, low contrast, etc.). The proposed approach was tested with 20 underwater videos, achieving an overall accuracy as high as 85%
Keywords: Video Processing, Detection, Tracking, Gaussian Mixture Model, Kalman Filterin