DGETMW: Motion Video Tracking Based on Memory Watershed Disc Gradient Expansion Template

Authors

Wei Wei, School of Electrical and Information Engineering, Anhui University of Science & Technology, Huainan 232001, China;
Kongping Wu, School of Electrical and Information Engineering, Anhui University of Science & Technology, Huainan 232001, China;
Laigong Guo, School of Electrical and Information Engineering, Anhui University of Science & Technology, Huainan 232001, China;
Qin Meng, School of Electrical and Information Engineering, Anhui University of Science & Technology, Huainan 232001, China;

Abstract

Abstract: In order to obtain ideal detection results of moving object, a new video moving object detection algorithm based on labeling watershed and detection algorithm and morphology were proposed. The image was pre-processed by diffusion model to eliminate noise interference on object detection, and the difference algorithm was used to extract outline of moving object.. Morphological operations were used to process the target outline, and marked watershed algorithm was used to segment moving object and performance was tested by simulation experiments. The simulation results show that the proposed algorithm can prevent over segmentation problems and accurately detect moving object from complex background, not only improve the detection accuracy but accelerate the speed of moving object detection.

Recommended Citation

Wei, Wei; Wu, Kongping; Guo, Laigong; and Meng, Qin (2020) "DGETMW: Motion Video Tracking Based on Memory Watershed Disc Gradient Expansion Template," Journal of System Simulation: Vol. 28: Iss. 2, Article 29.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss2/29

First Page

462

Revised Date

2015-07-26

DOI Link

https://doi.org/

Last Page

467

CLC

TP391

Recommended Citation

Wei Wei, Wu Kongping, Guo Laigong, Qin Meng. DGETMW: Motion Video Tracking Based on Memory Watershed Disc Gradient Expansion Template[J]. Journal of System Simulation, 2016, 28(2): 462-467.