A Comparative evaluation of foreground / background segmentation algorithms

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Date

2012

Author

Pakyürek, Muhammet

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Foreground Background segmentation is a process which separates the stationary objects from the moving objects on the scene. It plays significant role in computer vision applications. In this study, several background foreground segmentation algorithms are analyzed by changing their critical parameters individually to see the sensitivity of the algorithms to some difficulties in background segmentation applications. These difficulties are illumination level, view angles of camera, noise level, and range of the objects. This study is mainly comprised of two parts. In the first part, some well-known algorithms based on pixel difference, probability, and codebook are explained and implemented by providing implementation details. The second part includes the evaluation of the performances of the algorithms which is based on the comparison v between the foreground background regions indicated by the algorithms and ground truth. Therefore, some metrics including precision, recall and f-measures are defined at first. Then, the data set videos having different scenarios are run for each algorithm to compare the performances. Finally, the performances of each algorithm along with optimal values of their parameters are given based on f measure.

Subject Keywords

Computer vision., Artificial intelligence., Image processing, Digital image correlation., Computer algorithms.

URI

http://etd.lib.metu.edu.tr/upload/12614666/index.pdf
https://hdl.handle.net/11511/22122

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. Pakyürek, “A Comparative evaluation of foreground / background segmentation algorithms,” M.S. - Master of Science, Middle East Technical University, 2012.