Title :
Unsupervised foreground-background segmentation using growing self organizing map in noisy backgrounds
Author :
Ghasemi, Afsane ; Safabakhsh, Reza
Author_Institution :
Dept. of Comput. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
Segmentation of moving objects in an image sequence is one of the most fundamental and crucial steps in visual surveillance applications. This paper proposes a novel and efficient method for detecting moving objects in a noisy background by using a growing self organizing map to construct the codebook. The segmentation process distinguishes between those parts of the objects which move on static and dynamic background spaces such as roads and waving trees, respectively. The advantage of the proposed method is creating a small codebook based on the input pattern to model the background which results in less computational complexity and increases the speed of segmentation. We compare the proposed method with three other background subtraction algorithms and show that the proposed method has a higher precision and detection rate in comparison with other methods.
Keywords :
image denoising; image motion analysis; image segmentation; image sequences; object detection; self-organising feature maps; video surveillance; codebook; growing selforganizing map; image sequence; moving object detection; moving object segmentation; noisy background; unsupervised foreground-background segmentation; visual surveillance application; Adaptation model; Computational modeling; Image color analysis; Neurons; Pixel; Quantization; Training; codebook; mixture of Gaussians; motion analysis; segmentation; self organizing map;
Conference_Titel :
Computer Research and Development (ICCRD), 2011 3rd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-839-6
DOI :
10.1109/ICCRD.2011.5764031