A comparative study on mixture of Gaussians for object segmentation
Khatoon et al. · International Journal of ADVANCED AND APPLIED SCIENCES · 2017
Segmentation is the fundamental step in most of digital image processing and computer vision based applications for feature extraction.The purpose of segmentation is to partition an image into foreground and background.Numerous segmentation algorithms have been proposed for the last four decades ranging from degraded images; high and low contrast images, indoor video, outdoor videos, videos with static background and dynamic backgrounds.This paper presents evaluation and comparison of segmentation techniques used for real-time moving objects through static and adaptive number of Gaussians.The techniques are tested for both indoor and outdoor scenes.The comparison is presented on the basis of qualitative results and computational complexities.