@article{(Open Science Index):https://publications.waset.org/pdf/13811,
	  title     = {Performance Evaluation of ROI Extraction Models from Stationary Images},
	  author    = {K.V. Sridhar and  Varun Gunnala and  K.S.R Krishna Prasad},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper three basic approaches and different
methods under each of them for extracting region of interest (ROI)
from stationary images are explored. The results obtained for each of
the proposed methods are shown, and it is demonstrated where each
method outperforms the other. Two main problems in ROI
extraction: the channel selection problem and the saliency reversal
problem are discussed and how best these two are addressed by
various methods is also seen. The basic approaches are 1) Saliency
based approach 2) Wavelet based approach 3) Clustering based
approach. The saliency approach performs well on images containing
objects of high saturation and brightness. The wavelet based
approach performs well on natural scene images that contain regions
of distinct textures. The mean shift clustering approach partitions the
image into regions according to the density distribution of pixel
intensities. The experimental results of various methodologies show
that each technique performs at different acceptable levels for
various types of images.},
	    journal   = {International Journal of Electronics and Communication Engineering},
	  volume    = {4},
	  number    = {12},
	  year      = {2010},
	  pages     = {1845 - 1853},
	  ee        = {https://publications.waset.org/pdf/13811},
	  url   	= {https://publications.waset.org/vol/48},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 48, 2010},
	}