Title : ( Novel Image Segmentation Using Gaussian Mixture Models -Application to Plant Phenotypic Analysis )
Authors: Jinhai Cai , Mahmood Reza Golzarian , Stan Miklavcic ,
Full TextAbstract
A novel algorithm is proposed for background estimation using statistical pattern recognition. Usually the segmentation of objects in images is achieved by identifying homogeneous regions in individual images or by finding motions of objects in videos. In this paper, we combine the advantages of these approaches for the estimation of background using only two images. The proposed algorithm uses the difference between images to obtain initial estimation of background and then to refine the estimation using statistical pattern recognition. Experimental results have shown that the proposed algorithm can achieve promising performance in terms of accuracy and speed.
Keywords
background estimation; object segmentation; Gaussian mixture models; statistical pattern recognition
@inproceedings{paperid:1039119,
author = {Jinhai Cai and Golzarian, Mahmood Reza and Stan Miklavcic},
title = {Novel Image Segmentation Using Gaussian Mixture Models -Application to Plant Phenotypic Analysis},
booktitle = {(3rd International Conference on Signal Acquisition and Processing (ICSAP 2011},
year = {2011},
location = {سنگاپور},
keywords = {background estimation; object segmentation; Gaussian mixture models; statistical pattern recognition},
}
%0 Conference Proceedings
%T Novel Image Segmentation Using Gaussian Mixture Models -Application to Plant Phenotypic Analysis
%A Jinhai Cai
%A Golzarian, Mahmood Reza
%A Stan Miklavcic
%J (3rd International Conference on Signal Acquisition and Processing (ICSAP 2011
%D 2011
