Title :
A local histogram based Chan-Vese model for segmentation
Author :
Zhimei Zhang; Junyu Dong; Kun Liu; Yuzhong Shen
Author_Institution :
College of Information Science and Engineering, Ocean University of China, Qingdao, China
Abstract :
The Chan-Vese model is a successful Variational segmentation model for piecewise constant and smooth images. However, it is failed to detect tigers or leopards in an image. In this paper, we propose a modified model that segments tiger into a whole object. Our energy functional uses an improved fitting term based on local histogram and the energy minimizing is therefore looking for homogeneous histograms to distinguish objects. We present a numerical algorithm to compute the corresponding partial differential equation. The proposed model yields excellent performance on synthetic images and images from the Berkeley segmentation data set 500.
Keywords :
"Histograms","Image segmentation","Computational modeling","Active contours","Fitting","Level set","Mathematical model"
Conference_Titel :
Natural Computation (ICNC), 2015 11th International Conference on
Electronic_ISBN :
2157-9563
DOI :
10.1109/ICNC.2015.7378058