TY - GEN
T1 - Receptive field based image modeling method for interactive segmentation
AU - Yang, Bin
AU - Zhao, Qi Yang
AU - Zhang, Rui
AU - Yin, Bao Lin
PY - 2009
Y1 - 2009
N2 - In current interactive segmentation algorithms, image models are constructed and simplified to be independent of spatial features of images. This conflicts with receptive field hypothesis of human vision systems, and causes over-segmentation and under-segmentation. Based on receptive field hypothesis, the paper establishes an image modeling method in which spatial distances are taken into account, and a conservative factor is introduced into the image energy function to improve the segmentation veracity. It is shown by experiments that the method is more accurate than its counterparts.
AB - In current interactive segmentation algorithms, image models are constructed and simplified to be independent of spatial features of images. This conflicts with receptive field hypothesis of human vision systems, and causes over-segmentation and under-segmentation. Based on receptive field hypothesis, the paper establishes an image modeling method in which spatial distances are taken into account, and a conservative factor is introduced into the image energy function to improve the segmentation veracity. It is shown by experiments that the method is more accurate than its counterparts.
UR - https://www.scopus.com/pages/publications/73849134390
U2 - 10.1109/CISP.2009.5303490
DO - 10.1109/CISP.2009.5303490
M3 - 会议稿件
AN - SCOPUS:73849134390
SN - 9781424441310
T3 - Proceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
BT - Proceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
T2 - 2009 2nd International Congress on Image and Signal Processing, CISP'09
Y2 - 17 October 2009 through 19 October 2009
ER -