Interactive Image Segmentation via Adaptive Weighted Distances

Author

Protiere, Alexis ; Sapiro, Guillermo

Author_Institution

Ecole Polytechnique, Paris

Volume

16

Issue

4

fYear

2007

fDate

4/1/2007 12:00:00 AM

Firstpage

1046

Lastpage

1057

Abstract

An interactive algorithm for soft segmentation of natural images is presented in this paper. The user first roughly scribbles different regions of interest, and from them, the whole image is automatically segmented. This soft segmentation is obtained via fast, linear complexity computation of weighted distances to the user-provided scribbles. The adaptive weights are obtained from a series of Gabor filters, and are automatically computed according to the ability of each single filter to discriminate between the selected regions of interest. We present the underlying framework and examples showing the capability of the algorithm to segment diverse images

Keywords

Gabor filters; computational complexity; image segmentation; Gabor filters; adaptive weighted distances; interactive image segmentation; linear complexity computation; user-provided scribbles; Adaptive filters; Clustering algorithms; Gabor filters; Image processing; Image segmentation; Labeling; Pixel; Robustness; Adaptive weights; distance functions; interactive segmentation; linear complexity; natural images; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2007.891796

Filename

4130436