Title :
Interactive Image Segmentation via Adaptive Weighted Distances
Author :
Protiere, Alexis ; Sapiro, Guillermo
Author_Institution :
Ecole Polytechnique, Paris
fDate :
4/1/2007 12:00:00 AM
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;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2007.891796