Peer-Reviewed Journal Details
Mandatory Fields
Corcoran, P;Winstanley, A;Mooney, P
2011
November
Machine Vision and Applications
Complementary texture and intensity gradient estimation and fusion for watershed segmentation
Published
3 ()
Optional Fields
IMAGE SEGMENTATION ANISOTROPIC DIFFUSION EDGE-DETECTION CLASSIFICATION BOUNDARIES COLOR
22
1027
1045
In this paper, we identify two current challenges associated with watershed segmentation algorithms which attempt to fuse the visual cues of texture and intensity. The first challenge is that most existing techniques use a competing gradient set which does not allow boundaries to be defined in terms of both visual cues. The second challenge is that these techniques fail to account for the spatial uncertainty inherent in texture gradients. We present a watershed segmentation algorithm which provides a suitable solution to both these challenges and minimises the spatial uncertainty in boundary localisation. This is achieved by a novel fusion algorithm which uses morphological dilation to integrate intensity and texture gradients. A quantitative and qualitative evaluation of results is provided demonstrating that our algorithm outperforms three existing watershed algorithms.
NEW YORK
0932-8092
10.1007/s00138-010-0310-z
Grant Details