Elastically Adaptive Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation Based on the Integration of Pixel Affinity and Deformable Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multi-feature edge detection with the feature of local image complexity
ISCGAV'05 Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Feature space and metric measures for fusing multisensor images
International Journal of Remote Sensing
A Novel Algorithm for Automatic Brain Structure Segmentation from MRI
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
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Precise segmentation of underlying objects in an image is very important especially for biomedical image analysis. We present an integrated approach for boundary finding using region and curvature information along with the gradient. Unlike the previous methods, where smoothing is enforced by penalizing curvature, here the grey level curvature is used as an extra source of information. However, information fusion may not be useful unless used properly. To address that, we present results that highlight the pros and cons of using the various sources of information and indicate when one should get precedence over the others.