IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Region Growing and Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new approach to combining region growing and edge detection
Pattern Recognition Letters
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation and comparison of different segmentation algorithms
Pattern Recognition Letters
Computer and Robot Vision
Image Segmentation by Unifying Region and Boundary Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Integration of Image Segmentation Maps using Region and Edge Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quantitative methods of evaluating image segmentation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Concurrent Region Growing Algorithm Guided by Circumscribed Contours
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
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An unsupervised approach to image segmentation which fuses different sources of information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: an appropriated placement, the control of decision criterion, and the results refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method.