Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
A Level Set Method for the Extraction of Roads from Multispectral Imagery
AIPR '02 Proceedings of the 31st Applied Image Pattern Recognition Workshop on From Color to Hyperspectral: Advancements in Spectral Imagery Exploitation
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bottom-Up Hierarchical Image Segmentation Using Region Competition and the Mumford-Shah Functional
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
IEEE Transactions on Image Processing
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The level set method provides a means of segmenting images. Fundamentally, the level set method for image segmentation is a search algorithm that determines where an evolving curve's boundary pixels - who are meant to encompass an image segment's perimeter - should be placed according to some criteria. A method has been devised that utilizes the Mumford-Shah functional as a means of establishing that criteria. It has been shown that this method for image segmentation has limitations that, while mentioned in the original research, were not quantified with examples. We present evidence of these limitations, discuss how they occurred and describe our preliminary attempts at overcoming them. We conclude by offering a direction where this research might lead. This work is part of an ongoing research project.