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Computer Sciences

Series

1999

Image segmentation

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Full-Text Articles in Physical Sciences and Mathematics

Toboggan-Based Intelligent Scissors With A Four-Parameter Edge Model, William A. Barrett, Eric N. Mortensen Jun 1999

Toboggan-Based Intelligent Scissors With A Four-Parameter Edge Model, William A. Barrett, Eric N. Mortensen

Faculty Publications

Intelligent Scissors is an interactive image segmentation tool that allows a user to select piece-wise globally optimal contour segments that correspond to a desired object boundary. We present a new and faster method of computing the optimal path by over-segmenting the image using tobogganing and then imposing a weighted planar graph on top of the resulting region boundaries. The resulting region-based graph is many times smaller than the previous pixel-based graph, thus providing faster graph searches and immediate user interaction. Further, tobogganing provides an new systematic and predictable framework for computing edge model parameters, allowing subpixel localization as well as …

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Segmentation Of Satellite Imagery Of Natural Scenes Using Data Mining, Leen-Kiat Soh, Costas Tsatsoulis Mar 1999

Segmentation Of Satellite Imagery Of Natural Scenes Using Data Mining, Leen-Kiat Soh, Costas Tsatsoulis

School of Computing: Faculty Publications

In this paper, we describe a segmentation technique that integrates traditional image processing algorithms with techniques adapted from knowledge discovery in databases (KDD) and data mining to analyze and segment unstructured satellite images of natural scenes. We have divided our segmentation task into three major steps. First, an initial segmentation is achieved using dynamic local thresholding, producing a set of regions. Then, spectral, spatial, and textural features for each region are generated from the thresholded image. Finally, given these features as attributes, an unsupervised machine learning methodology called conceptual clustering is used to cluster the regions found in the image …

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