Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated separation of touching grains in digital images of thin sections
Computers & Geosciences
Modified curvature motion for image smoothing and enhancement
IEEE Transactions on Image Processing
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This paper illustrates an interactive approach to digital characterization of granulated materials, based on mathematical morphology, digital topology and non-linear differential equations. The digital characterization is achieved using a three-step sequential process, namely: denoising, interactive segmentation and quantification, with emphasis in the interactive segmentation step, since it has significant impact on the characterization results. Denoising is used to extract foreground and background markers. Image segmentation results from an anisotropic region-growing and merging process based on immersion simulation. Region-growing evolves as a fully automated process, initiated at local image minima, while merging requires manual insertion of one single marker per region-of-interest. Non-significant regions are merged according to a hierarchy established by a set of markers and merging rules, which represent a robust solution to the over-segmentation problem inherent to immersion simulation algorithms. The sensitivity of the segmentation algorithm to local intensity variations allows the detection of the edges with high accuracy. Quantification is achieved using a suitable stereometric method, which computes the three-dimensional size distribution from the two-dimensional size distribution observed on the image. It is shown that this interactive approach represents a viable solution to digital characterization of granulated materials.