Introduction to mathematical morphology
Computer Vision, Graphics, and Image Processing
Computer Vision, Graphics, and Image Processing
Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Range image analysis by using morphological signal decomposition
Pattern Recognition
An overview of morphological filtering
Circuits, Systems, and Signal Processing - Special issue: median and morphological filters
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Computer and Robot Vision
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Computer Vision and Image Understanding
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Image segmentations have been performed to identify the surface fragmentation of rock piles using 3D surface data, and quantified. The advantages for fragmentation measurement using image analysis are significant and include: quantifying image segmentation performance in isolation of the downstream processes of fragment classification and size distribution calculation, utilization of 3D data to overcome various limitations of photographic-based image analysis, and the capacity to use 3D fragment data to eliminate the misclassification of partially visible fragments as smaller entirely visible fragments. The segmentation results have been quantified by comparison with the 3D surface data of each individual rock fragment. Mathematical morphology and image segmentation algorithms have been extended from greyscale image-based definitions and applied to irregularly spaced 3D coordinate surface data. 3D coordinate surface data can now be morphologically processed directly in 3D, segmented, visualized, and directly compared to the actual surface fragmentation in order to quantify the results.