Morphological Image Processing for Python
Discover the power of Morphological Image Processing with the SDC Morphology Toolbox for Python
(Latest version is 1.6 March 31, 2008).
The SDC Morphology Toolbox for Python is a powerful collection of latest
gray-scale morphological tools that can be applied to image segmentation,
non-linear filtering, pattern recognition and image analysis.
Download a free fully functional
30-day evaluation version of the toolbox.
Version 1.6 news
- Very fast connected components labeling (Union-find algorithm)
- MaxTree-based connected operators
- Attribute openings: Area, Volume, Height, Bounding-Box
- Regional maxima dynamics
- Marker propagation
- Most operators work for binary and gray-scale images
- Image (2D arrays), volume or sequence processing (3D arrays) and signal processing (1D arrays)
- Support for structuring elements in decomposed form (faster algorithms)
- Planar and non-planar structuring elements
- Images represented in byte, short and signed integer data types
- Fast queue-based algorithms for distance transform, watershed, morphological reconstruction, labeling, area-opening, etc.
- Fast binary operations using intrinsic 32 bit parallel operations available in 32 bit machines
Main classes of operators
- Gray-scale Dilation & Erosion
- Morphological Filters: opening, closing, alternating sequential filters
- Connected Operators: watershed, open and close by reconstruction, labeling, regional maxima and minima, alternating sequential filters by reconstruction, area opening, h-dome and h-basin
- Distance Transforms including geodesic
- Residues: gradient, contour, top-hat
- Hit-Miss: skeletonization, skiz
- Watershed: gray-scale from markers. Based on gradient or similarity