|Lecturer||B. S. Daya Sagar|
|Period||May 02, 2017 - May 05, 2017|
Course objectives and contents
For various phenomena related to varied phenomena, different types of data in functional and binary forms are available across spatial, spectral and temporal resolutions. To address the intertwined topics—like pattern retrieval, pattern analysis, spatial reasoning, and simulation and modelling for understanding spatiotemporal behaviours of such phenomena and processes that could be acquired through wide ranging mechanisms—various original algorithms and modelling techniques that are mainly based on mathematical morphology (originally founded by Matheron 1975, Serra 1982, 1988, and subsequent works by Soille 2003, Najman and Talbot 2010, Sagar 2013) are available.
This course presents fundamentals of mathematical morphology and scaling theories and their applications to address the aforementioned intertwined topics. The information that follows includes a brief syllabus on mathematical morphology and applications, tentative lecture titles, broad categorization of mathematical morphology, instructor's bio, and time-schedules of this one-week long course.
1) Introduction to mathematical morphology: Minkowski addition and Minkowski subtraction, Introduction to the Lattice Theory, Structuring element and its decomposition.
2) Fundamental morphological operators: Erosion, Dilation, Opening, Closing. Binary Vs Greyscale morphological operations.
3) Hit-or-miss transform, skeletons, morphological reconstructions, thinning, thickening: Hit-or-Misstransformation, Skeletonization, Coding of binary image via skeletonization, skeletonization by influence zones (SKIZ), weighted SKIZ, Medial Axis Transformation (MAT), skeletonization via Euclidean distance Transformation, Partial skeletons, Morphological shape decomposition (MSD), Morphological thinning, thickening, pruning, MSD Vs SKIZ.
4) Granulometry, classification, texture analysis: Binary and greyscale granulometries, pattern spectra analysis (shape-size spectrum), physical significance of granulometries, Linear granulometries, Rectangular ranulometries. Feature (shape-size-orientation) based classification of spatial fields and spatial objects.
5) Morphological Filtering and Segmentation: Multiscale morphological transformations, Top-Hat and Bottom-Hat transformations, Alternative Sequential filtering, Segmentation, Watershed segmentation, Connected operators for segmentation, hierarchical segmentation via watersheds, markers, hierarchical segmentation, geodesic active contours
6) Geodesic transformations and metrics: Geodesic morphology, Graph-based morphology, City-Block metric, Chess board metric, Euclidean metric, Geodesic distance (shortest paths), Dilation distance, Hausdorff dilation and erosion distances. Median set, weighted median set, quench stripe, morphological interpolation and extrapolations, Efficient implementation of morphological operators.
7) Applications of mathematical morphology
May 2, 2017 10:00-12:00, 14:00-16:30;
May 3, 2017 10:00-12:00, 14:00-16:30;
May 4, 2017 10:00-12:00, 14:00-16:30;
May 5, 2017 10:00-12:00, 14:00-16:30;
The lessons are in the "Garda" room (Povo 1)