Morphological operations in image processing and analysis

Morphological operations applied in image processing and analysis are becoming increasingly important in today\u27s technology. Morphological operations which are based on set theory, can extract object features by suitable shape (structuring elements). Morphological filters are combinations of morphological operations that transform an image into a quantitative description of its geometrical structure which based on structuring elements. Important applications of morphological operations are shape description, shape recognition, nonlinear filtering, industrial parts inspection, and medical image processing. In this dissertation, basic morphological operations are reviewed, algorithms and theorems are presented for solving problems in distance transformation, skeletonization, recognition, and nonlinear filtering. A skeletonization algorithm using the maxima-tracking method is introduced to generate a connected skeleton. A modified algorithm is proposed to eliminate non-significant short branches. The back propagation morphology is introduced to reach the roots of morphological filters in only two-scan. The definitions and properties of back propagation morphology are discussed. The two-scan distance transformation is proposed to illustrate the advantage of this new definition. G-spectrum (geometric spectrum) which based upon the cardinality of a set of non-overlapping segments in an image using morphological operations is presented to be a useful tool not only for shape description but also for shape recognition. The G-spectrum is proven to be translation-, rotation-, and scaling-invariant. The shape likeliness based on G-spectrum is defined as a measurement in shape recognition. Experimental results are also illustrated. Soft morphological operations which are found to be less sensitive to additive noise and to small variations are the combinations of order statistic and morphological operations. Soft morphological operations commute with thresholding and obey threshold superposition. This threshold decomposition property allows gray-scale signals to be decomposed into binary signals which can be processed by only logic gates in parallel and then binary results can be combined to produce the equivalent output. Thus the implementation and analysis of function-processing soft morphological operations can be done by focusing only on the case of sets which not only are much easier to deal with because their definitions involve only counting the points instead of sorting numbers, but also allow logic gates implementation and parallel pipelined architecture leading to real-time implementation. In general, soft opening and closing are not idempotent operations, but under some constraints the soft opening and closing can be idempotent and the proof is given. The idempotence property gives us the idea of how to choose the structuring element sets and the value of index such that the soft morphological filters will reach the root signals without iterations. Finally, summary and future research of this dissertation are provided

Quantitative analysis with electron energy-loss: spectroscopic imaging and its application in pathology

After the invention of the transmission electron microscope (TEM) in 1931 by Ruska and Knoll, it took about 20 years to develop the inslmment into a tool for ultrastructural research. In material science this led to the ability to visualize and investigate atomic arrangements through the imaging of columns of atoms in a lattice or by electron diffraction. In biology the instrument enabled the visualization of cell structures at an unsurpassed level of detail. New cell structures, cells and organisms were depicted and more knowledge was gained about the complex ultrastructural morphology of the cell. Novel preparation procedures for fixation, cytochemical staining and labelling, embedding and the llse of ultramicrotomy and cryo-techniques increased the investigative capabilities of the TEM in the direction of cell functioning. In physics, right from the beginning, it was recognized that the interaction of electrons irradiating a specimen can be used not only for visualization but also gives the opportunity to investigate the chemical nature of the irradiated matter. This opened the way to the analytical use of the TEM and many instruments were subsequently equipped with highly specialized detectors for each of the analytical possibilities. In this way true microanalytical laboratories were created. Two main types of TEMs have been developed: the scanning transmission electron microscope (STEM) and the conventional transmission electron microscope (CTEM)