A Study of Morphological Operators with Applications

The present work deals with the A study of morphological opertors with applications. Morphology is now a.necessary tool for engineers involved with imaging applications. Morphological operations have been viewed as filters the properties of which have been well studied (Heijmans, 1994). Another well-known class of non-linear filters is the class of rank order filters (Pitas and Venetsanopoulos, 1990). Soft morphological filters are a combination of morphological and weighted rank order filters (Koskinen, et al., 1991, Kuosmanen and Astola, 1995). They have been introduced to improve the behaviour of traditional morphological filters in noisy environments. The idea was to slightly relax the typical morphological definitions in such a way that a degree of robustness is achieved, while most of the desirable properties of typical morphological operations are maintained. Soft morphological filters are less sensitive to additive noise and to small variations in object shape than typical morphological filters. They can remove positive and negative impulse noise, preserving at the same time small details in images. Currently, Mathematical Morphology allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory of fuzzy sets.Fuzzy sets have proved to be strongly advantageous when representing in accuracies, not only regarding the spatial localization of objects in an image but also the membership of a certain pixel to a given class. Such inaccuracies are inherent to real images either because of the presence of indefinite limits between the structures or objects to be segmented within the image due to noisy acquisitions or directly because they are inherent to the image formation methods.

Segmentation of Brain Tissue from Magnetic Resonance Images

Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.

Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

Solvent-induced Morphology of the Binary Mixture of Diblock Copolymer in Thin Film: The Block Length and Composition Dependence of Morphology

A series of binary SB blend samples with various overall volume fraction of PS (Phi(PS)) and different discrete distribution of the block length (denoted as d(PS) or d(PB)) were prepared by mixing various asymmetric poly(styrene)-block-poly(butadiene) (SB) block copolymers with a symmetric SB block copolymer. The influences of the external solvent field, composition, and the block length distribution on the morphologies of the blends in the thin films were investigated by atomic force microscopy (AFM) and transmission electron microscopy (TEM). The experimental results revealed that after solvent annealing, the interface of the blend thin films depended mainly on the cooperative effects of the annealing solvent and the inherently interfacial curvature of the blends. Upon exposure to the saturated vapor of cyclohexane, which has preferential affinity for the PB block, a "threshold" of Phi(PS) (approximate 0.635-0.707) was found. Below such threshold, the influence of the annealing solvent played an important role on the interfacial curvature of the blend thin film.

Using Mathematical Morphology for Geometric Music Retrieval

The usual task in music information retrieval (MIR) is to find occurrences of a monophonic query pattern within a music database, which can contain both monophonic and polyphonic content. The so-called query-by-humming systems are a famous instance of content-based MIR. In such a system, the user's hummed query is converted into symbolic form to perform search operations in a similarly encoded database. The symbolic representation (e.g., textual, MIDI or vector data) is typically a quantized and simplified version of the sampled audio data, yielding to faster search algorithms and space requirements that can be met in real-life situations. In this thesis, we investigate geometric approaches to MIR. We first study some musicological properties often needed in MIR algorithms, and then give a literature review on traditional (e.g., string-matching-based) MIR algorithms and novel techniques based on geometry. We also introduce some concepts from digital image processing, namely the mathematical morphology, which we will use to develop and implement four algorithms for geometric music retrieval. The symbolic representation in the case of our algorithms is a binary 2-D image. We use various morphological pre- and post-processing operations on the query and the database images to perform template matching / pattern recognition for the images. The algorithms are basically extensions to classic image correlation and hit-or-miss transformation techniques used widely in template matching applications. They aim to be a future extension to the retrieval engine of C-BRAHMS, which is a research project of the Department of Computer Science at University of Helsinki.

Communication: Unusual dynamics of hybrid nanoparticles and their binary mixtures

We present the results on the evolution of microscopic dynamics of hybrid nanoparticles and their binary mixtures as a function of temperature and wave vector. We find unexpectedly a nonmonotonic dependence of the structural relaxation time of the nanoparticles as a function of the morphology. In binary mixtures of two of the largest nanoparticles studied, we observe re-entrant vitrification as a function of the volume fraction of the smaller nanoparticle, which is unusual for such high diameter ratio. Possible explanation for the observed behavior is provided. (C) 2010 American Institute of Physics. doi:10.1063/1.3495480]

Solvation dynamics of tryptophan in water-dimethyl sulfoxide binary mixture: In search of molecular origin of composition dependent multiple anomalies

Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.

Anomalous phase transitions in soft colloid-polymer binary mixtures

We have shown earlier [1] that these PGNPs resemble star polymers or spherical brushes in terms of their morphology in the melt. However, these particles show dynamics in melt which is quite different from other soft colloidal particles. Since most of the work on soft colloidal particles have been performed in solutions we have now explored the phase behavior of the PGNPs in good solvent using microscopic structural and dynamical measurements on binary mixtures of homopolymers and soft colloids consisting of polymer grafted nanoparticles. We observe anomalous structural and dynamical phase transitions of these binary mixtures, including appearance of spontaneous orientational alignment and logarithmic structural relaxations, as a function of added homopolymers of different molecular weights. Our experiments points to the possibility of exploiting the phase space in density and homopolymer size, of such hybrid systems, to create new materials with unique properties.

Logic-operated mathematical morphology and its optical implementation

A more powerful tool for binary image processing, i.e., logic-operated mathematical morphology (LOMM), is proposed. With LOMM the image and the structuring element (SE) are treated as binary logical variables, and the MULTIPLY between the image and the SE in correlation is replaced with 16 logical operations. A total of 12 LOMM operations are obtained. The optical implementation of LOMM is described. The application of LOMM and its experimental results are also presented. (C) 1999 Optical Society of America.

FUZZY SOLID SETS FOR MATHEMATICAL MORPHOLOGY AND OPTICAL IMPLEMENTATION

Fuzzy sets in the subject space are transformed to fuzzy solid sets in an increased object space on the basis of the development of the local umbra concept. Further, a counting transform is defined for reconstructing the fuzzy sets from the fuzzy solid sets, and the dilation and erosion operators in mathematical morphology are redefined in the fuzzy solid-set space. The algebraic structures of fuzzy solid sets can lead not only to fuzzy logic but also to arithmetic operations. Thus a fuzzy solid-set image algebra of two image transforms and five set operators is defined that can formulate binary and gray-scale morphological image-processing functions consisting of dilation, erosion, intersection, union, complement, addition, subtraction, and reflection in a unified form. A cellular set-logic array architecture is suggested for executing this image algebra. The optical implementation of the architecture, based on area coding of gray-scale values, is demonstrated. (C) 1995 Optical Society of America

Effect of binary block-selective solvents on self-assembly of ABA triblock copolymer in dilute solution

We have studied the self-assembly of the ABA triblock copolymer (P4VP-b-PS-b-P4VP) in dilute solution by using binary block-selective solvents, that is, water and methanol. The triblock copolymer was first dissolved in dioxane to form a homogeneous solution. Subsequently, a given volume of selective solvent was added slowly to the solution to induce self-assembly of the copolymer. It was found that the copolymer (P4VP(43)-b-PS366-b-P4VP(43)) tended to form spherical aggregate or bilayer structure when we used methanol or water as the single selective solvent, respectively.

Effect of the nature of annealing solvent on the morphology of diblock copolymer blend thin films

The morphologies and structures for the thin film of blend systems consisting of two asymmetric polystyrene-block-polybutadiene (SB) diblock copolymers induced by annealing in the vapor of different solvents, namely, cyclohexane, benzene, and heptane, which have different selectivity or preferential affinity for a certain block, were investigated by tapping mode atomic force microscopy (AFM) and transmission electron microscopy (TEM). The results revealed that even a slight preferential affinity of good solvent for one block would strongly alter the morphology of the blend thin film.

Microphase Separation of Mixed Polymer Brushes: Dependence of the Morphology on Grafting Density, Composition, Chain-Length Asymmetry, Solvent Quality, and Selectivity

Microphase separation of binary mixed A/B polymer brushes exposed to different solvents is studied using Single-Chain-in-Mean-Field simulations. Effects of solvent quality and selectivity, grafting density, composition, and chain-length asymmetry are systematically investigated, and diagrams of morphologies in various solvents are constructed as a function of grafting density and composition or chain-length asymmetry. The structure of the microphase segregated morphologies lacks long-range periodic order, and it is analyzed quantitatively Using Minkowski measures.

Control of self-organized low-dimensional morphology in Poly(styrene-b-4vinylpyridine)/polystyrene blend thin films

The surface morphologies of poly(styrene-b-4vinylpyridine) (PS-b-P4VP) diblock copolymer and homopolystyrene (hPS) binary blend thin films were investigated by atomic force microscopy as a function of total volume fraction of PS (phi(PS)) in the mixture. It was found that when hPS was added into symmetric PS-b-P4VP diblock copolymers, the surface morphology of this diblock copolymer was changed to a certain degree. With phi(PS) increasing at first, hPS was solubilized into the corresponding domains of block copolymer and formed cylinders. Moreover, the more solubilized the hPS, the more cylinders exist. However, when the limit was reached, excessive hPS tended to separate from the domains independently instead of solubilizing into the corresponding domains any longer, that is, a macrophase separation occurred. A model describing transitions of these morphologies with an increase in phi(PS) is proposed. The effect of composition on the phase morphology of blend films when graphite is used as a substrate is also investigated.

The formation of ordered nanoholes in binary, chemically similar, symmetric diblock copolymer blend films

Binary symmetric diblock copolymer blends, that is, low-molecular-weight poly(styrene-block-methyl methacrylate) (PS-b-PMMA) and high-molecular-weight poly(styrene-block-methacrylate) (PS-b-PMA), self-assemble on silicon substrates to form structures with highly ordered nanoholes in thin films. As a result of the chemically similar structure of the PMA and the PMMA block, the PMMA chain penetrates through the large PMA block that absorbs preferentially on the polar silicon substrate. This results in the formation of nanoholes in the PS continuous matrix.