Fuzzy control system for a remote focusing microscope

Space Station Crew Health Care System procedures require the use of an on-board microscope whose slide images will be transmitted for analysis by ground-based microbiologists. Focusing of microscope slides is low on the list of crew priorities, so NASA is investigating the option of telerobotic focusing controlled by the microbiologist on the ground, using continuous video feedback. However, even at Space Station distances, the transmission time lag may disrupt the focusing process, severely limiting the number of slides that can be analyzed within a given bandwidth allocation. Substantial time could be saved if on-board automation could pre-focus each slide before transmission. The authors demonstrate the feasibility of on-board automatic focusing using a fuzzy logic ruled-based system to bring the slide image into focus. The original prototype system was produced in under two months and at low cost. Slide images are captured by a video camera, then digitized by gray-scale value. A software function calculates an index of 'sharpness' based on gray-scale contrasts. The fuzzy logic rule-based system uses feedback to set the microscope's focusing control in an attempt to maximize sharpness. The systems as currently implemented performs satisfactorily in focusing a variety of slide types at magnification levels ranging from 10 to 1000x. Although feasibility has been demonstrated, the system's performance and usability could be improved substantially in four ways: by upgrading the quality and resolution of the video imaging system (including the use of full color); by empirically defining and calibrating the index of image sharpness; by letting the overall focusing strategy vary depending on user-specified parameters; and by fine-tuning the fuzzy rules, set definitions, and procedures used

One image reduction algorithm for RGB color images

We investigate the problem of combining or aggregating several color values given in coding scheme RGB. For this reason, we study the problem of averaging values on lattices, and in particular on discrete product lattices. We study the arithemtic mean and the median on product lattices. We apply these aggregation functions in image reduction and we present a new algorithm based on the minimization of penalty functions on discrete product lattices

Normalized Weighting Schemes for Image Interpolation Algorithms

This paper presents and evaluates four weighting schemes for image interpolation algorithms. The first scheme is based on the normalized area of the circle, whose diameter is equal to the minimum side of a tetragon. The second scheme is based on the normalized area of the circle, whose radius is equal to the hypotenuse. The third scheme is based on the normalized area of the triangle, whose base and height are equal to the hypotenuse and virtual pixel length, respectively. The fourth weighting scheme is based on the normalized area of the circle, whose radius is equal to the virtual pixel length-based hypotenuse. Experiments demonstrated debatable algorithm performances and the need for further research.Comment: 8 pages, 14 figure

Image Superresolution Reconstruction via Granular Computing Clustering

The problem of generating a superresolution (SR) image from a single low-resolution (LR) input image is addressed via granular computing clustering in the paper. Firstly, and the training images are regarded as SR image and partitioned into some SR patches, which are resized into LS patches, the training set is composed of the SR patches and the corresponding LR patches. Secondly, the granular computing (GrC) clustering is proposed by the hypersphere representation of granule and the fuzzy inclusion measure compounded by the operation between two granules. Thirdly, the granule set (GS) including hypersphere granules with different granularities is induced by GrC and used to form the relation between the LR image and the SR image by lasso. Experimental results showed that GrC achieved the least root mean square errors between the reconstructed SR image and the original image compared with bicubic interpolation, sparse representation, and NNLasso

Colour Morphology with Application to Image Magnification

Mathematische morfologie is een theorie voor de analyse van ruimtelijke structuren, gebaseerd op verzamelingenleer en het begrip verschuiving. In de jaren zestig voerden G. Matheron en J. Serra, beiden geïnspireerd door de studie naar de geometrische vorm van poreus medium, het begrip mathematische morfologie in. Poreus medium is binair in de zin dat een punt van poreus medium ofwel deel uitmaakt van een porie ofwel behoort tot de grondmassa rond de poriën. Zo ontwikkelden Matheron en Serra een theorie voor de analyse van binaire beelden. De grondmassa kan beschouwd worden als de verzameling van objectpunten in het beeld, terwijl de poriën het complement van deze verzameling vormen. Bijgevolg kunnen objectpunten behandeld worden met eenvoudige bewerkingen zoals unie, doorsnede, complement en verschuiving. Mathematische morfologie werd oorspronkelijk dus enkel voor binaire beelden ontwikkeld. Op deze manier legden Matheron en Serra alvast de basis voor mathematische morfologie in de beeldanalyse. Vandaag de dag heeft mathematische morfologie vele toepassingen in de beeldanalyse zoals randdetectie, ruisverwijdering, objectherkenning, patroonherkenning, beeldsegmentatie en beeldvergroting in o.a. de biologische en medische wereld. De basiswerktuigen van mathematische morfologie zijn de morfologische operatoren die een gegeven beeld $A$ dat we willen analyseren omzet naar een nieuw beeld $P(A,B)$ gebruik makend van een structuurelement $B$, om zo bijkomende informatie over de vorm, grootte, oriëntatie of beeldafmetingen van voorwerpen in $A$ te verkrijgen. Behalve de schijfjes- en umbrabenadering kan binaire morfologie uitgebreid worden naar morfologie voor grijswaardenbeelden door gebruik te maken van vaagverzamelingenleer, vaagmorfologie genoemd. De toepassing van morfologische operatoren op kleurenbeelden is zeker niet voor de hand liggend. En daarover handelt dit proefschrift. We hebben onze nieuwe kleurenmorfologische aanpak toegepast op het vergroten van zwart-wit beelden en kleurenbeelden met scherpe randen en onscherpe randen

Analysis of holograms of reacting sprays Final report

Holograms of reacting and nonreacting droplet sprays for data reductio

Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders

In this work we study a new class of similarity measures between interval-valued fuzzy sets. The novelty of our approach lays, firstly, on the fact that we develop all the notions with respect to total orders of intervals; and secondly, on that we consider the width of intervals so that the uncertainty of the output is strongly related to the uncertainty of the input. For constructing the new interval-valued similarity, interval valued aggregation functions and interval-valued restricted equivalence functions which take into account the width of the intervals are needed, so we firstly study these functions, both in line with the two above stated features. Finally, we provide an illustrative example which makes use of an interval-valued similarity measure in stereo image matching and we show that the results obtained with the proposed interval-valued similarity measures improve numerically (according to the most widely used measures in the literature) the results obtained with interval valued similarity measures which do not consider the width of the intervals

VISION SYSTEM FOR ONLINE DEFECT-DETECTION. An evaluation of methods for defect-detection for KWH Mirka's abrasives

KWH Mirka has machines for punching out disks from their abrasive sheets. The sheets have gone through many processing stages during its fabrication, and as a result they contain different kinds of defects. Sheets have been joined several times with dif-ferent techniques, the grip cloth has been joined, and test pieces have been carved out. These kinds of defects are made on purpose and are usually already marked, but not always. The abrasive roll may also contain unintended defects such as folds or stains. The goal of this thesis is to develop a complete system, and also evaluate different methods, for detecting defects in Mirkas abrasive sheets. An Omron FZ5 vision system has been installed at the machine and the first goal is to configure this system so that it detects the most common defects. This system should perform according to the re-quirements set by KWH Mirka and the environment at the machine. This part of the work shall also give an idea of the suitability of the Omron-library for this task. In an attempt to complete the texture processing shortcomings in the Omron-library, another algorithm based on features in frequency space will be tested with Matlab. Fuzzy membership functions are used to compare measured values against values from faultless material. The result is a complete system for detecting the most common defects, along with an evaluation of some more advanced method’s suitability for defect detection based on the pattern on abrasive sheets. This is all summarized to a recommendation on up-grades if more advanced measurements are to be done in the future.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format