Characterisation of mortar morphology in thin sections by digital image processing

2005 ◽  
Vol 35 (8) ◽  
pp. 1613-1619 ◽  
Author(s):  
Nicoletta Marinoni ◽  
Alessandro Pavese ◽  
Marco Foi ◽  
Luca Trombino
2021 ◽  
Vol 54 (1C) ◽  
pp. 16-29
Author(s):  
Shareef Al-Hamed

As igneous rocks have widely chemical and mineralogical compositions, there are many ways to classify these rocks. These ways are classical approved methods to give a reliable classification and nomenclature of rocks. Some igneous rocks may be classified by digital image processing to assist in classical methods. Five igneous samples were cut, prepared of thin sections, and polished to classify them by classical methods and digital image processing by ENVI software. Moreover, part of these samples crushed an analysis of major oxides. The current igneous samples have referred to the basic and mesocratic rocks based on the classical methods and this has corresponded to ENVI software. The igneous samples have reflected the leucogabbros when classify them by classical and ENVI classifications, except the G5 sample, which has been referred to as gabbro by ENVI. There is a clear similarity between the classical and ENVI classifications. ENVI classification is a reliable classification to assist the classical methods in the nomenclature of igneous rocks, especially, plutonic rocks, it can be also applied to thin sections of volcanic rocks to classify and nomenclature classification by ENVI has been applied on fifty thin sections of limestones to identify microfacies which are classified beforehand by classical (optical) classification. According to optical classification, microfacies have classified as mudstone, wackestone, packstone, and grainstone. When the digital classification is applied to them, there is no grainstone texture found in these them. Digital thin sections, where the true name of these microfacies is packstone. Therefore, the positive sides of the digital image processing by ENVI software appeared and contrasted to the optical classification which contained some mistakes when applied to the nomenclature of these microfacies.


Author(s):  
R. C. Gonzalez

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.


Author(s):  
L. Montoto ◽  
M. Montoto ◽  
A. Bel-Lan

INTRODUCTION.- The physical properties of rock masses are greatly influenced by their internal discontinuities, like pores and fissures. So, these need to be measured as a basis for interpretation. To avoid the basic difficulties of measurement under optical microscopy and analogic image systems, the authors use S.E.M. and multiband digital image processing. In S.E.M., analog signal processing has been used to further image enhancement (1), but automatic information extraction can be achieved by simple digital processing of S.E.M. images (2). The use of multiband image would overcome difficulties such as artifacts introduced by the relative positions of sample and detector or the typicals encountered in optical microscopy.DIGITAL IMAGE PROCESSING.- The studied rock specimens were in the form of flat deformation-free surfaces observed under a Phillips SEM model 500. The SEM detector output signal was recorded in picture form in b&w negatives and digitized using a Perkin Elmer 1010 MP flat microdensitometer.


Author(s):  
J. Hefter

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.


Author(s):  
K. N. Colonna ◽  
G. Oliphant

Harmonious use of Z-contrast imaging and digital image processing as an analytical imaging tool was developed and demonstrated in studying the elemental constitution of human and maturing rabbit spermatozoa. Due to its analog origin (Fig. 1), the Z-contrast image offers information unique to the science of biological imaging. Despite the information and distinct advantages it offers, the potential of Z-contrast imaging is extremely limited without the application of techniques of digital image processing. For the first time in biological imaging, this study demonstrates the tremendous potential involved in the complementary use of Z-contrast imaging and digital image processing.Imaging in the Z-contrast mode is powerful for three distinct reasons, the first of which involves tissue preparation. It affords biologists the opportunity to visualize biological tissue without the use of heavy metal fixatives and stains. For years biologists have used heavy metal components to compensate for the limited electron scattering properties of biological tissue.


Author(s):  
Sindhu Madhuri G. ◽  
Indira Gandhi M P

Image is a basic and fundamental data source for the digital image processing. This image data source is required to be processed into information or intelligence and further to knowledge levels where it is required to understand and migrate into knowledge economy systems. Image registration is one of such key and most important process already identified in the digital image processing domain. Image registration is a process of bringing the reference image and sensed image into a common co-ordinate system, and application of complex transformation techniques for necessary comparison of reference with sensed images obtained from different - views, times, spaces, etc., in order to extract the valuable information and intelligence embedded in them. Due to the complexity of overall image registration process, it is difficult to suggest a single transformation technique even for a specific application. In addition, it is highly impossible to suggest one single transformation technique for comparison of various sensed images with a reference image during the image registration process. This research gap calls for the development of new image registration techniques for the application of more than one transformation technique during the image registration process for the necessary comparisons with reference image & sensed images, those are obtained from the available heterogeneous sources or sensors, based on the requirement. In addition, it is a basic need to attempt for the measurement of effectiveness of the image registration process also. Therefore, a research framework is developed for image registration process and attempted for the measurement of its effectiveness also. This new research area is a novel idea, and is expected to emerge as a provision for the knowledge computations with creative thinking through the embedded intelligence extraction during the complex image registration process.


Sign in / Sign up

Export Citation Format

Share Document