Metallurgical Image Analysis Software Free Download
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Download ZEN lite, your free copy of the powerful ZEN microscopy software. Use ZEN lite as a viewer for your CZI files or other standard file types. Perform image acquisition or fundamental image analysis and processing tasks.
Please note: ZEN lite is the free, unlicensed edition of ZEN. Once ZEN has been downloaded and installed, ZEISS Microscopy Installer will check your ZEN license and, if you don't have one, will default you to ZEN lite.
PAXcam easily attaches to your upright or inverted metallograph, and allows easy acquisition of high resolution images. Images are suitable for reports, presentations, measurements, and image analysis functions, and PAX-it software may be integrated with your PAXcam to provide flexible tools for metallographic measurements, analysis, and reporting.
PAX-it metallography software is leading-edge digital imaging software for a wide variety of metallurgical applications, for labs set up for quality control or quality assurance, production, inspection, failure analysis, and research.
Metlab Equipments & Engineering Systems is Leading Manufacturer, Trader and Exporter of Metallurgical Lab Equipments , We Set Up Full Metallurgical Lab in that we Cover Metallurgical Microscop, Stereo Zoom Microscope, Research microscope, Image Analysis Software, Digital Microscopy Camera, Abrasive Cutting Machine, Grinding Machine, Polishing Machine & Hot Mounting Press etc. Salient features such as safe usage, reliable performance, high accuracy, wide measuring range, fine calibration and long functional life make our range of testing equipment highly popular in the market. Owing to these products' compliance with international quality standards, these are extensively used in numerous industrial applications.Contact us info@metlab.in or Visit Mob: 9898046788metallographic analysis is the study of a materials microstructure and can be considered an integral branch for metallurgical testing or for the field of materials science. Microstructural analysis of a material's metallographic microstructure aids in determining if the material has been processed correctly and is therefore a critical step for determining products reliability (Quality Control) and/or for determining why a material failed (Metallographic Failure analysis). Metallurgy is primarily the study of metals, however, many of the principles used for testing metals applies to ceramics, plastics, minerals, computer chips and many other applications which may be more unique such as measuring the age of the fish population in a lake by statistically analyzing the thickness of the ear bone.
Abstract:Optical image analysis (OIA) supporting microscopic observation can be applied to improve ore mineral characterization of ore deposits, providing accurate and representative numerical support to petrographic studies, on the polished section scale. In this paper, we present an experimental application of an automated mineral quantification process on polished sections from Zaruma-Portovelo intermediate sulfidation epithermal deposit (Ecuador) using multispectral and color images. Minerals under study were gold, sphalerite, chalcopyrite, galena, pyrite, pyrrhotite, bornite, hematite, chalcocite, pentlandite, covellite, tetrahedrite and native bismuth. The aim of the study was to quantify the ore minerals visible in polished section through OIA and, mainly, to show a detailed description of the methodology implemented. Automated ore identification and determination of geometric parameters predictive of geometallurgical behavior, such as grade, grain size or liberation, have been successfully performed. The results show that automated identification and quantification of ore mineral images are possible through multispectral and color image analysis. Therefore, the optical image analysis method could be a consistent automated mineralogical alternative to carry on detailed ore petrography.Keywords: optical image analysis; multispectral images; color images; ore minerals; optical microscopy
Stereology has been used to characterize a three-dimensional (3D) microstructure in terms, for example, of the above-described parameters for several years now, while only analyzing two-dimensional (2D) micrographs (Ref 10). The principle, however, remains the same nowadays, even with more powerful microscopes and computers available: The linear intercept (LI) method is still widely used to characterize microstructures (Ref 11,12,13,14,15,16). This method consists in drawing test lines over a micrograph and counting the amount of intercepts of the carbide-carbide and carbide-matrix interfaces as well as measuring the length of each newly defined segment throughout each line (Ref 17). In its modern version, however, these operations are performed by image analysis software over digital micrographs. These programs consider rows and/or columns of the digital image as the test lines and automatically measure all the required quantities.
Although this automatic method has become standard in the field of image analysis (Ref 8, 18), the information that can be extracted out of it is limited by its own nature: d and λ are linear density parameters. They are not, at least explicitly, giving away any details about the shape or distribution of the particles. Take, for example, two two-phase alloys with the same d value. One could mistakenly expect these two alloys to be equivalent to each other in terms of morphology or size distribution of its particles. However, in reality, the two alloys can contain carbides with completely different shapes and therefore completely different size distributions. This means that the mean carbide intercept size does not unequivocally determine the carbide form and/or its size dispersion. This can be easily seen in one of the most general stereology equations:
With this shortage and a future computational application in mind, this proposal describes the aforementioned relation in terms of the carbide equivalent areal diameter (EAD) (which is a measure of the carbide size and is not biased by the shape of the feature) and some tailored parameters to properly describe every detail in any carbide phase. An alternative definition for carbide contiguity is also provided. The approach is based entirely on features that are measurable with any image analysis software such as areas and perimeters.
As in every microstructural/stereological analysis, the first step is to obtain good quality micrographs. Given the small size that the carbides in these tool steels might have, scanning electron microscope (SEM) micrographs are employed. These are to be taken from different sectors of the sample to secure good representation of the overall structure. It is noteworthy that the lighting conditions must be as constant as possible within each image as well as over the batch to avoid errors in the analysis stage.
The second step, as discussed above, is importing the image batch to the image analysis environment, where the intensity information of each pixel and its surrounding is used to create a binary, i.e., black and white (B&W), version of the microstructure.
As previously discussed, the image batch is imported into the image processing software, where it is processed sequentially. This means that once the settings for the enhancement and binarization are set for one picture, all the other micrographs taken from the same sample are processed in the same way, one after the other.
The implementation of some of these measurements is straightforward: (i), (ii) and (iii) are easily performed with the help of any image analysis software capable counting the number of pixels that form each pixel island. This work scheme is an extension of work previously developed by some of the authors in (Ref 37), where binary characterization was successfully employed to create 2D finite element method models. Points (iv) and (v), on the other hand, are carried out with a somewhat more complex approach. Figure 8 displays in red a schematic representation of the magnitudes to be measured.
In Eq 11, 12 and 23, perimeter measurements are required. These measurements were taken with the algorithm described in section 2.3.1. This function computes the perimeter of the pixel islands even if these islands lay on one of the edges of the image. It was therefore necessary to remove these pixels from the measurement to avoid overestimation of the boundaries. Its authors published the script in the MATLAB® File Exchange Web site, and the script is free to use (Ref 54). In the case that the analyzed images were the product of subdividing a larger micrograph, the objects lying in the borders of the smaller binary subimages can be reconstructed by, respectively, summing the corresponding perimeters and areas.
The proposed procedure is a very useful tool in various levels. The novel approach to binarization, for example, can be independently employed to tackle other complex applications in the image processing field. The most promising field of application is material characterization and design, with the aim set on improving abrasive wear resistance, based on the newly defined parameters and their implications in the already known intercept size and free path in the matrix. For instance, in a recent work by Bostanabad et al. (Ref 22), where the state-of-the-art techniques in microstructure characterization and reconstruction are detailed, it can be seen how the physical descriptors here described fit the needs of a regular 2D/3D reconstruction scheme. Further developments in the creation of these microstructures are ongoing both in 2D and in 3D.
At ATRONA, we offer you one of the most advanced metallurgical test labs in the country with the latest instruments, equipment and technology, and four full time metallurgists on staff, including our lead metallurgist, Ott Odeh. Our metallurgical lab has four fully-equipped Metallographs with full image analysis capabilities utilized for microstructure examination, a Keyence VHX-5000 Digital Microscope, two full Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS) systems with full digital imaging, two fully-automatic micro-hardness testing systems capable of performing all sorts of routines and mapping procedures, and the ability to perform simultaneous testing on up to eight samples, automated direct hardness testers, and much more. 2b1af7f3a8