TOOLS TO STORE INFORMATION ABOUT THE ENVIRONMENT

Earth Science provide large amounts of data. The available information can be stored and then analysed in different systems. For disciplines such as: geology, geophysics and environmental protection are created database. At the request of the Ministry of the Environment was established portal containing a record of such databases. There are a number of databases that can be classified into several groups. Presented work focuses on the analysis of environmental databases. The study analysed the opportunities offer such systems, examined access to information

Idee nowelizacji kodeksu karnego

Praca recenzowana / peer-reviewed pape

Applying image mining to the analysis of rock structure images [abstract] /

Tyt. z nagłówka.Artykuł jest abstr. referatu z konferencji.Bibliogr. s. 87.Obtaining, storing and sharing geological digital data in a form of images have been influenced by the dynamic development of information technology. Due to the fact that the multimedia data is not connected with a give PC or storage medium any more, but it is widely available as databases stored on network servers and accessed simultaneously by a number of users this suggests that data should be analyzed also in a new, for example parallel form. It necessitates defining the way in which the data in question is organized and interpreted efficiently. The aim of this discussion is to present the possibility to define image mining method for understanding and analyzing large image sets based on the methods of image analysis. The Authors present the concept of IT system developed to search for the images of particular rock structures in multimedia databases. Up till now, the use of databases in the image analysis process has been reduced to storing large amounts of data in form of images. However, all transformations and the analysis of such sets are performed on the user’s PC. On the one hand, this requires a large data set (images) to be sent by network each time, but on the other hand this may also pose problems resulting from managing such large amounts of analyzed images on a PC. A solution for image exploration, which is based on any attributes extracted with computer image analysis with the use of extensions for server-side operations is proposed. The proposed approach eliminates these problems completely by moving all transformations of image analysis onto a database server platform. For this purpose, a set of routines realizing transformations of image analysis and mathematical morphology were developed. The proposed approach allows the unification of the image processing and analysis area as well as advanced statistical analysis of obtained parameters describing geometrical sized of the objects and images. The methodology is based exclusively on an image request, to which the system’s response is a set of images presenting visually similar rocks (Ładniak & Młynarczuk 2015). The search is based only on the query in the form of the image, while the system in response returns a collection of photographs representing the same structure of the rock. The proposed method is based on the methods of image analysis and the artificial intelligence, in particular, on the methods of data clustering and data classification. Decisions concerning the classification were based on six different methods of clustering and classification of data. As a result of the study showed that methods such as MEC, and based on the naive Bayes classifier and the method of the k-nearest neighbors have a very good classification results reaching for some of the studied rocks up to 100% correct decisions. To detect the similarity it is required to apply Determination of the characteristics identifying photographs (using image analysis algorithms), then verification of feature representativeness – to reduce considerable correlation between the measure of particular features in the representations of particular features, and apply decision making methods (in form of methods of cluster analysis). As a results, the proposed methodology was illustrated by practical realization of measurement types for a simple structure of copper concentrate, from the point of view of image analysis, structures such as dolomites from, for example, Rędziny and Laskowa Góra and sandstones from Tumlin and Wiśniówka and also from the point of view of method where the purpose is to enable effective search of images of a given rock in multimedia databases. The research material was microscope images of thin sections of 19 rock types. The analyzed rocks came from the southern regions of the Polish (Carpathian and Sudeten) Mountains. From these rocks thin sections were made. The photos were taken with a polarized light optical microscope, at the optimum illumination and magnification which was the same for all the photos registered for a given type of rock. For each rock type, 250 photos were taken. The collection of images that were used in the process of performing measurements encompassed 5,250 digital images presenting 21 rock types. The discussed system concept, based on a feature space defined by the authors, successfully matches up images with the reference standard. The effectiveness rate of that process is very high (very often, it is 100%). Failed classifications concern only the images which differ visually in a considerable way from the rest of the images within a given group. As a conclusion authors would like to show that the main purpose of proposed solution is to facilitate the decision-making process involved in determining the measurements of the stereological parameters of rocks and the similarity of investigated objects. The proposed method of image mining is based on the application of database technologies, image processing, and image analysis and artificial intelligence concepts. The authors demonstrate that these may turn out to be effective mathematical methods, successfully applied to the problem of image understanding, performed with imagings presenting rock textures. In the opinion of the authors, it meets the requirements and, as such it can be applied to the problem of searching for images in databases, searching discs in order to find images of a given rocks and automatic information gain based on video sequences, e.g. in order to find frames presenting particular rock structures.Dostępny również w formie drukowanej.KEYWORDS: geological digital data, information technology, multimedia

Evaluation of Local Matching Methods in Image Analysis for Mineral Grain Tracking in Microscope Images of Rock Sections

Modern geological techniques have resulted in vast and growing databases of digital images and video sequences of rocks, which are available for the use of researchers. The number of database images continues to increase exponentially, creating a need for techniques that will enable the automation of data set management. Desired techniques include query by image, a topic that has been extensively elaborated on in the literature recently. Unfortunately, using such techniques in the geological sciences has been very sporadic and insufficient. This paper presents the evaluation of characteristic local features within rock images for tracking objects on images or video sequences. It also discusses the possibilities for using selected local feature descriptors for content-based image retrieval (CBIR) in the area of geological sciences. The evaluation was performed for the Speeded Up Robust Features (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), Harris–Stephens Algorithm (HSA), Minimum Eigenvalue Algorithm (MEA), and Features from Accelerated Segment Test algorithm (FAST) methods, which are widely known and appreciated in the computer vision field. These methods were analysed for their application to microscopic images of rocks. Five functional cases of geological grain tracking were investigated, based on a selected non-transformed query image, as well as a computer-rotated, acquisitive-rotated, computer-magnified, and an acquisitive-magnified query image. The results demonstrated that these methods can be successfully used for geological applications

Technical Note. The Concept of a Computer System for Interpretation of Tight Rocks Using X-Ray Computed Tomography Results

The article presents the concept of a computer system for interpreting unconventional oil and gas deposits with the use of X-ray computed tomography results. The functional principles of the solution proposed are presented in the article. The main goal is to design a product which is a complex and useful tool in a form of a specialist computer software for qualitative and quantitative interpretation of images obtained from X-ray computed tomography. It is devoted to the issues of prospecting and identification of unconventional hydrocarbon deposits. The article focuses on the idea of X-ray computed tomography use as a basis for the analysis of tight rocks, considering especially functional principles of the system, which will be developed by the authors. The functional principles include the issues of graphical visualization of rock structure, qualitative and quantitative interpretation of model for visualizing rock samples, interpretation and a description of the parameters within realizing the module of quantitative interpretation

Multi-criteria optimization of the turning parameters of Ti-6Al-4V titanium alloy using the Response Surface Methodology

The paper depicts an application of Response Surface Methodology (RSM) for predicting selected parameters in turning of Ti-6Al-4V titanium alloy using polycrystalline diamond tool. Response surface plots that are generated by the model helps in determining the optimum combination of input factors (cutting speed vc and feed rate f) for best possible surface roughness (Sa), cutting force (Fc)and temperature (T) for dry and cooling turning. The methodology of multi-criteria optimization was used to establish the interaction between input parameters and given responses