The occurrence of faults in coal seams has an impact on the possibility of methane hazard. There are several methods for identifying tectonic faults, but they cannot be applied directly to solve dynamic hazard problems in coal mine. Thus, searching for appropriate methods, that can detect faults in regional and local scales is needed. In order to meet this need, the paper proposes a new measurement method of estimating changes to the coal structure, based on profilometry measurements (roughness analysis) and application of madogram functions. Based on examining coal samples from near fault zones it was shown that the proposed approach allows us to detect changes of the coal surface that appear as the distance to a tectonic fault gets shorter. The proposed method, due to its simplicity and speed of measurement, implies a potential for practical application in the process of detecting local tectonic dislocations in coal mines.

Urbanization has a far-reaching impact on the environment, economy, political and social processes. Therefore, understanding the spatial distribution and evolution of human settlements is a key element in planning strategies that ensure the sustainable development of urban and rural settlements. Accordingly, it is very important to map human settlements and to monitor the development of cities and villages. Therefore, the problem of settlements has found its reflection in the creation of global databases of urban areas. Global settlement data have extraordinary value. These data allow us to carry out the quantitative and qualitative analyses as well as to compare the settlement network at a regional, national and global scale. However, the possibility of conducting both spatial and attribute analyses of these data would be even more valuable. The article describes how to prepare raster data so that they can be implemented into a vector database. It answers the questions whether it is possible to combine these data with databases available in Poland and what benefits it brings. It presents the methods of data generalization and the optimization of time and disk space. As a result of the study, two vector databases with GUF data were developed. The first database resolution is similar to the original (~12 m resolution) database, the second database contains less detailed (~20 m resolution) data, generalized using mathematical morphology. Both databases have been enriched with descriptive data obtained from the National Geodetic and Cartographic Resource.

In this paper methods and their examination results for automatic segmentation and parameterization of vessels based on spectral domain optical coherence tomography (SD-OCT) of the retina are presented. We present three strategies for morphologic image processing of a fundus image reconstructed from OCT scans. A specificity of initial image processing for fundus reconstruction is analysed. Then, the parameterization step is performed based on the vessels segmented with the proposed algorithm. The influence of various methods on the vessel segmentation and fully automatic vessel measurement is analysed. Experiments were carried out with a set of 3D OCT scans obtained from 24 eyes (12 healthy volunteers) with the use of an Avanti RTvue OCT device. The results of automatic vessel segmentation were numerically compared with those prepared manually by the medical doctor experts.

Buzz, squeak and rattle (BSR) noise has become apparent in vehicles due to the significant reductions in engine noise and road noise. The BSR often occurs in driving condition with many interference signals. Thus, the automatic BSR detection remains a challenge for vehicle engineers. In this paper, a rattle signal denoising and enhancing method is proposed to extract the rattle components from in-vehicle background noise. The proposed method combines the advantages of wavelet packet decomposition and mathematical morphology filter. The critical frequency band and the information entropy are introduced to improve the wavelet packet threshold denoising method. A rattle component enhancing method based on multi-scale compound morphological filter is proposed, and the kurtosis values are introduced to determine the best parameters of the filter. To examine the feasibility of the proposed algorithm, synthetic brake caliper rattle signals with various SNR ratios are prepared to verify the algorithm. In the validation analysis, the proposed method can well remove the disturbance background noise in the signal and extract the rattle components with well SNR ratios. It is believed that the algorithm discussed in this paper can be further applied to facilitate the detection of the vehicle rattle noise in industry.