Enhanced Crack Depth Measurement through Binary Image Processing and Geometric Analysis

Kavita Bodke

Accepted: 2025-10-07

Abstract

This paper presents a novel, image-based approach for automated quantifying structural crack width and depth in concrete using binary image processing techniques. Concrete cracks are critical indicators of potential structural failure, and traditional manual inspection methods are often time-consuming, unsafe, and prone to inaccuracies. The proposed method automates crack detection by converting RGB images of concrete surfaces into binary images, isolating the cracks, and measuring their width using the Euclidean distance formula. The depth of the cracks is then estimated using trigonometric relationships based on the measured crack width and viewing angles (30°, 45°, and 60°). This lightweight, cost-effective approach provides a practical alternative to more complex machine learning-based detection methods, making it ideal for real-time infrastructure health monitoring. The results highlight the effectiveness of this technique in accurately measuring crack width and depth across multiple angles, providing critical data for infrastructure health monitoring.

Visual display of tropical cyclone structure zone hazard assessment based on almost periodic analysis

A.A. Paramonov, A.V. Kalach

Accepted: 2025-09-24

Abstract

A visual hazard assessment of tropical cyclone structure zones based on almost periodic analy-sis is proposed. We consider a visualization toolkit that allows us to customize and display both tropical cyclone zones whose radii are multiples of the found characteristic near-periods and shad-ing of the interzonal space taking into account the degree of hazard relative to the cyclone center.
As the main tools we used the visualization modules of the matplotib library Circle and Wedge, which allow us to customize the identified structural zones according to their hazard degree. This development can be useful for emergency-rescue services as an operational diagnostic tool to sup-port decision-making in emergencies caused by natural hazards.

AUTOMATED DIABETIC RETINOPATHY DIAGNOSIS AND CLASSIFICATION USING DEEP LEARNING WITH CAPSULE NETWORK LAYERS AND STOCHASTIC ENSEMBLE APPROACH

M.A Abini, S Sridevi Sathya Priya

Accepted: 2025-09-10

Abstract

Adapting Virtual Vegetation Samples to Multiobject Visualization of a New Type

P.Yu. Timokhin, M.V. Mikhaylyuk

Accepted: 2025-09-06

Abstract

The paper focuses on the visualization of vegetation arrays within virtual environment systems through a novel type of virtual object known as multiplicable point cloud (MPC). It addresses the challenge of adapting virtual vegetation samples, derived from 3D scans of real natural objects, to the MPC-format. The research highlights key discrepancies between these samples and the MPC-format, and presents a method to resolve these issues using the open-source CloudCompare software. Additionally, the paper proposes an output file format for the adapted virtual samples, utilizing a straightforward and easily interpretable PLY-syntax (Polygon File Format). Under the approbation of the proposed solutions, the adaptation and multiobject visualization of various virtual samples of tree- and grass-like plants were conducted. The results of the approbation affirm the expediency of the proposed method and approach, as well as their potential to effectively enhance the realism of virtual environments.

Principles of organization of continuity in discrete geometrized space

A.V. Tolok, N.B. Tolok

Accepted: 2025-08-24

Abstract

The paper considers the principle of analytical transition to a local function at points on the domain of an implicit function defining a geometric object. Herewith, a transition to partial derivatives is provided to obtain a general form of an implicit local function describing the local geometry for any single point in the object domain. On the analogy of R-functional modeling, a mathematical apparatus for union/intersecting local geometric characteristics of a local function at a single point is provided to construct a discrete region of a complex geometric object.
An example of the intersection of two functions on a defined domain of arguments demonstrates the obtaining of a discretely geometrized three-dimensional manifold for describing a cylinder.
The proposed work is the continued development of method of the Functional Voxel Modeling which offers an analytical structure for the discrete-continuous description of complex geometric objects instead of the means of linear approximation currently used in this method.

Visualization of Complex Roots for Nonlinear Algebraic Equations

Mehmet Pakdemirli

Accepted: 2025-05-26

Abstract

Visualization of complex roots of a nonlinear algebraic equation is discussed in this work. The method is based on calculating the modulus of the complex valued function and representing it as a surface in a three dimensional space where the axis consist of real and imaginary axis and the modulus function. Since it may be inconvenient to visualize multiple roots in a three dimensional surface, contour plot is suggested as an alternative to visualize better the location of roots. Roots of polynomial functions as well as non-polynomial functions are treated as examples. The contour plot is the best to visualize the complex roots in a single graph.

DATA CLASSIFICATION WITH USING VISUALIZATION TOOLS

Andrey Dzengelewski

Accepted: 2025-04-29

Abstract

This article discusses ways to use visualization tools to build object classifiers during automation of a large enterprise. The proposed approaches allow stakeholders to get a visual representation and participate in the decisions required when building a classifier for large arrays of records.
The use of visualization tools is considered when selecting classification objects, determining the attributes and values of classification attributes, ensuring the convenience of the classifier and implementing conflicting requirements from stakeholders. Among the proposed solutions, the methods of using system classes, building logical and physical models of the classifier, multidimensional classification, attribute-value data model, logical data model for describing the required analytics are described.
The subject area is a classifier of works and services, examples of using the proposed solutions and the results of building a classifier at a large enterprise are given.

Using Sperm Imaging with Laser Interference Microscopy for Comprehensive Assessment of the Functional State of Cells during Cryopreservation and under the Action of Molecular Hydrogen

A.V. Deryugina, M.N. Ivaschenko, P.S. Ignatiev, V.B. Metelin

Accepted: 2025-04-29

Abstract

Significant advances have been made in sperm cryopreservation but the search for effective sperm cryopreservation technologies is a pressing issue in modern biology and medicine. The most effective cryopreservation leaves 50-60% of viable cells. The paper discusses the use of molecular hydrogen (H2) as a new approach to enhancing sperm protection during freezing and thawing. H2 is a universal antioxidant and limits damage to biomolecules. Visual registration of spermatozoa under the action of H2 was performed using modern microscopy techniques. Laser interference microscopy was used in the work. Laser interference microscopy records the cell surface architectonics depending on the modulation of the optical density of cellular structures. This visualization option provides information on the metabolic level and expands the possibilities for interpreting experimental results. Sample preparation, dyes, and fixatives are not used in interference visualization. The paper presents an analysis of phase images of spermatozoa during cryopreservation and using H2 as a cryoprotector. Verification of the method for analyzing phase characteristics of spermatozoa as an indicator of the metabolic state of cells was performed by analyzing clinical and laboratory parameters of spermatozoa. The phase height of spermatozoa during cryopreservation decreased, the intensity of energy processes decreased, and the oxidative potential of cells increased. A direct correlation was shown between the phase height of spermatozoa and the concentration of ATP, and an inverse correlation was found from the concentration of malondialdehyde (MDA). The use of H2 determined an increase in the phase height of spermatozoa, an increase in energy metabolism, and a decrease in cell oxidation. Changes in the metabolic activity of spermatozoa under the action of H2 were combined with an improvement in sperm fertility. Thus, phase interference microscopy allows for a qualitative and quantitative assessment of the physiological state of spermatozoa. It is an objective method of vital analysis of complex metabolic activity of cells. It can be used for express diagnostics of their functional state.

Pressure-gradient method for the visualization of a wave attractor

Stepan Elistratov

Accepted: 2025-04-13

Abstract

A wave attractor, a phenomenon of self-focusing of internal/inertial waves on a closed trajectory, has recently been widely studied from different viewpoints. How-ever, there is a lack of investigations concerning its visualization. Peculiar set-ups lately studied show that conventional methods need some improvement.

Herewith, in gas dynamics, the Schlieren method, based on the density gradient, is widely used. Concerning incompressible flows, it is inapplicable; however, pressure can be considered instead density. In this work, a pressure gradient is used as a way to visualize an attractor.

Determination of Adiabatic Wall Temperature in High-Speed Gas Flows Using Infrared Thermography

Н.С. Маластовский, Н.А. Киселёв, А.Г. Здитовец, А.Ю. Виноградов

Accepted: 2025-03-21

Abstract

This paper presents a method for the non-contact determination of the adiabatic wall temperature in high-speed gas flows. The method is based on the processing of a sequence of thermograms obtained using an IR camera, within a program developed in Python 3.10. The approach demonstrated high efficiency when handling large datasets, particularly concerning minimizing temporal and computational demands. The adiabatic wall temperature was determined under both steady-state conditions, directly in the experiment, and transient conditions, through the extrapolation of the heat flux as a function of the current temperature of the examined surface. The effectiveness of this method was demonstrated in the investigation of non-mechanical energy separation in compressible gas flows.

Three-dimensional images of residual strain fields by wavelet transform method

I.V. Laktionov, E.V. Gladkih, A.P. Fedotkin, G.Kh. Sultanova, А.S. Useinov

Accepted: 2025-03-21

Abstract

The accuracy of measuring Vickers hardness values depends on image focusing both during automated determination of residual imprint diagonal lengths and during operator working. Widespread algorithms for image focusing are based on brightness and contrast adjustment. We propose a new approach based on alternative algorithms for more accurate microscope focusing system used in marking imprints after indentation. Implemented algorithms are based on variance, Laplace function and wavelet transform. We select the optimum values of the basis and transform depth when using the wavelet transform. We tested new approach on samples with poor contrast, rough surfaces, and materials with pile-ups occurred in the indentation process. Applying different focusing functions depending on focus position demonstrates a more stable performance of the algorithm with wavelet transform. We also demonstrated obtaining a fully focused frame and a pseudo three-dimensional map of the sample.

Use of Hadamard matrices in single-pixel imaging

Denis V. Sych

Accepted: 2024-08-13

Abstract

Single-pixel imaging is a method of computational imaging that allows to obtain images of objects using a photodetector that does not have spatial resolution. In this method, the object is illuminated by light having a special spatio-temporal structure, — light patterns, and a single-pixel photodetector measures the total amount of light reflected from the object. The possibility of obtaining an image and the image quality are closely related to the properties of the applied patterns and computational algorithms. In this paper, we consider patterns obtained from modified Hadamard matrices and study the features of image calculation using single-pixel imaging. We show the possibility of reducing both the sampling time and the computational resources required to obtain images by modifying the pattern system. The proposed theoretical method can be used in the practical implementation of the single-pixel imaging method in an experiment.