image processing

Dense concrete is an essential building material in industrial, civil and transportation constructions. The physical and mechanical characteristics of concrete – compressive strength, elastic modulus, density etc. – are interrelated, and various non-destructive testing methods are used to establish the correlations between them. One of the structural features of concrete is porosity – the presence of pores and voids in the concrete body.

A high-precision method for predicting the linear dimensions of three-dimensional objects of arbitrary shape based on computed tomography data has been developed. The method is aimed at reducing measurement errors caused by partial-volume effects, shadow transitions, and arbitrary spatial orientation of the object.

This article proposes three methods for parallelizing the compression of video streams from Earth surface scanners installed on microsatellites. The core innovation lies in the application of vertical, horizontal, and block-based segmentation of the input stream to enable scalable and high-throughput image compression. The study establishes a quantitative relationship between video stream intensity and satellite parameters, and also determines the required number of compression cores based on the satellite's characteristics and the performance of a single core.

The article explores the possibilities of implementing the JPEG-LS image compression algorithm on Field Programmable Gate Arrays (FPGA) for processing monochrome video streams from Earth surface scanners. A comparison of software implementations of the algorithms, their compression ratio, and execution time is conducted. Methods for improving FPGA performance are considered, using parallel data processing and optimized data structures to accelerate compression and decompression processes.

The paper investigates computer diagnostic systems, their architectures, methods, and algorithms used in their work to diagnose cancer, including breast, lung, brain, and other tumors.

Traditional and neural network methods for image segmentation and classification are analyzed and compared, and diagnostic tools in medicine are analyzed.

The key approaches to medical image processing are investigated, in particular, the analysis of segmentation methods based on U-Net networks and classification using convolutional neural networks.

Introducing neural network training process modification that uses combination of several datasets to optimize search of objects and obstacles using mobile robotic systems in a closed space. The study includes an analysis of papers and existing approaches aiming to solve the problem of object boundary detection and discovers the key features of several neural network architectures. During research, it was discovered that there is an insufficient amount of data about the effectiveness of using obstacle detection approaches by mobile robotics systems in a closed space.

Запропоновано алгоритмічні та програмні засоби опрацювання зображень в операційній системі Mac OS X. Забезпечено можливість коригування колірних характеристик зображення, змінюючи контрастність, чіткість, насиченість тіней, інтенсивність теплих відтінків, а також усунення ефекту червоних очей. Показані результати тестування запропонованих засобів, які підтверджують їх ефективність.

Стосовно зображень розроблено модифікації алгоритму RSA такі, що зберігається криптографічна стійкість і забезпечується повна зашумленість зображення, з метою унеможливити використання методів візуальної обробки зображень.

For images modified RSA algorithm is developed such that stored cryptographic and secured full noisy image in order to prevent the use of methods of visual imaging.

This article examines the features of algorithmic and software tools for processing fuzzy images. The work uses three filters: CIGaussianBlur, CIUnsharpMask and CIBlendWithAlphaMask. The described filters allow you to improve image quality, reduce noise and reproduce details.The initial task is to process the blurring of images. For this, the CIGaussianBlur filter is used, which applies a Gaussian blur to the image. This blur reduces high-frequency noise and adds smoothness to the contours of objects.The second filter, CIUnsharpMask, is used to restore image details.