Robust object detection in images corrupted by impulse noise

This paper proposes two effective normalized similarity functions for robust object detection in very high density impulse noisy images. These functions form an integral similarity estimate based on relations of minimum by maximum values for all pairs of analyzed image features. To provide invariance under the constant brightness changes, zero-mean additive modification is used. We explore properties of our functions and compare them with other commonly used for object detection in images corrupted by impulse noise. The efficiency of our approach is illustrated and confirmed by experimental results

Review of Methods for Smartphone Application Foot Size Estimation From Images

The task of obtaining real-world coordinates of an object is quite challenging. In this paper proposed brief explanation of algorithms dedicated to overcome this challenge. They were analyzed including their advantages and disadvantages in application to possible implementation in smartphone app

Analysis of motion detection in video for early forest fire detection

Reliable and early detection of forest fire can significantly reduce the damage caused to forestry. Using of machine vision systems, namely video fire detectors, belongs to promising area forest fire recognition. Motion detection is the key step for smoke and flame monitoring in video. This document describes some methods of movement detection in video sequences, including comparative analysis of opportunities to find moving regions, their advantages and disadvantages

Metallographic studies

The composition of the fractions of the heavier cut of pyrolysis gas oil production was investigated by gas chromatography. In order to increase the profitability of pyrolysis units, it is recommended to organize complex technological schemes for the processing of the heavier cut of pyrolysis gas oil

Object localization and classification based on convolutional neural networks

The paper deals with the basic structural elements of the convolution neural network as well as methods for describing and tested methods of localization of objects in the neural network. Effective approaches are proposed for the construction of algorithm of objects localization. The results of the implementation of the algorithm are presented

Analysis person re-identification methods

This paper reviews the most common non-destructive testing (NDT) methods of concrete strength as utilized by the structural engineering industry. The factors that influence the success of NDT methods are discussed and ways to mediate their influence are recommended. Reference is made to standard guidelines for the application and interpretation of the discussed NDT methods. Perceptions of NDT inadequacy were attributable to lack of understanding construction materials and NDT methods themselves. The intent of this paper is to address these concerns by describing the most common successful methods of NDT as applied to concrete structures

Analysis person re-identification methods

This paper reviews the most common non-destructive testing (NDT) methods of concrete strength as utilized by the structural engineering industry. The factors that influence the success of NDT methods are discussed and ways to mediate their influence are recommended. Reference is made to standard guidelines for the application and interpretation of the discussed NDT methods. Perceptions of NDT inadequacy were attributable to lack of understanding construction materials and NDT methods themselves. The intent of this paper is to address these concerns by describing the most common successful methods of NDT as applied to concrete structures