SCIENCE@home

Detection of Distorted Points on Images of Micro-Objects Based on The Properties and Peculiarities of the Wavelet - Transformation

I. Jumanov,R. Safarov,O. Djumanov

Published 2022 in 2022 International Russian Automation Conference (RusAutoCon)

ABSTRACT

Scientific and methodological foundations for the identification of images of unknown objects with the allocation of local areas of objects of interest, the use of traditional Gaussian, median filtering, fast Fourier transform, cosine transform, wavelet transforms, shift transforms, segmentation, factorization based on the use of redundancy of information structural components and their features. Mechanisms for detecting and correcting distorted points in fragment pictures have been developed based on the use of statistical, dynamic and neural network models. A wide range of mechanisms for filtering, segmentation, factorization, recognition and classification of images of non-stationary objects in conditions of a priori insufficiency, parametric uncertainty, and low reliability of information have been investigated and implemented. Operators of wavelet, shift and other transformations, color coding, visualization of objects with regulation of their formalized parameters are investigated. Tested realizations of the generalized mechanism of identification, recognition and classification of pictures of a human brain tumor have been tested, in particular, unicellular elements of the brain with and without pathology have been investigated. A software package for visualization, recognition, classification of images of unknown objects has been developed, the are carried out of which are carried out in conditions of a priori insufficiency, parametric uncertainty, and low reliability of information.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-13 of 13 references · Page 1 of 1

CITED BY