Methods for Improving Image Quality for Contour and Textures Analysis Using New Wavelet Methods

Dumitrescu, Cătălin; Răboaca, Maria Simona; Felseghi, Raluca‐Andreea

doi:10.3390/app11093895

Cited by 4 publications

(2 citation statements)

References 38 publications

(28 reference statements)

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“…If eighteen equalizing curves are used for image recognition, the time savings of the developed method compared to the traditional one will be 3,6 times. This algorithm allows you to process images in real time, like similar methods [21][22][23].…”

Section: Compression Of Color and Grayscale Images With Smooth Transi...mentioning

confidence: 99%

Research on graphic data formats for compact representation and comparison of images

Gertsiy

2024

TST

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This article investigates common methods of lossy and lossless compression of graphic information. The advantages and disadvantages of compression methods are identified as a result of the research. A comparative analysis of the main capabilities of graphic information compression methods is conducted. The relevance lies in the efficient transmission, processing, and storage of graphic information, as large data volumes require increased network bandwidth and significant resources for data storage. The practical significance lies in solving the task of effectively reducing data sizes by applying well-known compression methods. Based on the study of graphic data formats, the development of algorithms for the computational scheme of "precise" processing of halftone images for pattern recognition is presented. Such a scheme rewrites a multigradient image into a three-level representation and implements a balancing procedure, which allows forming image features in a more compact form and computing the correlation function faster. The effectiveness of using developed methods of compact image representation with correlation comparison of balancing curves is demonstrated compared to traditional correlation comparison of images.

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Section: Compression Of Color and Grayscale Images With Smooth Transi...mentioning

confidence: 99%

Research on graphic data formats for compact representation and comparison of images

Gertsiy

2024

TST

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“…BCI systems have a wide range of applications from quite simple to complex. There are BCI applications for spelling, simple computer games, wheelchair control, internet browsing or in a virtual environment [40,41]. Usually, applications are specially built for a certain type of BCI, being part of an integrated system.…”

Section: Introductionmentioning

confidence: 99%

Using Brain-Computer Interface to Control a Virtual Drone Using Non-Invasive Motor Imagery and Machine Learning

2021

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In recent years, the control of devices “by the power of the mind” has become a very controversial topic but has also been very well researched in the field of state-of-the-art gadgets, such as smartphones, laptops, tablets and even smart TVs, and also in medicine, to be used by people with disabilities for whom these technologies may be the only way to communicate with the outside world. It is well known that BCI control is a skill and can be improved through practice and training. This paper aims to improve and diversify signal processing methods for the implementation of a brain-computer interface (BCI) based on neurological phenomena recorded during motor tasks using motor imagery (MI). The aim of the research is to extract, select and classify the characteristics of electroencephalogram (EEG) signals, which are based on sensorimotor rhythms, for the implementation of BCI systems. This article investigates systems based on brain-computer interfaces, especially those that use the electroencephalogram as a method of acquisition of MI tasks. The purpose of this article is to allow users to manipulate quadcopter virtual structures (external, robotic objects) simply through brain activity, correlated with certain mental tasks using undecimal transformation (UWT) to reduce noise, Independent Component Analysis (ICA) together with determination coefficient (r2) and, for classification, a hybrid neural network consisting of Radial Basis Functions (RBF) and a multilayer perceptron–recurrent network (MLP–RNN), obtaining a classification accuracy of 95.5%. Following the tests performed, it can be stated that the use of biopotentials in human–computer interfaces is a viable method for applications in the field of BCI. The results presented show that BCI training can produce a rapid change in behavioral performance and cognitive properties. If more than one training session is used, the results may be beneficial for increasing poor cognitive performance. To achieve this goal, three steps were taken: understanding the functioning of BCI systems and the neurological phenomena involved; acquiring EEG signals based on sensorimotor rhythms recorded during MI tasks; applying and optimizing extraction methods, selecting and classifying characteristics using neuronal networks.

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Design of Practical Photogrammetry Technique for Unmanned Aerial Vehicle Application

Kumari,

Dubey

2023

2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)

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Methods for Improving Image Quality for Contour and Textures Analysis Using New Wavelet Methods

Cited by 4 publications

References 38 publications

Research on graphic data formats for compact representation and comparison of images

Research on graphic data formats for compact representation and comparison of images

Using Brain-Computer Interface to Control a Virtual Drone Using Non-Invasive Motor Imagery and Machine Learning

Design of Practical Photogrammetry Technique for Unmanned Aerial Vehicle Application

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