Аналіз Властивостей, Характеристик Та Результатів Застосування Новітніх Детекторів Для Визначення Особливих Точок Зображення

Gorokhovatsky, V. О.; Pupchenko, D. V.; Solodchenko, K. G.

doi:10.26906/sunz.2018.1.093

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Розглянемо математичне представлення застосування ORB та BRISK для класифікації зображень ВНП [16]. Припустимо, що у нас є певна множина 𝑍𝑍 = {𝑍𝑍 𝑗𝑗 } 𝑗𝑗=1 𝐽𝐽 ознак бази зображень, яку складають еталони (Z jеталон, Jчисло класів).…”

Section: таблиця 1 порівняльний аналіз характеристик зазначених алгор...unclassified

Approaches to the formation of an image database in the explosive ordnance identification system for further training of a neural network

Protsiuk,

Draglyuk,

Palamarchuk

et al. 2024

Communication, Informatization and Cybersecurity Systems and Technologies

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The use of unmanned aerial vehicles to detect explosive objects is a promising area of demining. Currently, a significant role in identifying detected objects remains with the operator (human). To solve the problem of identifying images of explosive objects, it is advisable to equip unmanned aerial vehicles or other robotic systems with appropriate software and hardware with built-in elements of artificial intelligence that would allow to recognize detected objects with a certain probability by their characteristic local features (shape/image, body material, body temperature) and classify them without operator participation. Recognition consists in calculating the relevance measure between the descriptions of the object and the reference, whose images are given as sets of descriptor vectors, and optimizing the values of this measure for the reference database. The article discusses the main algorithms (methods) for image identification and selects those that have higher performance and are built according to the binary type, which simplifies the calculation process and reduces costs. In general, the combination of ORB and BRISK descriptors gives better results, since it takes into account color distortion, poor lighting, noise, and different projections. The paper proposes approaches to forming a database of explosive ordnance images, which will further serve as an input layer for training a neural network to identify explosive ordnance. In the course of the work, a program code was written that makes it possible to test the performance of combined methods (algorithms) of image identification in terms of database formation, storage and testing.

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Section: таблиця 1 порівняльний аналіз характеристик зазначених алгор...unclassified

Approaches to the formation of an image database in the explosive ordnance identification system for further training of a neural network

Protsiuk,

Draglyuk,

Palamarchuk

et al. 2024

Communication, Informatization and Cybersecurity Systems and Technologies

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“…Another class of image comparison methods is featurebased. It consists of searching for specific image featurestypically descriptors -and matching them with a pair of images [9]. ORB (Oriented FAST and Rotated BRIEF) image descriptor detector was proposed in [10] as an alternative to previous known SIFT and SURF methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Image Pair Comparison for Near-duplicates Detection

Gorokhovatskyi¹,

Peredrii²

2023

IJC

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The paper describes the search for a solution to the image near-duplicate detection problem. We assume that there are only two images to compare and classify whether they are near-duplicates. There are some traditional methods to match pair of images, and the evaluation of the most famous of them in terms of the problem is performed in this research. The effective thresholds to separate near-duplicate classes are found during experimental modeling using the INRIA Holidays dataset. The sequence of methods is proposed to make the joint decision better in terms of accuracy. It is shown also that the accuracy of binary classification of the proposed approach for the combination of the histogram comparison and ORB descriptors matching is about 85% for both near-duplicate and not near-duplicate pairs of images. This is compared to the existing methods, and it is shown, that the accuracy of more powerful methods, based on deep learning, is better, but the speed of the proposed method is higher.

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Modern status of the problem of hallux valgus surgery HALLUX VALGUS (Review)

Liabakh¹,

Rudenko²

2020

HOTP

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Summary. The problem of hallux valgus (HV) surgery remains actual. There are some unresolved social and medical issues in particular: great widening of HV, patient’s unsatisfaction of cosmetic and functional results, imperfection of classifications, discrepancy between surgeon’s and patient’s expectation from surgery. The possibility of Manchester Grading Scale using can correctly bypass the methodological imperfection of classifications grounded on scialogical parameters. The conclusion was done about the necessity of comparative studies concerning to the effectiveness of surgical methods.

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Аналіз Властивостей, Характеристик Та Результатів Застосування Новітніх Детекторів Для Визначення Особливих Точок Зображення

Cited by 3 publications

References 7 publications

Approaches to the formation of an image database in the explosive ordnance identification system for further training of a neural network

Approaches to the formation of an image database in the explosive ordnance identification system for further training of a neural network

Image Pair Comparison for Near-duplicates Detection

Modern status of the problem of hallux valgus surgery HALLUX VALGUS (Review)

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