Optimization of identification of micro-objects based on morphological and brightness characteristics of image points

Жуманов, И.И., Сафаров, Р.А., Джуманов, О.И.

Рақамли технологияларнинг назарий ва амалий масалалари · 2025-yil

Annotatsiya

A methodology has been developed for optimizing the identification, recognition, and classification of micro-objects based on dynamic models combined with neural networks with tools for filtering impulse interference and noise, foreign particles, and other defects of image points; the methods and models of which are used in the systems of palynology, ecology, environmental protection, medicine, and other fields of knowledge. Identification mechanisms have been developed, including tools for contour extraction, segmentation, obtaining segment boundaries with hard and soft thresholds, and filtering using morphological characteristics of the image. Estimates of identification errors due to inadequacy of approximation, interpolation, and extrapolation of the image contour have been obtained. A software package for recognizing and classifying images of micro-objects has been developed, in which cubic, biquadratic, and interpolation spline functions and wavelet transformation have been synthesized.

Maqola ma’lumotlari
MualliflarЖуманов, И.И., Сафаров, Р.А., Джуманов, О.И.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
Nashr sanasi2025-04-06
Jild8
Son1
Betlar105-113
TilRus
DOI10.62132/ijdt.v8i1.238

Kalit so‘zlar

изображение, микрообъект, идентификация, распознавание, классификация, фильтрация, эффективность, программный комплекс, image, micro-object, identification, recognition, classification, filtering, efficiency, software package

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