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Texture analysis using Horadam Polynomial coefficient estimate for the class of Sakaguchi kind function

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NIAID Data Ecosystem2026-03-14 收录
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We designated the variable "A" as the image of a closed palm's input. We analyzed the GLCM matrix of the original image using an internal command. We assessed the same quality indicators, including contrast, correlation, energy, homogeneity, and entropy. The variables "a," "b," and "c" are initialized as the first three coefficients of the Horadam Polynomial estimations and are taken into account at various angles from "h1" to "h8," or respectively 180, 90, 0, 270, 45, 135, and "225." h1 to h8 convoluted with the original image and quality metrics are investigated.

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2023-02-14
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