GIS Optical Partial Discharge Pattarn Identification Based on Two-dimensional Gabor Transform and Image Features

Gao, Qiang; Fang, Yuan; Yuan, Feng; Cheng, Dawei; Li, Zailin; Pan, Jia-Yu

doi:10.1109/aeero52475.2021.9708280

Cited by 1 publication

(1 citation statement)

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“…This study extracts image features by affecting color, shape, and textures. The test results of the study claimed that the image is processed effectively and accurately [53]. Venkatachalam et al discussed an innovative approach using Gabor filtering and Walsh-Hadamard transforms.…”

Section: E Hough Transform Based Methodsmentioning

confidence: 99%

An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)

Sharma,

Basheer

et al. 2023

IEEE Access

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Object formation is imperative to the recent computer vision, pattern recognition, healthcare, and automation applications. The objects are generated from images by defining edges and the segmentation process. This article introduced a novel method, Outer Totality Cellular Automata (OTCA), for defining actual and continuous edges of the image objects. The OTCA analysis nearby 25 neighbourhood pixels of all the pixels and generate a unique and efficient threshold. The proposed method has three primary functions, i.e. vitality, rule mapping, and improved morphological functions. The key objectives are image smoothing, neighbourhood analysis, defining game of life rule, and edges smoothing. Notably, the proposed method aimed to segment different coloured images, i.e., RGB, HSV, and YUV. The proposed method also aimed to produce more truthful results on blurred, reflected, shaded night vision images. The experimental process demonstrates using standard open-source datasets and validated using image quality assessment parameters, i.e., entropy, PSNR, SSIM, and MSE. The results claim 3% − 12% more structural analogous, factual, and accurate than existing classical methods and recent searches.

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Section: E Hough Transform Based Methodsmentioning

confidence: 99%