A Novel Fast Iterative Parallel Thinning Algorithm

Ma, Jun; Ren, Xunhuan; Yurevich, Tsviatkou Viktar

doi:10.1145/3448823.3448836

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…In recent three years, two new methods under this category have been proposed: FPSA [7] and SPSA [8] methods. The FPSA method is first proposed in [9], and further presented and discussed in [7]. In the FPSA method, 13 different templates are included, whereas in the SPSA method, four different templates are used.…”

Section: Types Of Denoising Techniquesmentioning

confidence: 99%

Survey of Noise-Against Techniques for Extracting Stable Skeleton

Liu,

Ma,

Ren

et al. 2023

J. Phys.: Conf. Ser.

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Stable skeletons are promising as a compact, concise, and efficient descriptor since they can reflect much critical information about the original object, such as topology, connectivity, etc. However, extracting stable skeletons from images is very challenging since most existing skeleton extraction methods, also named skeletonization methods in some literature, are sensitive to noise, which limits the application of the skeletons in the recognition field. Many denoising methods have been proposed to extract stable skeletons to overcome this problem. However, up to now, there are few review papers to conclude these denoising methods and present their pros and cons. Therefore, In this paper, we survey existing denoising techniques for extracting stable skeletons from images. We first categorize these denoising methods, analyze their core idea, and then present their pros and cons for comparison. In addition, we also offer the potential research direction and possibly challenge.

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Section: Types Of Denoising Techniquesmentioning

confidence: 99%

Survey of Noise-Against Techniques for Extracting Stable Skeleton

Liu,

Ma,

Ren

et al. 2023

J. Phys.: Conf. Ser.

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Promising Research and Development Results in the Field of Image and Speech Signal Processing

Likhachov,

Ma,

Petrovsky

et al. 2024

Doklady Belorusskogo gosudarstvennogo universiteta informatiki

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An analysis of the prospects for the development of technologies for processing images and speech signals is presented. The main results in these areas obtained in recent years in the relevant scientiﬁc schools of Belarusian State University of Informatics and Radioelectronics are presented. It is shown that the use of machine learning technologies in combination with methods of digital processing of images and speech signals can signiﬁcantly increase the eﬃciency of systems for their recognition and classiﬁcation.

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A Novel Fast Iterative Parallel Thinning Algorithm

Cited by 2 publications

References 12 publications

Survey of Noise-Against Techniques for Extracting Stable Skeleton

Survey of Noise-Against Techniques for Extracting Stable Skeleton

Promising Research and Development Results in the Field of Image and Speech Signal Processing

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