Texture Segmentation Using Gabor Filter And hadamard Transform With Small Space Analysis, Texture Frequency, Non-Linear Filtering, And Postprocessing

Kaaviya; Ponharieesh Krishnakumar; Rajakumaran Jayaraman; Sakthi Dinesh Pounraj

doi:10.2991/978-94-6463-250-7_19

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Texture Segmentation Using Gabor Filter And hadamard Transform With Small Space Analysis, Texture Frequency, Non-Linear Filtering, And Postprocessing

Authors

Kaaviya¹^{, *}, Ponharieesh Krishnakumar², Rajakumaran Jayaraman³, Sakthi Dinesh Pounraj⁴

¹dept. of ECE, Panimalar Engineering College, Chennai, India

²dept. of ECE, Panimalar Engineering College, Chennai, India

³dept. of ECE, Panimalar Engineering College, Chennai, India

⁴dept. of ECE, Panimalar Engineering College, Chennai, India

^*Corresponding author.

Corresponding Author

Kaaviya

Available Online 17 October 2023.

DOI: 10.2991/978-94-6463-250-7_19 How to use a DOI?
Keywords: -texture frequency; small space analysis; non-linear filtering and post processing
Abstract: -An innovative texture segmentation method based on Gabor filters and Hadamard transforms is proposed in this paper together with small space analysis, texture frequency, non-linear filtering, and post-processing. Using Gabor filters, texture features are extracted and the dimensionality of feature vectors is reduced using small space analysis. A texture frequency histogram represents the texture frequency of each Gabor filter response. Based on the histogram, support vector machine classifiers are used to segment textures. Non-linear filtering techniques and post-processing techniques are employed to enhance texture information and refine segmentation results. Experimental results on several texture datasets demonstrate that the proposed method out performs state-of-the-art texture segmentation methods in terms of accuracy and robustness. The proposed method has promising applications in medical image analysis, remote sensing, and industrial quality control.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 6th International Conference on Intelligent Computing (ICIC-6 2023)
Series: Advances in Computer Science Research
Publication Date: 17 October 2023
ISBN: 10.2991/978-94-6463-250-7_19
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-250-7_19 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Kaaviya
AU  - Ponharieesh Krishnakumar
AU  - Rajakumaran Jayaraman
AU  - Sakthi Dinesh Pounraj
PY  - 2023
DA  - 2023/10/17
TI  - Texture Segmentation Using Gabor Filter And hadamard Transform With Small Space Analysis, Texture Frequency, Non-Linear Filtering, And Postprocessing
BT  - Proceedings of the 6th International Conference on Intelligent Computing (ICIC-6 2023)
PB  - Atlantis Press
SP  - 101
EP  - 107
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-250-7_19
DO  - 10.2991/978-94-6463-250-7_19
ID  - 2023
ER  -

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