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Line Segment-Based Clustering Approach With Self-Organizing Maps

Line Segment-Based Clustering Approach With Self-Organizing Maps

G. Chamundeswari, G. P. S. Varma, C. Satyanarayana
Copyright: © 2021 |Volume: 14 |Issue: 4 |Pages: 12
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781799860037|DOI: 10.4018/JITR.2021100103
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MLA

Chamundeswari, G., et al. "Line Segment-Based Clustering Approach With Self-Organizing Maps." JITR vol.14, no.4 2021: pp.33-44. http://doi.org/10.4018/JITR.2021100103

APA

Chamundeswari, G., Varma, G. P., & Satyanarayana, C. (2021). Line Segment-Based Clustering Approach With Self-Organizing Maps. Journal of Information Technology Research (JITR), 14(4), 33-44. http://doi.org/10.4018/JITR.2021100103

Chicago

Chamundeswari, G., G. P. S. Varma, and C. Satyanarayana. "Line Segment-Based Clustering Approach With Self-Organizing Maps," Journal of Information Technology Research (JITR) 14, no.4: 33-44. http://doi.org/10.4018/JITR.2021100103

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Abstract

Clustering techniques are used widely in computer vision and pattern recognition. The clustering techniques are found to be efficient with the feature vector of the input image. So, the present paper uses an approach for evaluating the feature vector by using Hough transformation. With the Hough transformation, the present paper mapped the points to line segment. The line features are considered as the feature vector and are given to the neural network for performing clustering. The present paper uses self-organizing map (SOM) neural network for performing the clustering process. The proposed method is evaluated with various leaf images, and the evaluated performance measures show the efficiency of the proposed method.

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