An Edge based Clustering Technique with Self-Organizing Maps

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G. Chamundeswari 1,* G. P. S. Varma 2 Ch. Satyanarayana 3

1. Jawaharlal Nehru Technological University Kakinada, Kakinada, A.P., India

2. SRKR Engineering College, Bhimavaram, A.P., India

3. Dept. of CSE, UCE, Jawaharlal Nehru Technological University Kakinada, Kakinada, A.P., India

* Corresponding author.


Received: 16 Nov. 2017 / Revised: 3 Dec. 2017 / Accepted: 7 Dec. 2017 / Published: 8 May 2018

Index Terms

Filter, edge, sub image, feature vector, neural network


Recently, artificial neural networks are fund to be efficiently used in clustering algorithms. So, the present paper focuses on the development of a novel clustering method based on artificial neural networks. The present paper uses an enhancement filter to enhance the segments in the input image. After this, the various sub images are generated and features are computed for each sub and edge image. Finally, the Self Organizing Map (SOM) is used for clustering process. The proposed novel method is evaluated with a database of 795 leaf images. Further various Probability Distributed Functions (PDFs) are used to evaluate the efficacy of the proposed method. The performance measures of the proposed method indicate the efficiency of the extended clustering method with SOM.

Cite This Paper

G. Chamundeswari, G. P. S. Varma, Ch. Satyanarayana, "An Edge based Clustering Technique with Self-Organizing Maps", International Journal of Information Technology and Computer Science(IJITCS), Vol.10, No.5, pp.30-39, 2018. DOI:10.5815/ijitcs.2018.05.03


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