Line Segment-Based Clustering Approach With Self-Organizing Maps
| Autor: | G. Chamundeswari, G. P. S. Varma, Ch. Satyanarayana |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Self-organizing map
ComputingMethodologies_PATTERNRECOGNITION Line segment General Computer Science Computer science business.industry Computer Science::Computer Vision and Pattern Recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Artificial intelligence Cluster analysis business |
| Zdroj: | Journal of Information Technology Research. 14:33-44 |
| ISSN: | 1938-7865 1938-7857 |
| DOI: | 10.4018/jitr.2021100103 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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