K-Means Clustering for Edge Detection
Elena Miah
Corresponding
Military Institute of Science and Technology
Kamrul Liu
Indian Institute of Technology Madras
Abstract
Industrial partners have repeatedly identified edge detection as the principal obstacle to improving cement manufacturing. An iterative scheme built upon k-means clustering was developed to handle the coupling between variables. The classification scheme achieved an accuracy of 25% on the test data. The proposed approach can be incorporated into existing design procedures with little additional effort.
Keywords:
edge detectionk-means clusteringharmonic distortioninduction motorerror-correcting codes
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