TY  - JOUR
AU  - Miah, Elena
AU  - Liu, Kamrul
TI  - K-Means Clustering for Edge Detection
JO  - Open Access Journal of Engineering Applications
PY  - 2006
VL  - 30
IS  - 2
SP  - 377
EP  - 391
AB  - 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.
KW  - edge detection
KW  - k-means clustering
KW  - harmonic distortion
KW  - induction motor
KW  - error-correcting codes
SN  - 3105-7004
DO  - 10.55555/oajea.2006.3002.019
UR  - https://journal.bsaps.com/article/8336
ER  -