TY - JFULL AU - Luciano Nieddu and Giuseppe Manfredi PY - 2010/11/ TI - A Constrained Clustering Algorithm for the Classification of Industrial Ores T2 - International Journal of Industrial and Manufacturing Engineering SP - 1112 EP - 1117 VL - 4 SN - 1307-6892 UR - https://publications.waset.org/pdf/15142 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 46, 2010 N2 - In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores. ER -