A Partition Metric for Clustering Features Analysis
| Data(s) |
07/12/2009
07/12/2009
2007
|
|---|---|
| Resumo |
A new distance function to compare arbitrary partitions is proposed. Clustering of image collections and image segmentation give objects to be matched. Offered metric intends for combination of visual features and metadata analysis to solve a semantic gap between low-level visual features and high-level human concept. |
| Identificador |
1313-0463 |
| Idioma(s) |
en |
| Publicador |
Institute of Information Theories and Applications FOI ITHEA |
| Palavras-Chave | #Partition #Metric #Clustering #Image Segmentation |
| Tipo |
Article |
