Combining supervised learning with color correlograms for content-based image retrieval
Jing Huang, S. Ravi Kumar, Mandar Mitra · 1997
The paper addresses how relevance feedback can be used to improve the performance of content-based image retrieval.We present two supervised learning methods: learning the query and learning the metric.We combine the leaming methods with the recently proposed color correlograms for image indexing/retrieval.Our results on a large image database of over 20,000 images suggest that these learning methods are quite effective for content-based image retrieval.