Blobworld is a system for image retrieval based on finding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions ("blobs") with associated color and texture descriptors. Querying is based on the attributes of one or two regions of interest, rather than a description of the entire image. In order to make large-scale retrieval feasible, we index the blob descriptions using a tree. Because indexing in the high-dimensional feature space is computationally prohibitive, we use a lower-rank approximation to the high-dimensional distance. Experiments show good results for both querying and indexing.