A Spatial Similarity Measure for Image Database Applications
Abstract
Image Retrieval has been considered as an important task in many application areas such as Geographic Information Systems and Computer-Aided Design. Facilitating retrieval of images based on their similarity to a specified image is a desirous feature of a retrieval scheme for an image database. Providing a suitable means for expressing spatial relationships in a query often improves the ease of specifying it. In this report, we propose a similarity retrieval algorithm for use in retrieval by spatial similarity. We also describe the generation of a test bed of images and the user interface development. The proposed method has been applied to a test bed of images comprising of floor and furniture layout designs. Each layout design is generated as an image consisting of several objects such as sofa, chair, and table. The dissimilarity between images is based on the notion of distance. The Euclidean distance is computed between the centroids of the matching pairs of constituent objects in both the images. The sum of all such distances plus a suitable penalty for non matching objects is a quantitative measure of spatial similarity. The experimental results obtained using the spatial similarity algorithm quite well agree with our intuitive ranking of the images in the collection. Image Databases, Spatial Databases.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 30, 1992
- Accession Number
- ADA251572
Entities
People
- Dwayne Carr
- V. N. Gudivada
- Vijay V. Raghavan
Organizations
- Jackson State University