An Efficient Signature File Strategy for Similarity Retrieval from Large Iconic Image Databases

Abstract

In the previous signature-based approaches to retrieve symbolic pictures from a large iconic image database, only pictures of type-2 similarity are considered, where a picture A is of type-2 similarity with pictureB when both pictures have the same spatial relationship between any two objects in the pictures. When queries of objects, type-0 similarity and type-1 similarity are asked, signatures for objects, type-0 similarity and type-1 similarity are required. Note that a picture is of type-0 similarity when all the spatial category relationships of each object pair are the same to the query picture, and a picture is of type-1 similarity when the picture is of type-0 similarity and all the orthogonal relationships of each object pair are the same to the query picture. Although these four kinds of signatures can be constructed and stored in advance to speed up answering such kinds of queries as in the approach of Lee et al. [1], such a large signature file containing those four kinds of signatures really wastes space. In this paper, we first present the revised version of Y. I. Chang and Yang's bit-string-based access strategy [2], which constructs type-2 signatures. Based on the revised version, we then propose algorithms to dynamically convert those type-2 signatures into object signatures, type-0 signatures and type-1 signatures at run time so that we can answer queries of object similarity, type-0 similarity, type-1 similarity and type-2 similarity by storing only one type of signatures, i.e. the type-2 signatures. While in the Lee et al. signature file strategy based on the 2D B -string representation [1], they have to construct and store four types of signatures in the database to achieve the same goal. From our simulation, we show that our approach can provide a higher rate of a correct match and has a smaller storage requirement than the approach of Lee et al.