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As in conventional database management systems (DBMSs), to allow users to efficiently access and retrieve data objects, a multimedia database management system (MMDBMS) must employ an effective access method such as indexing and hashing. This paper provides a survey of tree-based multidimensional indexing techniques for MMDBMSs that maintain image data represented as feature vectors. These techniques support such data while maintaining desirable characteristics of a B-tree, an index structure most commonly used in traditional DBMSs. In this survey, we provide descriptions of each tree as well as give examples of the different data organization schemes. We also describe the advantages and disadvantages of using each technique. In addition, we provide classifications of the trees using several different properties. These classifications should assist researchers in identifying the strengths and weaknesses of any new indexing technique they develop as well as help users determine the most appropriate data structure for their applications.

Typically, multimedia database management systems process content-based image retrieval queries by extracting a set of features from each data object as it is inserted into the underlying database. By expressing queries that are based upon these features, users are able to retrieve the data objects back from the database. Previous research has demonstrated that one method of improving the effectiveness of similarity searches in such systems is to augment the underlying database with a set of edited images to allow more flexible matching. Space can be saved by storing the additional images as sequences of editing operations instead of as large binary objects. This paper proposes an approach for processing retrieval queries in such an environment and presents the results of a performance evaluation demonstrating the effectiveness of the approach.

Many current multimedia database management systems perform content-based retrieval of images by extracting a set of features from each data object inserted into the underlying database. This allows users to search the database for images that are similar to an input query image where the similarity is determined by comparing the previously extracted features. Thus, the ability of the system to compare images depends upon the features it can extract from them. This also means that the system may fail to correctly match one of its stored images to the query image if their corresponding features do not sufficiently match. One approach to minimize the occurrences of these situations is to add modified versions of the stored image to the database and attempt to match the query image to any one of them. This paper discusses the advantages and applicability of this approach.

In order to improve the robustness of systems that perform similarity searching, it may be necessary to augment a collection of images in a Multimedia DataBase Management System (MMDBMS) with an additional set of edited images. Previous research has demonstrated that space can be saved in such a system by storing the edited images as sequences of editing operations instead of as large binary objects. The existing approaches for performing similarity searching in an MMDBMS, however, typically assume that the data objects are stored as binary objects. This paper proposes algorithms for performing colour-based similarity searches of images stored as editing operations and provides a performance evaluation illustrating their respective strengths and weaknesses.

Many current multimedia database management systems perform content-based retrieval of images by extracting the values of various features from every object stored in their system. This can be time-consuming, especially if extracting the features requires a human to analyze each object. This process can be minimized in multimedia database systems that store images as a sequence of editing operations, called specifications, instead of the usual binary format. This paper discusses the advantages and applicability of such systems and the issues that must be resolved in order to develop them.