. Increasing interest for configuration similarity is currently developing in the context of Digital Libraries, Spatial Databases and Geographical Information Systems. The corresponding queries retrieve all database configurations that match an input description (e.g., "find all configurations where an object x 0 is about 5km northeast of another x 1 , which, in turn, is inside object x 2 "). This paper introduces a framework for configuration similarity that takes into account all major types of spatial constraints (topological, direction, distance). We define appropriate fuzzy similarity measures for each type of constraint to provide flexibility and allow the system to capture real-life needs. Then we apply pre-processing techniques to explicate constraints in the query, and present algorithms that effectively solve the problem. Extensive experimental results demonstrate the applicability of our approach to images and queries of considerable size. 1. INTRODUCTION As opposed to visu...

Fuzzy set methods have been used to model and manage uncertainty in various aspects of image processing, pattern recognition and computer vision. High-level computer vision applications hold a great potential for fuzzy set theory because of its links to natural language. Linguistic scene description, a language-based interpretation of regions and their relationships, is one such application that is starting to bear the fruits of fuzzy set theoretic involvement. In this paper, we are expanding on two earlier endeavors. We introduce new families of fuzzy directional relations that rely on the computation of histograms of forces. These families preserve important relative position properties. They provide inputs to a fuzzy rule base that produces logical linguistic descriptions along with assessments as to the validity of the descriptions. Each linguistic output uses hedges from a dictionary of about thirty adverbs and other terms that can be tailored to individual users. Excellent results from several synthetic and real image examples show the applicability of this approach. Keywords Relative Positions, Force Histograms, Spatial Relations, Linguistic Descriptions, Scene Understanding, Fuzzy Logic. 2 1.

IN THIS thesis, a new methodology is presented which supports the efficient representation, indexing and retrieval of images by content. Images may be indexed and accessed based on spatial relationships between objects, properties of individual objects, and properties of object classes. In particular, images are first decomposed into groups of objects, called "image subsets", and are indexed by computing addresses to all such groups. All groups up to a predefined maximum size are considered. This methodology supports the efficient processing of queries by image example and avoids exhaustive searching through the entire image database.

Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation Picture Archiving and Communication Systems (PACS), and can be used as a diagnostic decision support tool and as a tool for medical research and training. This paper presents the architecture and features of I 2 C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I 2 C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which...

Large image databases have emerged in various applications in recent years. A prime requisite of these databases is the means by which their contents can be indexed and retrieved. A multilevel signature file called the Two Signature Multi-Level Signature File (2SMLSF) is introduced as an efficient access structure for large image databases. The 2SMLSF encodes image information into binary signatures and creates a tree structure that can be efficiently searched to satisfy a user’s query. Two types of signatures are generated. Type I signatures are used at all tree levels except the leaf level and are based only on the domain objects included in the image. Type II signatures, on the other hand, are stored at the leaf level and are based on the included domain objects and their spatial relationships. The 2SMLSF was compared analytically to existing signature file techniques. The 2SMLSF significantly reduces the storage requirements; the index structure can answer more queries; and the 2SMLSF performance significantly improves over current techniques. Both storage reduction and performance improvement increase with the number of objects per image and the number of images in the database. For an example large image databases, a storage reduction of 78 % may be achieved while the performance improvement may reach 98%.

Abstract—Configuration similarity is a special form of content-based image retrieval that considers relative object locations. It can be used as a standalone method, or to complement retrieval based on visual or semantic features. The corresponding queries ask for sets of objects that satisfy some spatio-temporal constraints, e.g., “find all triplets of objects ( I, P, Q), such that I is northeast of P, which is inside Q. ” Exhaustive processing (i.e., retrieval of the best solutions) of configuration similarity queries, in general, has exponential complexity and fast search for sub-optimal solutions is the only way to deal with the vast amounts of multimedia information in several real-time applications. In this paper we first discuss the utilization of nonsystematic search heuristics, based on genetic algorithms, simulated annealing and hill climbing approaches. An extensive experimentation with real and synthetic datasets reveals that hill climbing techniques are the best for the current problem; therefore, as a subsequent step we study the search space, and develop improved variations of hill climbing that take advantage of the special structure of the problem to enhance speed. The proposed heuristic methods significantly outperform systematic search when there is only limited time for query processing. Index Terms—Content-based retrieval, local search algorithms, spatial similarity. I.

Former layouts contain much of the know-how of architects. A generic and automatic way to formalize this know-how in order to use it by a computer would save a lot of effort and money. However, there seems to be no such way. The only access to the know-how are the layouts themselves. Developing a generic software tool to reuse former layouts you cannot consider every part of the architectual domain or things like personal style. Tools used today only consider small parts of the architectual domain. Any personal style is ignored. Isn't it possible to build a basic tool which is adjusted by the content of the former layouts, but may be extended incremently by modeling as much of the domain as desirable? This paper will describe a reuse tool to perform this task focusing on topological and geometrical binary relations. 1 Introduction The main idea of TOPO is to transfer the knowledge about useful topologies from former layouts to a new problem in order to correct, extend or detail the qu...

E#ective image retrieval by content from database requires that visual image properties are used instead of textual labels to recover pictorial data. Retrieval by image similarity given a template image is particularly challenging. The di#culty is to derive a similarity measure that combines shape, grey level patterns and texture in a way that closely conforms to human perception. In this paper a system is presented which supports retrieval by image similarity based on elastic template matching. The template can be both a 1D template modeling the contour of an object, and a 2D template modeling a part of an image with a significant grey level pattern. The retrieval process is obtained as a continuous interaction by which the original query of the user can be refined or changed on the basis of the results provided by the system. # 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

This paper deals with queries involving the retrieval of images that contain certain object configurations. Consider, for instance, that a user wants to “find all images where there exists a building adjacent to the west side of a park which is southwest and near a commercial center”. This query can be formulated as a constraint satisfaction problem (CSP) where the query variables are nodes of the corresponding constraint network and the image objects constitute the domain of each variable. The arcs of the network correspond to spatial constraints (e.g., adjacent ∧ west (X1,X2), southwest ∧ near (X2,X3)). Problems of the above nature are, in general, intractable. In addition, spatial constraints (e.g., southwest, near) lack universally accepted semantics and cannot always be modeled by crisp relations; a fact that further complicates query processing. This paper focuses on the development of effective methods that take advantage of the special structure of the spatial domain to achieve good average performance even for large images and queries.

D strings is one of a few representation structures originally designed for use in an IDB environment. In this chapter, a generalized approach for 2-D string based indexing, which avoids the exhaustive search through the entire database of previous 2-D string based techniques, is proposed. The classical framework of representation of 2-D strings is also specialized to the cases of scaled and unscaled images. Index structures for supporting retrieval by content, utilizing the 2-D string representation framework, are also discussed. The performance of the proposed method is evaluated using a database of simulated images and compared with the performance of existing techniques of 2-D string indexing and retrieval. The results demonstrate a very significant improvement in retrieval performance.