Pictorial Information Systems Research Articles

Russian

An ornamental and coloristic basis comprises the dominant ethnic determinant of Bashkir folk art. Within the structure of the development of modern ethnic design, the ornament is also one of the most proactive factors. Tamgas’ modular units, Turkic runic writing graphemes and traditional ornamental basic motifs together form a triad consisting of several dozen elementary, stylized graphical units and, as an aggregate, constitute the fundamental principle behind the entire pictorial information system of Eurasian Mongol–Turkic nomadic culture. Folk artists, while transforming them in various ways, have over the centuries created thousands of derivative variations. Identifying these well-established modification techniques of ornamental and Tamgas-type elements on the basis of comparative structural analysis provides us with new opportunities in the field of the creation of modern decorative compositions. The active application of graphical design software opens up limitless creative possibilities for the use of these traditional modification methods in the professional work of designers in various fields. A thorough theoretical study of the artistic heritage and creative development of ornamental and iconic structures’ transformation principles in schools will help in the comprehension of folk art traditions at a new level. Thus, the study of the abovementioned triad in this context provides great practical value for the successive development of regional ethnic design.

A Study on Mandelbrot Sets to Generate Visual Aesthetic Fractal Patterns

The fractal pattern is a highly visual aesthetic image. This article describes the generation method of Mandelbrot set to generate fractal art patterns. Based on the escape time algorithm on complex plane, the visual aesthetic fractal patterns are generated from Mandelbrot sets. The generated program development, a pictorial information system, is integrated through the application of Visual Basic programming language and development integration environment. Application of the development program, this article analyzes the shape of the fractal patterns generated by the different power orders of the Mandelbrot sets. Finally, the escape time algorithm has been proposed as the generation tools of highly visual aesthetic fractal patterns.

Research topics in pictorial databases

Pictures are natural and effective means of communication among people, computers, and robotics. A pictorial database is a collection of sharable pictorial data encoded in various formats. During the past several years, pictorial databases have attracted growing attention as an important component in building pictorial information systems as well as intelligent information systems. Eight research tasks are presented. They are comparing the numerical and the linguistic variable approaches, examining new linguistic hedges, studying the similarity of various similarity measures, investigating pictorial data compression techniques, performing pictorial data compression using array grammars, applying the entity‐relationship (ER) model to picture description; further investigating the relationship hierarchy for picture representation using ER diagrams, and extracting pictorial knowledge from pictorial databases. The research results may have a major impact on the development of object‐oriented pictorial databases.

Symbolic picture retrieval by relative-metric spatial relations

Symbolic pictures can be used for iconic indexing, spatial reasoning, and similarity retrieval in the design of intelligent image database systems. [S. K. Chang, C. W. Yan, Donald C. Dimitroff, and Timothy Arndt, IEEE Trans. Software Engineering 1988, 14, 681–688; S.-K. Chang, Principles of Pictorial Information Systems Design, Prentice-Hall, New York, 1989.] However, previous approaches to designing such systems usually ignore relative-metric information on symbolic pictures and cause several deficiencies in indexing, spatial reasoning, and retrieval. In our approach, we extract relative-metric information from symbolic pictures and use such information to help establish indexes based on an improvement from a minimal perfect hashing scheme. As a result, more accurate picture retrieval can be achieved through our indexing mechanism. Capabilities in spatial reasoning and query representation/processing are also improved. By utilizing relative-metric spatial relations, an image database system becomes more flexible and intelligent. ©2000 John Wiley & Sons, Inc.

Breadth-first search oriented symbolic picture representation for spatial match retrieval

To provide sufficient information for percepting symbolic objects among pictures from pictorial information systems, an efficient spatial data structure is needed to identify objects and to specify the spatial relationships among objects in a picture. In this paper, a new symbolic picture representation is proposed through the traversal of a quadtree corresponding to a given picture using breadth-first search and thus is called BFS string. An iconic indexing scheme for retrieving symbolic pictures based on the proposed BFS strings is presented and the algorithms introduced in the bin-tree oriented iconic indexing scheme by Chang and Lee (1998b) [Journal of Data and Knowledge Engineering 26 (2)]. is applied to the scheme for manipulating spatial relationships among objects. Compared with the bin-tree oriented scheme in storage complexity, experimental results show that the proposed BFS string requires less storage space when the picture has a great number of objects.

A Survey of Access Methods for Image Data

The feasibility of storing large amount of digital images and the pictorial-oriented nature of many applications have attracted much interest in pictorial information systems. An important issue in such systems is the efficient retrieval of image based on its contents. Supporting content-based retrieval of image data is a difficult problem and embraces different technologies including image processing, user interface design, and database management. To provide efficient content-based retrieval, efficient access methods based on image features are required. This paper presents a survey of indexing techniques that support content-based retrieval of images. In particular, we examine access methods for three types of image features, namely, object shape, semantic objects, and spatial relationships among semantic objects. For each image feature, we look at how various approaches represent and organize the image features and how they support similarity retrieval.

Image synthesis based on the recognition of 3‐D polyhedras

Abstract A methodology of synthesizing images from the point of view of considering the object's recognizability is developed. The viewing parameters determining the synthesized image are decided based on the recognizability of the object. An object is identified through the determination of its position and orientation. In this paper, it is shown that we cannot distinguish topographically similar objects from a single perspective. Thus, the threshold i, determined by a scheme developed here for model i, is used to check whether a candidate model is accepted. The procedures of synthesizing an image also consist of determining the lighting conditions. The direction of light source is so chosen that |i‘•n k1 – i‘ • nk2 | ≥ (1/K), where i’ is the opposite direction of light source, nk 1 and nk 2 are the normals of two visible neighboring surfaces, and K is the number of edges between the visible surfaces of an object. After the direction of the light source is obtained, the intensity of the light source is determined such that the differences between two visible neighboring planes should be greater than a threshold. Finally, all the concepts presented are illustrated through several examples given in this paper. The result may be applied to the icon representation of an object which represents an execution process or a filename in a pictorial information system.

Pictorial information retrieval using the random neural network

A technique is developed based on the use of a neural network model for performing information retrieval in a pictorial information system. The neural network provides autoassociative memory operation and allows the retrieval of stored symbolic images using erroneous or incomplete information as input. The network used is based on an adaptation of the random neural network model featuring positive and negative nodes and symmetrical behavior of positive and negative signals. The network architecture considered has hierarchical structure and allows two-level operation during learning and recall. An experimental software prototype, including an efficient graphical interface, has been implemented and tested. The performance of the system has been investigated through experiments under several schemes concerning storage and reconstruction of patterns. These schemes are either based on properties of the random network or constitute adaptations of known neural network techniques.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

GENERATING RECTANGLES USING TWO-DIMENSIONAL GRAMMARS WITH TIME AND SPACE COMPLEXITY ANALYSES

A two-dimensional grammar for generating all possible rectangles is presented and illustrated by examples. The time and space complexity analyses of this grammar together with a parallel context-free array grammar and a free grammar are also presented. Generating pictures using two-dimensional grammars appear to be a fertile field for further study. The study of two-dimensional grammars has useful applications in region filling. pattern recognition. robotics, pictorial information system design and related areas.

Pictorial knowledge representation using pictorial semantic networks

SUMMARYClassifications of pictures and pictorial knowledge are presented. Pictorial knowledge is divided into three classes – angular pictorial knowledge, side pictorial knowledge, and angular and side pictorial knowledge. A block diagram of these three pictorial knowledge classes and a pictorial knowledge transformation module is also presented with illustrative examples. Pictorial semantic networks which in terms of pictorial nodes, property nodes, “is a” links, “has property” links, and “if and only if” links are introduced. Transitivity, generalization, specialization, inheritance hierarchy, and knowledge transformation properties are stated and illustrated by examples. Triangular, quadrangular, and polygonal knowledge representation using pictorial semantic networks are presented. The concepts of deducible property nodes are also presented with illustrative examples. Additional facts can be established from pictorial semantic networks. Thus, pictorial semantic networks are a useful way to represent pictorial knowledge in domains that use well-established taxonomies to simplify problem solving in pictorial information systems. Pictorial semantic networks offer what appears to be a fertile field for future study. The results may have useful applications in knowledge representation, expert systems, artificial intelligence, knowledge - based systems, pictorial information systems and related areas.

IDECAP Interactive Pictorial Information System for Demographic and Environmental Planning Applications

AbstractIDECAP is a database type information system. It is different from regular database systems as the information is mainly presented via thematic maps displayed on a graphics screen. Retrieval of information is usually achieved by means of graphical interaction with these images. The system utilizes interaction techniques and systems software from interactive computer graphics, using vector graphic and colour raster graphic stations for output. The present databank contains data based on grids and polygonal data. The system is being applied, but not restricted, to the Dutch 1971 Census data and the 1978 land use data. It allows the mapping of grid variables against a topographic background. Areas of interest can be investigated in detail by zooming in on a window drawn on the graphics screen by the user. Maps can be adjusted by user‐definable class distributions shown in the form of histograms with standard deviations.

Algorithms for finding most unsymmetrical chromosome images

By using chromosome images as a framework, algorithms for finding most unsymmetrical images are presented and illustrated with examples. Sixteen angularly-not-equal and six angularly-not-equivalent most unsymmetrical chromosome images are found. A state-transition table, a state-transition diagram, and six most unsymmetrical chromosome images are also presented. The results may have useful applications in pattern recognition, picture understanding, information storage and retrieval, artificial intelligence, fuzzy-set theory, and pictorial information systems.

ALGORITHMS FOR FINDING CHOMSKY AND GREIBACH NORMAL FORMS FOR A FUZZY CONTEXT‐FREE GRAMMAR USING AN ALGEBRAIC APPROACH

Algorithms for the construction of the Chomsky and Greibach normal forms for a fuzzy context‐free grammar using the algebraic approach are presented and illustrated by examples. The results obtained in this paper may have useful applications in fuzzy languages, pattern recognition, information storage and retrieval, artificial intelligence, database and pictorial information systems.

An efficient algorithm for finding kleene closure of regular expression matrices

An efficient algorithm for finding the Kleene closure of regular expressions matrices or fuzzy regular expression matrices is presented and illustrated by examples. Properties of Kleene closure are also investigated. The results may have useful applications in automata theory, pattern recognition, and pictorial information systems.

Fuzzy Tree Automata and Syntactic Pattern Recognition

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

Pictorial Information Systems

A pictorial information system is a special type of information system supporting the manipulation, storage, retrieval, and analysis of pictorial data. In the past, pictorial information systems have usually been designed for specific applications. But recent advances in data base technology, computer graphics, and pictorial data structures have led to the development of more general-purpose systems. This special issue is a survey of several design aspects of these systems.