Yutaka Ohsawa

A new tree type data structure with homogeneous nodes suitable for a very large spatial database

A new dynamic data structure for spatial retrieval called a GBD tree is proposed. The GBD tree is systematically constructed using homogeneous nodes with a small amount of extra data called a DZ expression which plays an important role in efficient multiway recursive division of N-dimensional space. On the GBD tree, CPU cost during insertion and deletion is much smaller than on an R-tree, while attaining higher spatial retrieval efficiency.<<ETX>>

A database capture system for mechanical drawings using an efficient multidimensional graphical data structure

A novel type of system for understanding mechanical drawings, named the AI-MUDAMS Recognizer, is proposed and discussed. In the system, contour vector data and core vector data for objects in the drawing image are first extracted and stored in a multidimensional graphical database. All the geometrical operations required for feature extraction and structural understanding of mechanical drawings are performed very efficiently and flexibly using only the vector data (rather than image data) in the database. Rule-based artificial intelligence techniques are used for structural understandings. Experimental results confirm the high speed of the systems and its ability to understand mechanical drawings.<<ETX>>

A color video image quantization method with stable and efficient color selection capability

Color video images have become a very important media in communication. This has increased the necessity of displaying and handling color video images on various types of computers. In computerized color image processing, most color images are represented by 24 bits per pixel. Such images usually contain a lot of redundancy and require a large amount of space to be stored. Furthermore, they require expensive full color display devices, so that many general-purpose computers which have only colormap display devices are not capable of displaying them. In order to lower the display and the storage cost, color image quantization algorithms are needed to reduce the number of colors in original images. The authors propose a color quantization method for video images which efficiently generates color quantized video images with stable color allocations.<<ETX>>

Drawing image understanding framework using state transition models

A flexible drawing understanding system with state transition models is proposed. The drawing processor AI-Mudams (written in C) is used as the token extractor in the embodiment discussed. Given drawing images are converted efficiently to suitable geometrical primitives, such as contour vectors, core vectors, dots loops, or, in some cases, primitives with semantics (road line, or house etc.). The understanding system kernel is implemented in Prolog, and the geometrical evaluator is also prepared in C for checking basic geometrical situations, including shape, geometrical relations, and allocations. This understanding kernel accepts the individual state transition rules corresponding to individual drawing images and recognition targets and realizes understanding in the form of bottom-up and top-down state transition. Experiments on different types of drawings reveal that the framework is flexible and effective for various kinds of drawing image.<<ETX>>

Data Structure for Multilayer N-Dimensional Data Using Hierarchical Structure

Data such as vectors, points and symbols of maps and facilities location maps are classified into layers and managed according to such attributes as roads, houses, and facilities. In editing a diagram, range searchings and neighborhood searching frequently are made, where the objects of search are the data in a number of layers. When such multidimensional data classified into layers (called multilayer data) are managed by the conventional multidimensional data structure, a problem occurs in that the retrieval efficiency varies greatly depending on the number of considered layers. This paper proposes the ML structure (multi-layered structure), which is a new managing structure for the multilayer data based on a tree structure. In ML structure, the node structure is extended so that data can be stored not only in the terminal node of the tree but also in the internal node. A layer management mechanism is added to each node. It is arranged that the data of the layer with small number of data are placed close to the root of the tree structure. As a result, a satisfactory performance with small variation in the retrieval efficiency is realized, even if a range searching is made for a particular layer, or for a number of layers. This paper describes the construction of ML structure, method of data management, and searching. It is shown by experiment that the data management and searching by ML structure is effective for the multilayer data.

An efficient data management method for spatial objects using MD-tree-experimental evaluation and comparisons

An efficient spatial data management method for non-zero size spatial objects, called R(Region)MD-tree, is proposed. In this method, a graphic object in an N-dimensional space is represented as a point in a 2*N dimensional space by the centroid and the extension in each axial direction. The point data are managed by the MD-tree after applying the coordinate transformation. The point location problem or range searching in the original N-dimensional space are carried out by the hyper-rectangular range searching to the point data in the 2*N dimensional space. In this representation and data management, data objects are sorted and classified according to not only the location but also the size of the data. By the simulation experiments, the performances and efficiencies of the RMD-tree are compared with the conventional MD-tree and the R-tree. As the data objects become larger, the RMD-tree is superior in the searching speed by 2 approximately 4 times to the conventional ones, and the performances are almost comparable even if the objects are points or small graphic data.<<ETX>>

A new line data management structure suitable for geometrical retrievals based on spatial relations

With the recent widespread application of computer graphics, a management system for graphic data is required which is suited to interactive processing. This paper discusses the management structure for the line data, which can realize a retrieval in an efficient way according to the spatial relations. The dynamic data management structure called the BD time, which was developed by the authors for the multidimensional point data management, is employed. In the proposed system, the BD tree is modified into a form (nonpacket type) suited to high-speed processing, and is extended to suit the line data. In this system, the segment is managed by its centroid and the circumscribed quadrilateral. The BD tree is composed of a set of centroids, where each node has information concerning the circumscribed quadrilaterals for all segments in the subtree. The retrieval is made efficient by the information concerning the circumscribed quadrilateral. In this paper, the data structure for the line data management is discussed first. Then various retrieval algorithms which depend on the spatial relations according to each application are discussed in detail. Finally, the usefulness of the proposed data structure is demonstrated by a retrieval experiment of actual geographical data.

Pattern Data representation and management in image database systems

Data representation and management in the image database system are discussed. It is pointed out first that both efficiency of representation (amount of data) and the efficiency of processing and retrieval are important in the representation and management of data. From this viewpoint, various kinds of image and graphics representations are discussed, arriving at the viewpoint of “management of M-dimensional data in N-dimensional space.” The point data (0 in N data) and the N-dimensional image data (N in N data) are considered. Various kinds of data structures such as KD tree, KDB tree, 2N partition tree and linear tree, are discussed and analyzed from the viewpoint of the preceding two characteristics. Especially, a tree-type data structure (called BD tree) is proposed where the N-dimensional rectangular region is used as the partition key. The structure and the performance are discussed indicating that the performance is better than in other structures. Examples of applications of the proposed data structure in the image database are discussed, as well as the possibilities of future applications.

An n‐dimensional region data management system using combined tree structures

In this paper we describe management system for region data using tree structures. Though the region data are divided into spatial data and alpha-numerical data, we are primarily concerned with the management of spatial data. In the proposed method the cellular data obtained by partitioning them into equally spaced meshes (the cells have regional IDs as values) are managed by using combined two-step binary tree structures. First, the three structures of the first step (primary structures) are constructed with the following procedure. (1) The object plane is recursively partitioned into two equal parts alternating vertically and horizontally, so that the number of kinds of regions contained in a small rectangle is two or less. (2) This partition procedure is represented by using a tree structure with two children (degree 2). Also, a secondary structure serves to distinguish the patterns of two regions in a rectangle given by a leaf of the primary structure and the representation by a simplified binary tree is used. The tree structures have the following characteristics. (1) Since global data on the whole object plane are obtained by the primary structure, range search can be conducted efficiently. (2) By using the simplified binary tree representation for the secondary structures, the total number of nodes is reduced to less than one half of that in an ordinary binary tree representation. (3) Since the operations for searching or overlaying are simplified, they can be executed at high speed.