July 1987 - Vol. 30 No. 7
Features
Recently developed word processing software can correctly format the cursive, interacting letters of the Arabic script. Moreover, new layout procedures can automatically intermix right-to-left Arabic writing with left-to-right text in European or other languages.
Spanish is a language with very precise and regular orthographic rules. A syllabication algorithm strictly based on syntactic analysis, not requiring any semantic knowledge, is presented and further extended to include hyphenation. Algorithms are presented as pattern matching schemata, and efficient implementations are considered.
The tea-leaf reader algorithm: an efficient implementation of CRC-16 and CRC-32
The tea-leaf reader CRC algorithms are error-detection algorithms that use a look-ahead table to increase execution speed.
The quadcode and its arithmetic
The quadcode is a hierarchical data structure for describing digital images. It has the following properties: (1) straightforward representation of dimension, size, and the relationship between an image and its subsets; (2) explicit description of geometric properties, such as location, distance, and adjacency; and (3) ease of conversion from and to raster representation. The quadcode has applications to computer graphics and image processing because of its ability to focus on selected subsets of the data and to allow utilization of multiple resolutions in different parts of the image. A related approach is the quadtree. Samet recently presented a thorough survey of the literature in that field [7]. Gargantini [2] and Abel and Smith [1] presented linear quadtrees and linear locational keys that are efficient labeling techniques for quadtrees. In those papers the geometric concepts of the image are discussed by using the tree as an interpretive medium, and the approaches and procedures are based on traversal of the nodes in the tree. In this paper we present the quadcode system, which is a direct description of the image, and discuss the geometric concepts in terms of the coded images themselves.
Adjacency detection using quadcodes
A method is presented for determining whether two given regions are adjacent, and for finding all the neighbors of different sizes for a given region. Regions are defined as elementary squares of any size. In a companion paper [2], we introduce the quadcode and discuss its use in representing geometric concepts in the coded image, such as location, distance, and adjacency. In this paper we give a further discussion of adjacency in terms of quadcodes. Gargantini [1] discussed adjacency detection using linear quadtrees. Her discussion was applied to pixels, and a procedure was given to find a pixel's southern neighbor only. This paper considers elementary squares of any size, and gives procedures for both aspects of the problem: for determining whether two given regions are adjacent, and for finding all the neighbors of different sizes for a given region.
