scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Parallel Image Processing Using Cellular Arrays

01 Jan 1983-IEEE Computer (IEEE)-Vol. 16, Iss: 1, pp 14-20
TL;DR: The basic techniques of image processing using two-dimensional arrays of processors, or cellular arrays, are reviewed and various extensions and generalizations of the cellular array concept are discussed and their possible implementations and applications are discussed.
Abstract: array computers are not new to image processing, but more refined techniques have led to broader implementations. We can now construct arrays with up to 128 x 128 processors. Nearly 25 years ago, Ungerl\"2 suggested a two-dimensional array of processing elements as a natural computer architecture for image processing and recognition. Ideally, in this approach, each processor is responsible for one pixel, or one element of the image, with neighboring processors responsible for neighboring pix-els. Thus, using hardwired communication between neighboring processors, local operations can be performed on the image, or local image features can be detected in parallel, with every processor simultaneously accessing its neighbors and computing the appropriate function for its neighborhood. Over the last two decades, several machines embodying this concept have been constructed. The Illiac 1113 used a 36 x 36 processor array (the Illiac IV used only an 8 x 8 array) to analyze \"events\" in nuclear bubble-chamber images by examining 36 x 36 \"windows\" of the images. In later machines, such as the CLIP,4 DAP,5 and Mpp,6 arrays of up to 128 x 128 processors were used and were applied blockwise to larger images. This article reviews the basic techniques of image processing using two-dimensional arrays of processors, or cellular arrays. It also discusses various extensions and generalizations of the cellular array concept and their possible implementations and applications. The term cellular array is used because these machines can be regarded as generalizations of bounded cellular automata, which have been studied extensively on a theoretical level. The relative merits of cellular arrays for image processing as compared to other architectures* are not discussed here; but they have been studied extensively for such purposes, on levels from theory to hardware. A cellular array (Figure 1) is a two-dimensional array of processors, or cells, usually rectangular, each of which can directly communicate with its neighbors in the array. Here, for simplicity, I assume that each cell is connected to its four horizontal and vertical neighbors. Each cell on the borders of the array then has only three neighbors, and each cell in the four corners of the array has only two. I also assume that a cell can distinguish its neighbors; i.e., it can send a different message to each neighbor, and when it receives messages from them, it knows which message came from which neighbor. To use a cellular array for image processing, we give …
Citations
More filters
Journal ArticleDOI
TL;DR: This paper provides a review of shape analysis methods, which play an important role in systems for object recognition, matching, registration, and analysis.

1,035 citations

Journal Article
TL;DR: Mitchell et al. as discussed by the authors presented results from an experiment similar to one performed by Packard (1988), in which a genetic algorithm is used to evolve cellular automata (CA) to perform a particular computational task.
Abstract: Author(s): Mitchell, Melanie; Hraber, Peter; Crutchfield, James P | Abstract: We present results from an experiment similar to one performed by Packard (1988), in which a genetic algorithm is used to evolve cellular automata (CA) to perform a particular computational task. Packard examined the frequency of evolved CA rules as a function of Langton's lambda parameter (Langton, 1990), and interpreted the results of his experiment as giving evidence for the following two hypotheses: (1) CA rules able to perform complex computations are most likely to be found near ``critical'' lambda values, which have been claimed to correlate with a phase transition between ordered and chaotic behavioral regimes for CA; (2) When CA rules are evolved to perform a complex computation, evolution will tend to select rules with lambda values close to the critical values. Our experiment produced very different results, and we suggest that the interpretation of the original results is not correct. We also review and discuss issues related to lambda, dynamical-behavior classes, and computation in CA. The main constructive results of our study are identifying the emergence and competition of computational strategies and analyzing the central role of symmetries in an evolutionary system. In particular, we demonstrate how symmetry breaking can impede the evolution toward higher computational capability.

474 citations

Journal ArticleDOI
TL;DR: The extent to which symmetry breaking and other impediments are general phenomena in any GA search is discussed, and four “epochs of innovation” in which new CA strategies for solving the problem are discovered by the GA are identified.

380 citations


Cites background from "Parallel Image Processing Using Cel..."

  • ...…by a breaking of the task s symmetries on the part of the GA The symmetry breaking results in a short term tness gain but ultimately prevents the discovery of the most highly t strategies We discuss the extent to which symmetry breaking and other impediments are general phenomena in any GA search...

    [...]

Journal ArticleDOI
TL;DR: Some shortcomings of the cellular-automaton formalism are discussed and some extensions and generalizations which may remedy these shortcomings are mentioned.

254 citations

Book
01 Jan 2004
TL;DR: Questions of particular interest include how images and image subsets are digitized; how geometric properties are defined for digitized sets; the computational complexity of computing them--in particular, whether they can be computed using simple (e.g., local) operations; characterizing image operations that preserve them; and characterizing digital objects that could be the digitizations of real objects that have given geometric properties.
Abstract: Digital geometry is the study of geometrical properties of subsets of digital images. If the digitization is sufficiently fine-grained, such properties can be regarded as approximations to the corresponding properties of the "real" sets that gave rise, by digitization, to the digital sets; but it is also important to define how the properties can be computed for the digital sets themselves. Questions of particular interest include how images and image subsets are digitized; how geometric properties are defined for digitized sets; the computational complexity of computing them--in particular, whether they can be computed using simple (e.g., local) operations; characterizing image operations that preserve them; and characterizing digital objects that could be the digitizations of real objects that have given geometric properties. Concepts that have been extensively studied include topological properties (connected components, boundaries); curves and surfaces; straightness, curvature, convexity, and elongatedness; distance, extent, length, area, surface area, volume, and moments; shape description, similarity, symmetry, and relative position; shape simplification and skeletonization.

249 citations

References
More filters
Journal ArticleDOI
Batcher1
TL;DR: The massively parallel processor (MPP) as discussed by the authors was designed to process satellite imagery at high rates, achieving 8-bit integer data, addition can occur at 6553 million operations per second (MOPS) and multiplication at 1861 MOPS.
Abstract: The massively parallel processor (MPP) system is designed to process satellite imagery at high rates. A large number (16 384) of processing elements (PE's) are configured in a square array. For optimum performance on operands of arbitrary length, processing is performed in a bit-serial manner. On 8-bit integer data, addition can occur at 6553 million operations per second (MOPS) and multiplication at 1861 MOPS. On 32-bit floating-point data, addition can occur at 430 MOPS and multiplication at 216 MOPS.

815 citations

Proceedings ArticleDOI
S. H. Unger1
06 May 1958
TL;DR: A stored program computer is described which can handle spatial problems by operating directly on information in planar form without scanning or using other techniques for transforming the problem into some other domain.
Abstract: The stored-program digital computer has been in existence for about a decade and has proven itself to be a powerful and versatile instrument. Roughly speaking, any solvable problem can be solved by a digital computer. At many tasks, such as the solution of systems of linear equations, these machines are thousands of times as fast as human beings.

194 citations

Journal ArticleDOI
TL;DR: The Pattern Articulation Unit is the first modular parallel processor which is capable of more reliable visual identification than part analog/part digital preprocessors of much less generality and potential virtuosity and can serve as a prototype to a new generation of parallel computers that will capitalize upon thin film and integrated semiconductor circuitry of the immediate future.
Abstract: This report describes the system design of an all-digital computer for visual recognition. One processor, the Pattern Articulation Unit (PAU), has been singled out for detailed discussion. Other units, in particular the Arithmetic Unit and the Taxicrinic Unit, are treated in reports listed in the bibliography. The PAU has been shown to be a processor of fundamentally new design-its logical organization has no analog in the central processing unit of existing computers. The PAU is the first modular parallel processor which because of its digital organization is capable of more reliable visual identification than part analog/part digital preprocessors of much less generality and potential virtuosity; is faster than any presently suggested alternative realizable today at comparable cost; and can serve as a prototype to a new generation of parallel computers that will capitalize upon thin film and integrated semiconductor circuitry of the immediate future.

164 citations

Journal ArticleDOI
S. H. Unger1
01 Oct 1959
TL;DR: Two types of pattern-processing problems are discussed in this paper and recognition and detection have been successfully carried out on an IBM 704 computer programmed to simulate a spatial computer (a stored-program machine comprised of a master control unit directing a network of logical modules).
Abstract: Two types of pattern-processing problems are discussed in this paper. The first, termed "pattern detection," consists of examining an arbitrary set of figures and selecting those having some specified form. The second problem, "pattern recognition," consists of identifying a given figure which is known to belong to one of a finite set of classes. This is the problem encountered when reading alphanumeric characters. Both recognition and detection have been successfully carried out on an IBM 704 computer which was programmed to simulate a spatial computer (a stored-program machine comprised of a master control unit directing a network of logical modules). One of the programs tested consisted of a recognition process for reading hand-lettered sans-serif alphanumeric characters. This process permits large variations in the size, shape, and proportions of the input figures and can tolerate random noise when it is well scattered in small specks. Programs for detecting L-shaped (or A-shaped) figures in the presence of other randomly drawn patterns have also been successfully tested.

155 citations