A description is given of the HMESH architecture, a modified broadcast-bus VLSI architecture consisting of an N multiplied by N mesh connected structure and a hierarchy of broadcast buses in each row and in each colum...
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ISBN:
(纸本)0818608048
A description is given of the HMESH architecture, a modified broadcast-bus VLSI architecture consisting of an N multiplied by N mesh connected structure and a hierarchy of broadcast buses in each row and in each column such that every bus has k processing.elements (PEs). That is, in any row or column, in the first level there are N/k buses with groups of k PEs connected to each bus. One PE from each of these groups is connected to second level of buses in a similar manner. This is recursively done until there are k PEs left, connected by a broadcast bus. With this architecture the authors show that many problems with applications to imageprocessing.and pattern analysis can be solved in O(log N) time.
A real-time architecture for the corner-turn transposition algorithm is proposed that uses the inherent parallelism and pipelining of the algorithm. A fundamental cell is defined that represents a matrix element and i...
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A real-time architecture for the corner-turn transposition algorithm is proposed that uses the inherent parallelism and pipelining of the algorithm. A fundamental cell is defined that represents a matrix element and is capable of handling data B bits in width. The cells are connected in a pipelined fashion along the rows (columns) of the matrix with interconnection between adjacent rows (columns) in a serpentine organization. The architecture is simple in structure and has local interconnection of the elements, which eliminates communication problems and achieves a high throughput as I/O transfers are eliminated. It is easily implementable in VLSI and has a minimum pin-out (2B plus 4 pins). It has a commendable cost/performance ratio and has wide applications in real-time imageprocessing.
Component labelling is an important part of region analysis in imageprocessing. Component labelling consists of assigning labels to pixels in the image such that adjacent pixels are given the same labels. There are v...
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Component labelling is an important part of region analysis in imageprocessing. Component labelling consists of assigning labels to pixels in the image such that adjacent pixels are given the same labels. There are various approaches to component labelling. Some require random access to the processed image; some assume special structure of the image such as a quad tree. algorithms based on sequential scan of the image are attractive to hardware implementation. One method of labelling is based on a fixed size local window which includes the previous line. Due to the fixed size window and the sequential fashion of the labelling process, different branches of the same object may be given different labels and later found to be connected to each other. These labels are con-sidered to be equivalent and must later be collected to correctly represent one single object. This approach can be found in [F,FE,R]. Assume an input binary image of size NxM. Using these labelling algorithms, the number of equivalent pair generated is bounded by O(N*M). The number of distinct labels is also bounded by O(N*M). There is no known algorithm that merge the equivalent label pairs in time linear to the number of pairs, that is in time bounded by O(N*M). We propose a new labelling algorithm which interleaves the labelling with the merging process. The labelling and the merging are combined in one algorithm. Merged label information is kept in an equivalent table which is used to guide the labelling. In general , the algorithm produces fewer equivalent label pairs. The combined labelling and merging algorithm is O(N*M), where NxM is the size of the image. Section II describes the algorithm. Section III gives some examples We discuss implementation issues in section IV and further discussion and conclusion are given in Section V.
The following topics are dealt with: cellular arrays for signal processing.high-speed signal processing.multidimensional digital signal processing.(DSP);beamforming and array processing.computer memories and data stor...
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ISBN:
(纸本)0818608161
The following topics are dealt with: cellular arrays for signal processing.high-speed signal processing.multidimensional digital signal processing.(DSP);beamforming and array processing.computer memories and data storage;structures for DSP;radar signal processing.adaptive signal processing.robotics;computer networks;learning machines;arithmetic for DSP;military applications of signal processing.imageprocessing.signal processing.algorithms;control applications;array and parallel processing.signal restoration and error detection;algorithms and architecture;pattern recognition;spectral analysis and modeling;control design;and VLSI for DSP. Abstracts of individual papers can be found under the relevant classification codes in this or other issues.
The feasibility of a proposed star field image pattern recognition system has been demonstrated by developing and demonstrating the major portions of the software which are required. This system includes an image samp...
The feasibility of a proposed star field image pattern recognition system has been demonstrated by developing and demonstrating the major portions of the software which are required. This system includes an image sampling device which transforms the visual image into a form suitable for computer digitalimageprocessing. The algorithms developed for this study are capable of processing.the image in this form to extract star locations and relative brightnesses, and to perform pattern recognition in order to identify the viewed star field from a reduced master chart of the area.
Computer recognition and inspection of objects is, in general , a complex procedure requiring a variety of kinds of steps which successively transform the iconic data to recognition information. We hypothesize that th...
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Computer recognition and inspection of objects is, in general , a complex procedure requiring a variety of kinds of steps which successively transform the iconic data to recognition information. We hypothesize that the difficulty of today's computer vision and recognition technology to be able to handle unconstrained environments is due to the fact that the existing algorithms are specialized and do not develop one or more of the necessary steps to a high enough degree. Our thesis is that there are no shortcuts. A recognition methodology must pay substantial attention to each of the following five steps: conditioning, labeling, grouping, extracting, and matching.
We present a two-dimensional cellular hypercube architecture for imageprocessing.that combines features of the conventional hypercube and cellular logic architectures for 2-D computation cells. A unified theory of pa...
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We present a two-dimensional cellular hypercube architecture for imageprocessing.that combines features of the conventional hypercube and cellular logic architectures for 2-D computation cells. A unified theory of parallel binary imageprocessing. binary image algebra (BIA), serves as a software tool for designing parallel imageprocessing.algorithms. To match the hardware to the software, we characterize the cellular processors using the same algebraic structure as BIA. The two-dimensional cellular (hypercube image processor is a cellular SIMD machine with N2 cells and has a simple overall organization, low cell complexity and fast processing.ability. An optical cellular hypercube implementation of BIA is proposed which offers parallel input/output and global interconnection capabilities which are difficult to do in planar VLSI technology.
Several structures for two-dimensional (2-D) block implemented FIR and IIR digital filters are presented which make use of single-instruction, multiple-data stream (SIMD) machines and pipeline architectures. A specifi...
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Several structures for two-dimensional (2-D) block implemented FIR and IIR digital filters are presented which make use of single-instruction, multiple-data stream (SIMD) machines and pipeline architectures. A specific structure using a length-2 convolution processor has also been developed to perform the matrix-vector operations with a minimum number of multiplications. The SIMD architecture is further modified to process 2N-1 image frames simultaneously in a pipeline fashion for direct 2-D block recursive and 2-D block state-space implementations. To yield higher a throughput rate, a pipeline mechanism has also been adopted at the processing.element level. The structures introduced provide a symmetric design for implementing near-real-time to real-time filtering operation.
Several algorithms and devices have been developed to enhance and restore details, as well as to quantify features in microscopic images that have been obtained with a scanning electron microscope (SEM) from samples s...
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Several algorithms and devices have been developed to enhance and restore details, as well as to quantify features in microscopic images that have been obtained with a scanning electron microscope (SEM) from samples submitted to stress fields within the SEM. A microcomputer is used to control the scanning of the electron beam and to acquire and digitize images for processing. By the use of software and hardware manipulation it is possible to observe and quantify microdisplacements of the elements of a composite material, in order to advance the understanding of their behavior in the elastic and plastic regimes, as well as to characterize their fracture modes.
KWIK is an integrated software environment designed to promote the rapid development of imageprocessing.algorithms. The system consists of a number of components: a compiler, editor, architecture/system configuration...
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ISBN:
(纸本)089252765X
KWIK is an integrated software environment designed to promote the rapid development of imageprocessing.algorithms. The system consists of a number of components: a compiler, editor, architecture/system configuration, look-up table generator and help facility. KWIK is menu-driven;the user selects an option from the five main ones above. These components form a set of tools which the user employs to accelerate the cycle from experimental stage to final algorithm. Each component is tightly coupled and internal information is passed amongst them. This common knowledge base can be used, for example, to advise if problems arise. The information base consists of two basic parts. A permanent (static) knowledge base includes imageprocessing.primitives, their arguments and method of implementation. The second part consists of temporary (dynamic) information which can, if required, be augmented to the permanent knowledge base.
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