The development of a multi-layer architecture for image processing

The extraction of useful information from an image involves a series of operations, which can be functionally divided into low-level, intermediate-level and high- level processing. Because different amounts of computing power may be demanded by each level, a system which can simultaneously carry out operations at different levels is desirable. A multi-layer system which embodies both functional and spatial parallelism is envisioned. This thesis describes the development of a three-layer architecture which is designed to tackle vision problems embodying operations in each processing level. A survey of various multi-layer and multi-processor systems is carried out and a set of guidelines for the design of a multi-layer image processing system is established. The linear array is proposed as a possible basis for multi-layer systems and a significant part of the thesis is concerned with a study of this structure. The CLIP7A system, which is a linear array with 256 processing elements, is examined in depth. The CLIP7A system operates under SIMD control, enhanced by local autonomy. In order to examine the possible benefits of this arrangement, image processing algorithms which exploit the autonomous functions are implemented. Additionally, the structural properties of linear arrays are also studied. Information regarding typical computing requirements in each layer and the communication networks between elements in different layers is obtained by applying the CLIP7A system to solve an integrated vision problem. From the results obtained, a three layer architecture is proposed. The system has 256, 16 and 4 processing elements in the low, intermediate and high level layer respectively. The processing elements will employ a 16-bit microprocessor as the computing unit, which is selected from off-the-shelf components. Communication between elements in consecutive layers is via two different networks, which are designed so that efficient data transfer is achieved. Additionally, the networks enable the system to maintain fault tolerance and to permit expansion in the second and third layers

Studies of algorithms and related imaging techniques for industrial inspection

This thesis will deal with algorithms and imaging techniques for use in automated industrial inspection. The work falls into two main areas, the first dealing with general problems relating to typical inspection tasks, the second with specific applications including the analysis of seals on plastic packets.The requirements of a general object location and inspection system will be discussed initially in relation to algorithms supplied with commercial systems, which often seem ad-hoc. This will be followed up with detailed analyses of several corner and small hole detection algorithms. The features looked for in a useful algorithm are: (1) a high execution speed when implemented on a general purpose microcomputer, (2) good accuracy in locating the desired features, (3) robustness when faced with poor quality, noisy or cluttered images and (4) the ability to distinguish between genuine features and others that appear, superficially, to be similar. A program using these feature detectors to locate partially occluded machine parts in typical images will be presented.The second main area of investigation is that of the detection of faults in heat sealed food packets and is one which has hitherto largely been overlooked. The main problem with these packets is that the cellophane wrapper is highly reflective, giving rise to large areas of glare in any off-camera image. Experience has shown that careful lighting arrangement alone will never totally remove this problem. However, a simple arrangement of switched light beams, along with computer processing, can almost totally eliminate the glare. This approach has been used in the inspection of packets where faults are revealed by parts of the product inside showing through holes in the wrapper. Alternatively, by careful alignment of the light sources, the surface structure of the sealed part of a packet may be revealed. This can reveal defects either through the absence of a regular pattern, or by the presence of wrinkles running across the seal. Algorithms have been developed demonstrating each of these inspection tasks.Overall the work presented in this thesis has spanned several traditional areas of interest, and has also developed the techniques required for packet inspection and other situations where glare is a problem.<p

Parallel architectures for image analysis

This thesis is concerned with the problem of designing an architecture specifically for the application of image analysis and object recognition. Image analysis is a complex subject area that remains only partially defined and only partially solved. This makes the task of designing an architecture aimed at efficiently implementing image analysis and recognition algorithms a difficult one. Within this work a massively parallel heterogeneous architecture, the Warwick Pyramid Machine is described. This architecture consists of SIMD, MIMD and MSIMD modes of parallelism each directed at a different part of the problem. The performance of this architecture is analysed with respect to many tasks drawn from very different areas of the image analysis problem. These tasks include an efficient straight line extraction algorithm and a robust and novel geometric model based recognition system. The straight line extraction method is based on the local extraction of line segments using a Hough style algorithm followed by careful global matching and merging. The recognition system avoids quantising the pose space, hence overcoming many of the problems inherent with this class of methods and includes an analytical verification stage. Results and detailed implementations of both of these tasks are given

Visual inspection : image sampling, algorithms and architectures

The thesis concerns the hexagonal sampling of images, the processing of industrially derived images, and the design of a novel processor element that can be assembled into pipelines to effect fast, economic and reliable processing. A hexagonally sampled two dimensional image can require 13.4% fewer sampling points than a square sampled equivalent. The grid symmetry results in simpler processing operators that compute more efficiently than square grid operators. Computation savings approaching 44% arc demonstrated. New hexagonal operators arc reported including a Gaussian smoothing filter, a binary thinner, and an edge detector with comparable accuracy to that of the Sobel detector. The design of hexagonal arrays of sensors is considered. Operators requiring small local areas of support are shown to be sufficient for processing controlled lighting and industrial images. Case studies show that small features in hexagonally processed images maintain their shape better, and that processes can tolerate a lower signal to noise ratio, than that for equivalent square processed images. The modelling of small defects in surfaces has been studied in depth. The flexible programmable processor element can perform the low level local operators required for industrial image processing on both square and hexagonal grids. The element has been specified and simulated by a high level computer program. A fast communication channel allows for dynamic reprogramming by a control computer, and the video rate element can be assembled into various pipeline architectures, that may eventually be adaptively controlled

Lattice gauge theories dynamical fermions and parallel computation

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