In this paper, we consider various spatial re-lationships that are of general interest in pic-torial database systems. We present a set of rules that allow us to deduce new relationship-s from a given set of relationships. A deduc-tive mechanism using these rules can be used in query processing systems that retrieve pic-tures by content. The given set of rules are shown to be sound, i.e. the deductions are logically correct. The rules are also shown to be complete for three dimensional systems, i.e. every relationship which is implied by a given consistent set of relationships F is deducible from F using the given rules. In addition, we show that the given set of rules is incomplete for two dimensional systems.

A novel shape description method based on the Morphological Signature Transform (MST) is presented in this dissertation. The MST uses multiresolution morphological image processing by non-convex multiple structuring elements. A binary image which contains the object shape to be described is represented by means of a multiresolution pyramid. The method is based on the successive morphological erosions of the input image at di erent resolutions by primary and rotated structuring elements. The areas of successively eroded images are computed for each structuring element at each pyramid level. The obtained set of numbers is arranged into vectors, ordered, and used as a shape descriptor. Experimental results demonstrate that the method is robust against noise and invariant to translation, rotation, and scale change. A new method for the selection of the optimal structuring element is presented in the second part of dissertation. For a given class of shapes the optimal structuring element for MST method is selected by means of a genetic algorithm. The optimization criteria is formulated to enable a robust shape matching. Experiments have been performed on a class of model shapes. The proposed optimal shape description method is applied to the problem of shape matching which

We present three types of analog VLSI circuits that can be used in manufacturing inspection systems. The first set of circuits performs an adaptive threshold of an input image. The second circuit uses morphological operations with programmable structuring elements to detect oriented edges. Both of these circuits can be used as high speed preprocessors for visual inspection of manufacturing processes. The third circuit performs a computation necessary for selective attention in visual processing. This circuit is a component of a larger system that will facilitate a serial/parallel processing scheme in order to increase the speed of processing in machine vision tasks. All circuits presented use focal-plane processing to achieve their massively parallel architectures. For each design, the processing pixels contain vertical bipolar phototransistors to accommodate parallel optical inputs. All circuits have been fabricated using a standard 2.0 m digital CMOS process. Data for each of these c...

Abstract. We use the genetic programming (GP) paradigm for two tasks. The first task given a GP is the generation of rules for the target / clutter classification of a set of synthetic aperture radar (SAR) images, the second, the generation of rules for the identification of tanks in a second set of SAR images. To perform these tasks, previously defined feature sets are generated on the various images, and GP is used to select relevant features and methods of analyzing these features. GP results are then compared with previous work using the feature sets. 1.

This document is an initial draft of the developing theory of image algebra. The primary objective of this treatise is to provide the reader with an introduction to the theory and foundations of image algebra. For readers interested in applications and image algebra specification of a wide variety of image processing transforms we recommend the Handbook of Computer Vision Algorithms in Image Algebra [46]. Since the discipline of image algebra is in its infancy and a state of flux, this document will undergo various changes before its completion in book format. The book will consist of eight chapters and will be largely self contained. The first chapter will contain all the introductory material; e.g., what is image algebra all about, the history of image algebra, the people involved, organization of the book, etc. Chapters 2 and 3 contain basic background material dealing with point set theory, topology, and abstract algebra. Lack of this background is often a fatal stumbling block to understanding the underlying concepts of image algebra and the mathematics of computer vision in general. As to this initial draft, we recommend reading the introduction and then proceed to a quick overview of the basic concepts that define image algebra, we suggest to start with Section 3.13 (Chapter 3) and then proceed directly to Chapter 4, referring to preceding sections for notation and theorems as the need arises.

We present here the description of a parallel implementation of mathematical morphology using the Linda model of parallel communication embedded within ISETL. The morphological operation of dilation of binary images is considered in detail, with an ISETL implementation given initially, then a description of how this was converted to run in a parallel version of ISETL, ISETL-Linda. INTRODUCTION We are interested in the implementation of binary mathematical morphology using ISETL-LINDA. ISETL (Baxter et al. (1)) is an interactive extension of SETL, which is a programming language based on mathematical notation and objects, primarily sets and functions. ISETL is a high level imperative programming language in which all objects (including functions) are first class. Linda (Carriero and Gelernter (2)) is a parallel coordination language, which uses a shared tuple space to allow multiple processes to communicate. It is independent of any machine architecture and all communication between...

A two-dimensional analog VLSI array that performs basic morphological image processing operations is presented. The system uses a smart pixel approach that facilitates the parallel computation of continuous real-time outputs. Photodetectors within the array of smart pixels also allow for parallel optical inputs. The processing is performed by current-mode circuitry implemented with CMOS technology. The signal values are encoded as analog current values. The processing array uses local communication to perform the morphological operation known as dilation, and outputs the difference between the original input image and the dilation image to detect edges. The system was fabricated using a standard 2.0 m digital CMOS process. Example output data of the fabricated circuitry are presented. 1: Introduction The theory of mathematical morphology has emerged as a means for performing multidimensional signal processing operations, especially in image processing applications. These operations t...

: We present an analogue VLSI circuit that performs morphological image processing operations on the focal plane. The circuit has been fabricated using a standard digital CMOS process. We exploit the parallelism of morphological image processing operations by using the massively parallel architecture of analogue VLSI arrays, achieving both high-speed and low-power computation [1]. The analogue circuit presented computes the grey-scale morphological operation of dilation. This system also allows for programmability of the structuring element used in the dilation operation. Introduction Mathematical morphology is a nonlinear image processing approach that uses set theory to perform functions such as object detection and image segmentation [2][3]. We have developed analogue VLSI circuits that perform the primary operations of morphological image processing [4][5]. These circuits exploit the parallelism of morphological image processing operations by using 2-dimensional arrays of smart p...

This document describes the essential operations that define the theory of mathematical morphology. In addition, the role that mathematical morphology may play in Automatic Target Recognition (ATR) algorithm development is investigated. Particular examples are provided that show how techniques from morphology might be applied to problems associated with ATR.

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