Knowledge-based machine vision systems for space station automation

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed

A graph theoretic approach to scene matching

The ability to match two scenes is a fundamental requirement in a variety of computer vision tasks. A graph theoretic approach to inexact scene matching is presented which is useful in dealing with problems due to imperfect image segmentation. A scene is described by a set of graphs, with nodes representing objects and arcs representing relationships between objects. Each node has a set of values representing the relations between pairs of objects, such as angle, adjacency, or distance. With this method of scene representation, the task in scene matching is to match two sets of graphs. Because of segmentation errors, variations in camera angle, illumination, and other conditions, an exact match between the sets of observed and stored graphs is usually not possible. In the developed approach, the problem is represented as an association graph, in which each node represents a possible mapping of an observed region to a stored object, and each arc represents the compatibility of two mappings. Nodes and arcs have weights indicating the merit or a region-object mapping and the degree of compatibility between two mappings. A match between the two graphs corresponds to a clique, or fully connected subgraph, in the association graph. The task is to find the clique that represents the best match. Fuzzy relaxation is used to update the node weights using the contextual information contained in the arcs and neighboring nodes. This simplifies the evaluation of cliques. A method of handling oversegmentation and undersegmentation problems is also presented. The approach is tested with a set of realistic images which exhibit many types of sementation errors

A knowledge-based machine vision system for space station automation

A simple knowledge-based approach to the recognition of objects in man-made scenes is being developed. Specifically, the system under development is a proposed enhancement to a robot arm for use in the space station laboratory module. The system will take a request from a user to find a specific object, and locate that object by using its camera input and information from a knowledge base describing the scene layout and attributes of the object types included in the scene. In order to use realistic test images in developing the system, researchers are using photographs of actual NASA simulator panels, which provide similar types of scenes to those expected in the space station environment. Figure 1 shows one of these photographs. In traditional approaches to image analysis, the image is transformed step by step into a symbolic representation of the scene. Often the first steps of the transformation are done without any reference to knowledge of the scene or objects. Segmentation of an image into regions generally produces a counterintuitive result in which regions do not correspond to objects in the image. After segmentation, a merging procedure attempts to group regions into meaningful units that will more nearly correspond to objects. Here, researchers avoid segmenting the image as a whole, and instead use a knowledge-directed approach to locate objects in the scene. The knowledge-based approach to scene analysis is described and the categories of knowledge used in the system are discussed

Novel nonlinear optical phenomena in nematic liquid crystals

In normal materials, the nonlinear optical effects arise from nonlinearities in the polarisabilities of the constituent atoms or molecules. On the other hand the nonlinear optical effects in liquid crystals arise from totally different processes. Also they occur at relatively low laser intensities. In a laser field a liquid crystal exhibits many novel and interesting nonlinear optical effects. In addition we also find laser field induced effects that are peculiar to liquid crystals, like structural transformations, orientational transitions, modulated structures and phase transitions, to name a few. Here we dwell upon a few of these interesting and important nonlinear optical phenomena that exist in nematic liquid crystals

Piezooptics of crystals

In this paper the effects of mechanical stress on the refractive, absorptive and the rotatory properties of crystals have been considered with particular emphasis on the role of crystal symmetry. Stress-induced optical activity and the photoelastic behaviour of transparent, weakly absorbing and metallic crystals have been discussed. Piezooptia of polycrystalline media has also been briefly dealt with

Control dependence for extended finite state machines

Though there has been nearly three decades of work on program slicing, there has been comparatively little work on slicing for state machines. One of the primary challenges that currently presents a barrier to wider application of state machine slicing is the problem of determining control dependence. We survey existing related definitions, introducing a new definition that subsumes one and extends another. We illustrate that by using this new definition our slices respect Weiser slicing’s termination behaviour. We prove results that clarify the relationships between our definition and older ones, following this up with examples to motivate the need for these differences

On some elastic instabilities in biaxial nematics

Within the framework of the continuum elastic theory of biaxial nematic liquid crystals, we have addressed ourselves to the structure, stability and energetics of some singular and non-singular topological defects, and certain director configurations. We find that certain non-singular hybrid disclinations could be energetically favourable relative to certain half-strength disclinations. The interaction between singular hybrids depends strongly on the biaxial elastic anisotropy. We suggest possible defect structures that can exist in spherical droplets of biaxial nematics. Further we find structural instabilities, in confined geometries, arising due to the inherent biaxiality of the system

On the optics of twist grain boundary smectics

We have studied theoretically the optical properties of twist grain boundary smectics. We find many reflection bands even at normal incidence. In some of the reflection bands an incident light in any state of polarization gets strongly reflected while in some others the strongly reflected state is of a circular polarization with the same or the opposite handedness as that of the structure. At oblique incidence, depending upon the screw symmetry, a reflection band either has three sub-bands of different polarizations or is a single band of a particular polarization. We find optical diffraction for light incident perpendicular to the twist axis. The diffraction pattern is completely different for TGBA and TGBC. In addition in absorbing TGBC the pattern can even become asymmetric. From a Fourier inversion of the complex diffracted amplitudes we can evaluate in some cases the sizes of the smectic blocks and the grain boundaries

Nematic kink states in a laser field

We have investigated the nonlinear optical interaction of uniform and kink states of a nematic and a ferrofluid-doped nematic (ferronematic) liquid crystal with an incident laser field. We find that the transition between the permitted uniform oreintational states of these systems is of first order in the case of nematics, and of second order in the case of ferronematics. In the latter case we also find the phenomenon of reentrance. We find new kink states in a magnetic field with topological winding different from p in the case of nematics, and 2π in the case of ferronematics. In ferronematics, due to grain segregation the phase diagrams for uniform and kink states are entirely different. In these systems we find a first or second order structural transformation from a single kink into a pair of kinks. Further, we obtain a rich variety of kink states as the intensity of the laser field is varied

Image Segmentation using Two-Layer Pulse Coupled Neural Network with Inhibitory Linking Field

For over a decade, the Pulse Coupled Neural Network(PCNN) based algorithms have been used for imagesegmentation. Though there are several versions of the PCNNbased image segmentation methods, almost all of them use singlelayerPCNN with excitatory linking inputs. There are fourmajor issues associated with the single-burst PCNN which needattention. Often, the PCNN parameters including the linkingcoefficient are determined by trial and error. The segmentationaccuracy of the single-layer PCNN is highly sensitive to the valueof the linking coefficient. Finally, in the single-burst mode,neurons corresponding to background pixels do not participatein the segmentation process. This paper presents a new 2-layernetwork organization of PCNN in which excitatory andinhibitory linking inputs exist. The value of the linkingcoefficient and the threshold signal at which primary firing ofneurons start are determined directly from the image statistics.Simulation results show that the new PCNN achieves significantimprovement in the segmentation accuracy over the widelyknown Kuntimad’s single burst image segmentation approach.The two-layer PCNN based image segmentation methodovercomes all three drawbacks of the single-layer PCNN