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The problem of locating a reference image within a larger image using a correlation technique is discussed. Although the particular application discussed is that of locating a reference image obtained from one video sensor or a photograph, within the larger field of view obtained from a second video sensor in real time (i.e., at the TV field rate), the results are general and useful for a number of applications. The tradeoffs necessary to obtain real time correlat are discussed and their effect on correlation accuracy is given.

A brief review of the principles of stereoscopy is given followed by a discussion of candidate methods for providing stereoscopic viewing of display data. An analog computer implementation of a stereoscopic graphics display system is described. The analog implementation provides real-time display capability but has no data storage capability. Implementation with a small digital computer provides data storage but is significantly slower for displaying dynamic changes in the data. Other points of comparison between the two systems are given with the conclusion that a hybrid system would combine good features of both. Experimental evaluation relative to eye fatigue is given for three specific viewing techniques. Example stereograms are given for both the digital and analog systems. Of particular interest was application of the display system for viewing biomedical data, as illustrated by an example display of a vectorcardiogram.

Electroencephalographic (EEG) data consisting of visual evoked responses monitored via an array of electrodes from humans and penicillin-induced focal epileptic discharge data recorded from rat neocortex are analyzed. This procedure, previously applied to seismic array data, offers a method by which high-resolution vector velocity and, thus, direction and speed of propagating wavefronts can be estimated.

As a result of characterizing joint scene content in terms of the joint probability density function, a new registration metric was defined as the threshold difference (TD) method. It produced a sharper correlation peak than other pixel-by-pixel methods investigated. Analytical comparisons and simulations were done to show the effects of scene content on registrations by direct cross correlation, mean absolute difference and thresholded difference methods. (Author)

Threshold effects are examined for a real-time image correlator in the absence of geometric distortion. Images obtained from two different television sensors are sampled and quantized to two levels. The correlation algorithm is then implemented as an "exclusive OR" followed by summation. For a KxL reference array the correlation algorithm produces an output between zero and KL. This paper examines the effect of choosing a threshold No above which the images are considered to be correlated. Probability of false alarm is found to be dependent on the total number of pixels used in the correlation algorithm. Probability of detection is found to depend also on the video signal-to-noise ratios and is computed for Gaussian, uniform and bimodal image distributions.

Sensing is the mechanism by which robots receive information from the world around them. Robot sensing, and in particular, robot vision is the basis for providing sensory inputs to a smart robot. Devices that make robot vision possible are typically classified as electro-optical sensors. Thus a critical review of robot vision is essentially a review of current and predicted capabilities for imaging electro-optical sensors. The critical element in an electro-optical sensor is the detector and most detectors are semiconductor devices. Thus we conclude that robot vision is closely tied to the state of the art in the development of photosensitive semiconductor materials and in the fabrication of large scale arrays of detector elements. This paper begins with a review of the fundamental principles that are important to electro-optical sensors. It then presents a brief tutorial on parameters for quantitatively evaluating the performance of detectors and electro-optical sensors. Selected state of the art sensor systems are next analyzed to show expected performance. Finally a review is given of detector technology as related to robot vision including a comparison of materials, array sizes, performance and cost.

A multisensor, microprocessor-controlled robotic locating system (RLS) is being devel-oped in our machine intelligence laboratory. A video camera, laser illuminator, optical angle sensors, and ultrasonics are the primary sensor components. Software is being de-veloped on a personal computer that has been augmented with video acquisition and high-speed signal processing boards. Real-time (less than 1 second) algorithms are being implemented that exploit both natural and artificial patterns. Artificial patterns are introduced by planting light-emitting diodes (LED) and reflective materials in the envi-ronment. Projecting light patterns is also part of the design. Using control points to determine camera position and orientation is a particularly interesting problem because of its apparent simplicity. Several algorithms for calibrat-ing a camera using control points are discussed in detail. The use of four control points in a rectangular configuration is especially detailed. A review of various approaches to camera calibration is included. The methods pre-sented are from the literature and work performed by the authors. These different ap-proaches provide insight into the nature of the problems. Closed form solutions are emphasized.

A practical system for computing attitude angles from the image of four rectangular, coplanar points has a number of potential error sources that degrade the accuracy of the attitude computation. An error analysis is presented for the Robot Locating System (RLS), which is a multisensor laboratory testbed that seeks to compute attitude angles from an image of four points. This paper discusses potential error sources and their relative effects for the RLS system. The error sources are discussed from a physical point of view and expected error characteristics are described. These error sources are then evaluated using a software simulation of the RLS system.

Modeling of electro-optical sensor performance with emphasis on the effects of smoke and aerosol in the path between target and sensor is discussed. The elements which comprise a simple model are presented along with characterization of propagation path effects. Design of an experiment to validate performance models is discussed with particular importance placed on the selection of targets to match sensor features. Data acquisition equipment and measurement techniques used for characterizing high bandwidth video signal synchronously with data characterizing the optical path are described.© (1980) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The Robotic Locating System (RLS) is a multisensor laboratory test bed designed to evaluate the feasibility of measuring target range and orientation in various robotic environments. The targets are considered to be cooperative and typically have LEDs or reflective material placed on them. Laser illumination in combination with video sensing is the primary sensor system. A pair of optical position sensors and an array of ultrasonic ranging sensors to augment system performance. This paper will report on the sensitivity study being done to determine the resolution and accuracy of the measurement process. In particular, details of measuring all six degrees of freedom (DOF) of a rectangular target with four LEDs or four spots of reflective tape will be presented.

A major operational need facing the next generation of Scout (ASH) and Attack (AAH) helicopters is to detect targets from nap-of-earth altitudes, on a realistic battlefield in a complex and cluttered scene. The targets of interest here are primarily the single, high threat target which will not be contained with the main body of target tanks and will not present many detection cues. Various image enhancement methods have been evaluated in terms of improved operator performance. Quantitative performance measures such as contrast, resolution and signal-to-noise ratio are computed for selected algorithms and related to observer performance probabilities. This paper presents analysis and simulation results for an image enhancement method known as local area gain control. It shows dependence on parameter selection and develops criteria for evaluation in terms relatable to detection probability.

A microprocessor based multisensor robotic locating system (RLS) was designed and is currently under development. The system uses primarily off-the-shelf components, integrated into a single package applicable to a wide variety of robotic tasks. Range and orientation to a specified target is measured using a combination of video camera, illuminator, ultra-sonics, and optical rangefinder. The processing algorithms are designed to operate in real time by exploiting known patterns that are on the target in the form of retroreflective material.

Two iterative algorithms are presented for phase retrieval from intensity measurements for two-dimensional complex-valued sequences. The first algorithm constructs a linear combination of present and past iteration outputs using a relaxation parameter. The second algorithm utilizes a Kalman-type filter to combine estimates of object domain magnitude. A new error metric is defined that uses residual monitoring to show the relationship of the error to the reconstructed image quality. These algorithms are first tested against real-valued images to investigate their convergence chacacteristics. Both algorithms are then applied to infrared images which are characterized by low-contrast and noise-corruption. The question of uniqueness is also addressed for two-dimensional complex-valued sequences.

The object-oriented paradigm offers a new approach to the development of software for image processing applications. The fundamental concept of the object-oriented paradigm is that problem solutions are implemented by sending messages to objects. This requires that the objects in a solution be defined along with messages to which each object will respond. This is in contrast to structured programming wherein one defines data structures and sends those data structures to a procedure as parameters.