Brian A. Kast

Automatic target recognition and tracking using an acousto-optic image correlator

This paper discusses a hybrid electro-optic image processor, developed for automatic target recognition and tracking using an acousto-optic correlator and digital electronics. The optical system performs the computationally intensive correlation operation on the large 2-D input scenes. The electronics provide the decision-making capability and also perform part of the postprocessing needed for increasing the peak-to-clutter ratio in cluttered scenes. The system is able to analyze each correlation plane and apply a real-time template selection algorithm to accommodate scale or rotation changes of the target. A demonstration of the current system capabilities is presented using a terrain board with several different types of stationary and moving model vehicles.

Normalization of correlations

Correlation s often used as an approach to automated pattern recognition. Generally, correlation provides a measure of the similarity between a reference template and regions of an input image. This measure is also highly dependent on intensity variations in the input image, thereby hindering the performance of simple peak detection decision algorithms. Normalization can be used to achieve intensity invariance of correlation results. This paper addresses some aspects of normalization for a few filter types. For matched filters, the Cauchy-Schwarz inequality provides an effective method by taking into account the energy of the input image within the spatial region of support of the template. For many other types of filters being considered for pattern recognition applications, the regions of support are not always limited to the area occupied by the template pattern. This excessive support can produce undesirable effects in the correlation results whether normalized or not. Benefits of normalized correlation such as intensity invariance and resistance to high energy clutter are discussed along with some problems associated with regions of support. Matched filters, phase-only filters, and binary phase-only filters are investigated. Computer simulations of several cases is used to demonstrate results.

Application of normalized gray-scale correlation

Real-time gray-scale correlation in the spatial domain has been demonstrated previously using an acousto-optical (AO) correlator. This work demonstrates normalized gray-scale correlation as implemented on an AO correlator system capable of operating at real-time video rates. Motivation for using normalized gray-scale correlation is presented. The normalized correlation algorithm as implemented on the AO correlator is detailed. The entire real-time AO correlator system is described, including the electronic support hardware and the user interface. Since normalization requires a division operation, system numerical precision issues are addressed. Test results obtained in non-real time experiments are presented.

Design and testing of space-domain minimum-average correlation energy filters for 2-D acousto-optic correlators

Two-dimensional acousto-optic (AO) correlators differ from frequency plane correlators in that multiplying, shifting, and adding, rather than Fourier transforming are used to obtain the correlations. Thus, manu of the available composite filter design techniques are not aimed at designing filters for use in AO correlators because they yield frequency-domain functions. In this paper, a method is introduced for designing filter impulse responses of arbitrary extent for implementation on AO correlators. These filters are designed to yield sharp correlation peaks. Simulation results are included to illustrate the viability of the proposed approach. Also included are some initial results from the first successful use of gray-scale composite filters on an AO correlator.

Design and testing of three-level optimal correlation filters

Previously, we have designed 3-level filters(suitable for implementation on magneto-optic spatial light modulators) to maximize the output signal-to-noise ratio (SNR) and to separately maximize peak-to-correlation energy (PCE) that measures the correlation peak sharpness. In practice, we want the correlation peaks to be sharp (i.e., large PCE) as well as noise-tolerant (i.e., large SNR). In this paper, we present a new method to optimally combine these two desirable properties into a single optimization procedure. Similar methods to trade off SNR versus peak efficiency and PCE versus peak efficiency will be presented. Both simulation and experimental results will be included.

Actuated Tweezers for Precision Microassembly

Sandia National Laboratories is exploring assembling micro, meso, and miniature scale parts into a variety of tiny devices. These devices are comprised of parts ranging from tens of microns to a few millimeters in size. In support of this activity, a rapid prototyping assembly workstation that enables an operator to assemble three-dimensional devices with a minimum of fixturing has been developed. This workstation consists of precision robotics, stages, cameras, and sensors integrated in a way that facilitates human interaction. Although many of the workstation components are commercially available, no inexpensive and durable grippers of suitably large range of motion could be found. This paper describes the design and testing of a novel micro gripper based on precision tweezers and actuated with a micro servo that has proven extremely useful for the operator directed assembly of micro scale devices.Copyright

Automatic target recognition using acousto-optic image correlator

A hybrid electro-optic image processor has been developed for automatic target recognition using an acousto-optic correlator and digital electronics. The optical system performs the computationally intensive correlation operation on the large 2-D input scenes. The electronics provide the decision-making capability and also perform part of the normalization needed for increasing the peak-to-sidelobe ratio in cluttered scenes. The system is able to analyze each correlation plane and apply a real-time template selection algorithm to accommodate scale or rotation changes of the target. A demonstration of the current system capabilities is presented using a terrain board with several different types of stationary and moving model vehicles.