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Deflection linearity and adjustment in a TV system are accomplished by a test pattern usually generated by a scanning process which may itself be subject to error. This paper describes a method and equipment for generating a circular test pattern derived from an electronic memory. The readout is accomplished by an accurate time base synchronous with scanning standards. By this means an extremely accurate circular (or other) pattern can be generated for adjustment of display devices.

In this paper we develop methods of segmenting a large system into smaller subsystems so that the letter can be diagnosed in parallel. Two basic techniques called serial segmentation and parallel segmentation are introduced. Furthermore, an algorithm is developed for the purpose of reducing the complexity and the size of the large subsystem.

This paper examines algorithms and techniques for use in a complete FLIR target cuer/recognizer. The application is the Air Force Theater Missile Defense Eagle Smart Sensor and Automatic Target Cuer/Recognizer (TESSA) program. The data used for this research are 1st generation FLIR images collected from an F-15E. The database contains thousands of images with various target arrangements. The specific target of interest is a mobile missile launcher, which will be defined as the primary target. The goal is to locate all vehicles (secondary targets) within a scene and identify the missile launchers. The system designed includes an image segmenter, region cluster algorithm, and classifier. Conventional algorithms in conjunction with neural network techniques are used to form a complete ATR system. Some of the conventional techniques include hit/miss filtering, difference of Gaussian filtering, and region clustering. A neural network (multilayer perceptron) is used for classification. These various algorithms are tested and combined into a functional ATR system. Overall target detection rate (cuer) is 84% with a 69% accurate primary target identification (recognizer) rate. Furthermore, the false alarm rate (a non-target cued as a target) is only 2.3 per scene. The research will be completed with a 10 flight test profile using an F-15E and will collect 3/sup rd/ generation FLIR images for use with these algorithms.