Pattern Recognition Relevant To Multiaperture Optics

Richard T. Schneider; Kenneth L. Meyers

doi:10.1117/12.976234

10 December 1986 Pattern Recognition Relevant To Multiaperture Optics

Richard T. Schneider, Kenneth L. Meyers

Proceedings Volume 0697, Applications of Digital Image Processing IX; (1986) https://doi.org/10.1117/12.976234
Event: 30th Annual Technical Symposium, 1986, San Diego, United States

Abstract

Multiaperture optics deals with image formation employing a large number of optical elements, the insect eye being an example. If the apposition design is used, each optical element creates one pixel only, although due to FOV overlap, there may be some additional information collected. The consequence is that multiaperture optics devices produce a relatively small number of pixels. This presents a challenge to any pattern recognition procedure by requiring it to make assumptions on the information content concerning the spaces between the pixels. Another challenge for pattern recognition, common for all systems, is speed. Therefore, time should not be wasted in examining dead zones in the field. The algorithm presented here meets the first challenge by transforming the presented image into a combination of rectangles of varying aspect ratios. The second challenge is met by selectively examining only those data locations known to be responsive and eliminating any blank space above and below the pattern. This process consists of three stages: 1) an essentially random distribution of data points is converted into rectangular form; 2) these rectangles are then converted into a series of "code elements" which are actually equal to the value of their aspect ratios; 3) this pattern of code elements is then compared to numbers representing some known patterns to achieve identification. The algorithm relies heavily on the concept of a-priori knowl-edge as well as recognizing a fairly small universe of patterns.

Citation Download Citation

Richard T. Schneider and Kenneth L. Meyers "Pattern Recognition Relevant To Multiaperture Optics", Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); https://doi.org/10.1117/12.976234

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KEYWORDS

Sensors

Binary data

Digital image processing

Eye

Signal detection

Superposition

Detection and tracking algorithms

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