Simplified Pattern Recognition Based On Multiaperture Optics

Richard T. Schneider; Shih-Chao Lin

doi:10.1117/12.940650

11 May 1987 Simplified Pattern Recognition Based On Multiaperture Optics

Richard T. Schneider, Shih-Chao Lin

Proceedings Volume 0786, Applications of Artificial Intelligence V; (1987) https://doi.org/10.1117/12.940650
Event: 1987 Technical Symposium Southeast on Optics, Electro-Optics, and Sensors, 1987, Orlando, FL, United States

Abstract

Multiaperture optics systems are similar in design to the concepts applying to the insect eye. Digitizing at the detector level is inherent in these systems. The fact that each eyelet forms one pixel of the overall image lends itself to optical preprocessing. There-fore a simplified pattern recognition scheme can be used in connection with multiaperture optics systems. The pattern recognition system used is based on the conjecture that all shapes encountered can be dissected into a set of rectangles. This is accomplished by creating a binary image and comparing each row of numbers starting at the top of the frame with the next row below. A set of rules is established which decides if the binary ones of the next row are to be incorporated in the present rectangle or start a new rectangle. The number and aspect ratios of the rectangles formed constitute a recognition code. These codes are kept and updated in a library. Since the same shape may give rise to different recognition codes depending on the attitude of the shape in respect to the detector grid, all shapes are rotated and normalized prior to dissecting. The rule is that the pattern is turned to maximize the number of straight edges which line up with the detector grid. The mathematical mechanism for rotation of the shape is described. Assuming a-priori knowledge of the size of the object exists, the normalization procedure can be used for distance determination. The description of the hardware for acquisition of the image is provided.

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Richard T. Schneider and Shih-Chao Lin "Simplified Pattern Recognition Based On Multiaperture Optics", Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); https://doi.org/10.1117/12.940650

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KEYWORDS

Sensors

Artificial intelligence

Binary data

Image compression

Image processing

Optical pattern recognition

Detector arrays

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