Paper
12 December 1997 Anthropomorphic robot for drawing stylized (generalized) object images
Vera Moiseevna Ginzburg
Author Affiliations +
Abstract
Periodic defocusing of the crystalline lens leads to generalization of an image projected on the retina. In the process, the fine structure of the image is eliminated while informative fragments (IF), that is, brighter spots with abrupt contour change, are emphasized. The shape and arrangement of IFs may be utilized by a visual system in order to trigger saccades and form receptive areas. Results of theoretical and experimental optical studies imitating physiological processes are described. These results may be of interest to physiologists and can be used to develop anthropomorphic technical systems. A brief comparative analysis of other anthropomorphic systems proposed by A.. P. Ginsburg, T. Podjio, D. I. Tomsit and others is given. A specific model of anthropomorphic robot representing a holographic correlator processing images by defocusing and by applying a set of spatial filters. These filters are constructed using a set of elementary images formed from two images, a straight stripe and a round spot, recognized by all living beings. Such a robot can be used for drawing letters and numerals from their written images; for classification of many similar images; for processing aerial photographs to determine boundaries between woods, various crops, etc. Input image defocusing is shown to be also useful for narrowing bandwidth in TV systems; for automatic loading of optical information after removal of noise. Keywords: optical pattern recognition, defocusing, visual system, spatial frequencies, optical transfer function, informative fragments, image perception, anthropomorphic robot.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vera Moiseevna Ginzburg "Anthropomorphic robot for drawing stylized (generalized) object images", Proc. SPIE 3173, Ultrahigh- and High-Speed Photography and Image-based Motion Measurement, (12 December 1997); https://doi.org/10.1117/12.294550
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