Abstract
Automatically recognition and classification of biological objects under microscope methods are shown in paper. Problem of separated of white-black and color images is studied. Method of separation of different type of objects (visual diapason of specter) with compare results is shown in the paper. Quality of segmentation methods analyses is presented in the paper. Schemes and table results of segmentation are exist. Methods of pattern recognition applicability for Computer Vision Systems of analysis and pattern recognition scenes in the visual spectrum are studied in the paper. The methods and algorithms can be used in Real-time Sensing, white-black and color patterns, reasoning and adaptation for Computer Vision Systems too. Example of such systems is the glasses for people with visual impairments; when the camera mounted in glasses receives and transmits environment data, and the contact plate with electrical leads via e-pulse transmits data to the eye retina. Author analyzed several pattern recognition methods that will allow to process data of the environment for the brain. This will make the visually impaired persons with sub reality vision better orientation in environment. Theoretical basic, algorithms and their compared for apply is presented in paper.
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Hrytsyk, V., Nazarkevych, M. (2022). Real-Time Sensing, Reasoning and Adaptation for Computer Vision Systems. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 77. Springer, Cham. https://doi.org/10.1007/978-3-030-82014-5_39
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