A spherical harmonic is defined which is an operationally optimal small finite subset of the infinite number of spherical harmonics allowed to exist mathematically. The composition of the subset differs depending on its position on virtual hemisphere. The subsets are further divided into small spherical tesserae whose dimensions vary depending on the distance from the hemispherical center. The images of the outside visual scenes are projected on the flat surface of the webcam and from there are read and recalculated programmatically as if the images have been projected on the hemisphere, rotational invariants are then computed in the smallest tesserae using numerical integration, and then invariants from neighboring tesserae are added to compute the rotational invariant of their union. Every computed invariant is checked with the library and stored there if there is no match. The rotational invariants are solely used for visual recognition and classification and operational decision making.
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