US 12,175,600 B2
Data management system for spatial phase imaging
Blair Barbour, Windemere, FL (US); Nicholas Englert, Orlando, FL (US); David Theodore Truch, Katy, TX (US); and John Harrison, Kissimmee, FL (US)
Assigned to Photon-X, Inc., Kissimmee, FL (US)
Filed by Photon-X, Inc., Kissimmee, FL (US)
Filed on Jan. 28, 2022, as Appl. No. 17/587,540.
Application 17/587,540 is a continuation of application No. PCT/US2020/045956, filed on Aug. 12, 2020.
Claims priority of provisional application 62/885,436, filed on Aug. 12, 2019.
Claims priority of provisional application 62/885,407, filed on Aug. 12, 2019.
Prior Publication US 2022/0405874 A1, Dec. 22, 2022
Int. Cl. G06T 17/20 (2006.01); G06T 1/00 (2006.01); G06V 10/147 (2022.01); G06V 10/44 (2022.01); G06V 10/54 (2022.01); G06V 10/762 (2022.01); H04N 19/90 (2014.01); G06V 20/13 (2022.01); G06V 20/64 (2022.01); G06V 40/13 (2022.01)
CPC G06T 17/20 (2013.01) [G06T 1/0007 (2013.01); G06V 10/147 (2022.01); G06V 10/44 (2022.01); G06V 10/54 (2022.01); G06V 10/762 (2022.01); G06V 20/13 (2022.01); G06V 20/64 (2022.01); G06V 40/1312 (2022.01)] 25 Claims
OG exemplary drawing
 
1. A data management system for spatial phase imaging, comprising:
a storage engine configured to receive and store input data in a record format, the input data comprising:
pixel-level first-order primitives generated based on electromagnetic (EM) radiation received from an object located in a field-of-view of an image sensor device; and
pixel-level second-order primitives generated based on the pixel-level first-order primitives;
an analytics engine configured to determine a plurality of features of the object by:
clustering the pixel-level first-order primitives having similar attributes and the pixel-level second-order primitives having similar attributes to define surfaces of the object; and
attributing a respective set of surface-level first-order primitives and surface-level second-order primitives to each surface of the object; and
an access engine configured to provide a user access to the plurality of features of the object determined by the analytics engine and to the input data stored by the storage engine.