Abstract: Among the various aspects of the present disclosure is the provision of devices, systems, and methods for tracking the positions and orientations of at least one bone screw implanted within a surgical site. The disclosed device includes an extension that includes an extension base configured to couple to the bone screw, a marker arm coupled at one end to the extension base in a hinged arrangement, and an optical marker attached to a free end of the marker arm opposite the hinged attachment. The optical marker includes a pair of lenticular arrays in a coplanar arrangement in which the major axes of the lenticular arrays are mutually perpendicular. Each lenticular array is configured to display different hues at different viewing angles. The disclosed method includes transforming a single image of a surgical site containing at least one bone screw and extension into the global positions of each bone screw based on the pixel positions and hues corresponding to the lenticular arrays of each optical marker.

Abstract: The present disclosure is directed to an approach to solve camera calibration from a single picture of a simply structured light field created by viewing a carefully designed lenticular sheet. The lenticular sheet has different colors visible at different relative orientations and gives linear constraints on the K-1?R matrix which can be decomposed to give the rotation and calibration. The method uses geometric cues from hue measurements and does not require a correspondence between a point in the image and a point on the calibration pattern.

Abstract: The present disclosure is directed to an approach to solve camera calibration from a single picture of a simply structured light field created by viewing a carefully designed lenticular sheet. The lenticular sheet has different colors visible at different relative orientations and gives linear constraints on the K-1?R matrix which can be decomposed to give the rotation and calibration. The method uses geometric cues from hue measurements and does not require a correspondence between a point in the image and a point on the calibration pattern.

Abstract: A method of detecting optical defects in a transparency may comprise the steps of providing a digital image of the transparency having a plurality of image pixels and detecting at least one candidate defect. The candidate defect may be detected by determining a grayscale intensity of each one of the image pixels and calculating an intensity gradient across adjacent pairs of the image pixels. Each image pixel may be assigned a gradient value comprising a maximum of the absolute value of the intensity gradients associated with the image pixel. A gradient image may be constructed comprising the gradient values assigned to corresponding ones of the image pixels. Image pixels may be identified as candidate pixels if such image pixels have a gradient value exceeding a gradient threshold. The candidate pixels may comprise the optical defect.

Abstract: A method of detecting optical defects in a transparency may comprise the steps of providing a digital image of the transparency having a plurality of image pixels and detecting at least one candidate defect. The candidate defect may be detected by determining a grayscale intensity of each one of the image pixels and calculating an intensity gradient across adjacent pairs of the image pixels. Each image pixel may be assigned a gradient value comprising a maximum of the absolute value of the intensity gradients associated with the image pixel. A gradient image may be constructed comprising the gradient values assigned to corresponding ones of the image pixels. Image pixels may be identified as candidate pixels if such image pixels have a gradient value exceeding a gradient threshold. The candidate pixels may comprise the optical defect.

Abstract: A method of detecting optical defects in a transparency may comprise the steps of providing a digital image of the transparency having a plurality of image pixels and detecting at least one candidate defect. The candidate defect may be detected by determining a grayscale intensity of each one of the image pixels and calculating an intensity gradient across adjacent pairs of the image pixels. Each image pixel may be assigned a gradient value comprising a maximum of the absolute value of the intensity gradients associated with the image pixel. A gradient image may be constructed comprising the gradient values assigned to corresponding ones of the image pixels. Image pixels may be identified as candidate pixels if such image pixels have a gradient value exceeding a gradient threshold. The candidate pixels may comprise the optical defect.