High clarity gemstone facet and internal imaging analysis
Systems and methods here may be used for a setup of image capturing of a gemstone, such as a diamonds that are of high clarity grades. The present embodiments can provide methods to capture a diamond surface and internal clarity features from a diamond table and through and of other facets. Systems and methods may be used to convert gemstone dimension information into azimuth, slope, and distance information and adjust the motorized stage accordingly for surface imaging. Further, a calibration method can consider the offsets between design and actual system alignment. A calibration process can be used to compensate the offsets. Further, an additional conversion can be derived to compensate the offset caused by the geometry of the gemstone. The methods can automatically capture surface reflection images on facets of the gemstone and internal features taken through facets of the gemstone.
1 . A method, comprising,
by a computer in communication with at least one light source and a digital camera,
causing a light source to emit light to illuminate a sample diamond with diffused light by directing the emitted light through a diffuser, wherein the sample diamond comprises a diamond table facet and a number of diamond facets;
by the computer, causing the digital camera to capture a set of surface images of the diamond table facet under the diffused light;
by the computer, causing illumination of the number of diamond facets, other than the diamond table facet, with collimated light by directing the emitted light through a collimator;
by the computer, causing the digital camera to capture a set of surface images of the number of diamond facets, other than the diamond table facet, under the collimated light;
by the computer, causing illumination of the diamond table facet with dark field illumination;
by the computer, causing the digital camera to capture a set of internal images through the diamond table facet at a plurality of focal depths under the dark field illumination;
by the computer, causing the digital camera to capture a set of internal images through the number of diamond facets other than the diamond table facet, at a plurality of focal depths under the dark field illumination;
by the computer, processing the set of surface images of the diamond table facet, the set of surface images of the number of diamond facets, the set of internal images through the diamond table facet, and the set of internal images through the number of diamond facets to identify one or more clarity features from the diamond table facet or any facet of the sample diamond; and
assigning a clarity grade for the sample diamond based on the one or more identified clarity features.
2 . The method of claim 1 further comprising,
by the computer, analyzing the captured surface digital images of the diamond table facet and surface digital images of the diamond facets other than the diamond table facet, to detect anomalies.
3 . The method of claim 2 further comprising,
by the computer, analyzing the captured internal digital images through the diamond table facet and through the diamond facets surfaces other than the diamond table facet, to detect anomalies.
4 . The method of claim 1 wherein the plurality of internal images is taken at focal scanning steps of 0.3 mm.
5 . The method of claim 1 wherein the captured digital camera images of the surface of the diamond facets other than the diamond table facet under collimated light include 56 surface images.
6 . The method of claim 1 wherein the captured digital camera images of the internal images include 96 internal images with a focal scanning step for example but not limited to 0.25 mm or 0.3 mm.
7 . The method of claim 1 further comprising, analyzing, by the computer, the surface images by localizing surface and surface reaching features from the surface images of each facet using boundary analysis or contrast comparison of pixels within each image;
identifying, by the computer, a type of surface and surface reaching features in the images wherein a type includes a feather, pit, scratch, polish lines, surface graining, or burns;
classifying, by the computer, a degree of surface and surface reaching features based on a size and a contrast of the surface features by comparing a detected inclusion size and contrast to a threshold value previously determined;
analyzing, by the computer, the internal images by localizing internal and surface reaching internal features from the captured internal digital images from different azimuth angles and depths;
identifying, by the computer, a type of internal and surface reaching internal features, wherein a type includes a feather, pinpoint, cloud, or internal graining;
differentiating, by the computer, internal inclusions using the surface analysis;
classifying, by the computer, a degree of internal and surface reaching internal features based on size and contrast of the internal features using pixel counting and contrast; and
generating, by the computer, the clarity grade using the surface and internal analyses.
8 . A system, comprising,
a computer with a processor and a memory, in communication with at least one light source and a digital camera, the computer configured to cause the at least one light source to illuminate a sample diamond, wherein the sample diamond is configured on a stage and comprises a diamond table facet and a number of diamond facets, the computer configured to cause the at least one light source to emit light to illuminate a sample diamond table facet with diffused light by directing the emitted light through a diffuser, cause the digital camera to capture surface images of the diamond table facet under the diffused light, cause illumination of the number of diamond facets, other than the diamond table facet, with collimated light by directing the emitted light through a collimator, cause the digital camera to capture surface images of the number of diamond facets, other than the diamond table facet under the collimated light, cause illumination of the diamond table facet with dark field illumination, cause the digital camera to capture internal images through the diamond table facet at a plurality of focal depths under the dark field illumination, and cause the digital camera to capture internal images through the number of diamond facets, other than the diamond table facet, at a plurality of focal depths under the dark field illumination, process the set of surface images of the diamond table facet, the set of surface images of the number of diamond facets, the set of internal images through the diamond table facet, and the set of internal images of through the number of diamond facets to identify one or more clarity features from the diamond table facet or any facet of the sample diamond, and assign a clarity grade for the sample diamond based on the one or more identified clarity features.
9 . The system of claim 8 wherein the system further includes a stage motor configured to rotate the stage, a slope motor configured to adjust slope of the digital camera to the stage, and a focus adjustment motor configured to adjust focus of the digital camera to the stage.
10 . The system of claim 9 wherein the system further includes a back silhouette light source and a silhouette camera configured to capture a plurality of digital silhouette images of the sample diamond on the rotating stage.
11 . The system of claim 8 wherein the computer is further configured to analyze the surface images by localizing surface and surface reaching features from the surface images of each facet using boundary analysis or contrast comparison of pixels within each image;
identify a type of surface and surface reaching features in the images wherein a type includes a feather, pit, scratch, polish lines, surface graining, or burns;
classify a degree of surface and surface reaching features based on a size and a contrast of the surface features by comparing a detected inclusion size and contrast to a threshold value previously determined;
analyze the internal images by localizing internal and surface reaching internal features from the captured internal digital images from different azimuth angles and depths;
identify a type of internal and surface reaching internal features, wherein a type includes a feather, pinpoint, cloud, or internal graining;
differentiate internal inclusions using the surface analysis;
classify a degree of internal and surface reaching internal features based on size and contrast of the internal features using pixel counting and contrast; and
generate the clarity grade using the surface and internal analyses.