Systems and methods for evaluating the appearance of a gemstone

Abstract

Of the “four C's,” cut has historically been the most complex to understand and assess. This application presents a three-dimensional mathematical model o study the interaction of light with a fully faceted, colorless, symmetrical round-brilliant-cut diamond. With this model, one can analyze how various appearance factors (brilliance, fire, and scintillation) depend on proportions. The model generates images and a numerical measurement of the optical efficiency of the round brilliant-called DCLR—which approximates overall fire. DCLR values change with variations in cut proportions, in particular crown angle, pavilion angle, table size, star facet length, culet size, and lower girdle facet length. The invention describes many combinations of proportions with equal or higher DCLR than “Ideal” cuts, and these DCLR ratings may be balanced with other factors such as brilliance and scintillation to provide a cut grade for an existing diamond or a cut analysis for prospective cut of diamond rough.

Description

PRIORITY [0001] This application is a divisional application of U.S. patent application Ser. No. 09 / 687,759, filed Oct. 20, 2000.BACKGROUND OF THE INVENTION [0002] The quality and value of faceted gem diamonds are often described in terms of the “four C's”: carat weight, color, clarity, and cut. Weight is the most objective, because it is measured directly on a balance. Color and clarity are factors for which grading standards have been established by GIA, among others. Clamor for the standardization of cut, and calls for a simple cut grading system, have been heard sporadically over the last 27 years, gaining strength recently (Shor, 1993, 1997; Nestlebaum, 1996, 1997). Unlike color and clarity, for which diamond trading, consistent teaching, and laboratory practice have created a general consensus, there are a number of different systems for grading cut in round brilliants. As described in greater detail herein, these systems are based on relatively simple assumptions about the re...

AI Technical Summary

Benefits of technology

[0016] Within the mathematical model, all of the factors considered important to diamond appearance—the diamond itself, its proportions and facet arrangement, and the lighting and observation conditions—can be carefully controlled, and fixed for a given set of analyses. However, such control is nearly impossible to achieve with actual diamonds. The preferred model described herein also enables a user to examine thousands of sets of diamond proportions that would not be economically feasible to create from diamond rough. Thus, use of the model allows the user to determine how cut proportions affect diamond appearance in a more comprehensive way than would be possible through observation of actual diamonds. In one preferred embodiment, the system, method and computer programs use to model the optical response of a gemstone use Hammersley numbers to choose the direction and color for each element of light refracted into a model gemstone (which defines the gemstone facets) to be eventually reflected by the model gemstone's virtual facets, and eventually exited from the model gemstone to be measured by a model light detector. The gemstone is then ultimately graded for its optical properties based on the measurement of said exited light elements from the gemstone model.

Problems solved by technology

However, no system described to date has adequately accounted for the rather complex relationship between cut proportions and two of the features within the canonical description of diamond appearance—fire and scintillation.

Yet each of these terms cannot be expressed mathematically without making some assumptions and qualifications.

However, since Tolkowsky only considered one refractive index, he could not verify the extent to which any of his rays would be dispersed.

However, regardless of what standard light modeling technique is used, the diamond modeling programs to date have failed to define effective metrics for diamond cut evaluation.

Spinning the data in this way greatly reduces the richness of information, adversely affecting the aptness of the metrics based on it.

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