Segmentation of Front Viewed Single Phase Diamond
At a Glance
Section titled âAt a Glanceâ| Metadata | Details |
|---|---|
| Publication Date | 2018-06-30 |
| Journal | International Journal of Trend in Scientific Research and Development |
| Authors | Yash Jain N, T. P. Deepa Riya Nayan Shah, Kajal Jain |
| Institutions | Jain University |
| Analysis | Full AI Review Included |
Technical Documentation and Analysis: Segmentation of Front Viewed Single Phase Diamond
Section titled âTechnical Documentation and Analysis: Segmentation of Front Viewed Single Phase DiamondâThis documentation analyzes the methods employed in the study of diamond quality assessment via image processing, focusing on how 6CCVDâs material science capabilities directly support and advance this research area, particularly in the verification and production of high-grade synthetic diamond (SCD/PCD) used in engineering applications.
Executive Summary
Section titled âExecutive SummaryâThe research details a robust, portable system for accurately estimating diamond quality (the 4 Câs) using computer vision, a methodology highly relevant to the certification and production of advanced synthetic diamond materials.
- Core Problem: Traditional, subjective naked-eye assessment of diamond quality (including synthetic CVD/HPHT stones) is inaccurate and lacks portability.
- Proposed Solution: A computer-aided system utilizing image processing (Fuzzy Segmentation and Canny Edge Detection) applied to front-viewed single-phase diamond images.
- Quality Metrics: The system successfully extracts and calculates the standard GIA 4 Câs: Cut (facet count, symmetry), Color (RGB extraction), Clarity (inclusions/blemishes), and Carat Weight (size/rarity estimation).
- Synthetic Diamond Relevance: The study explicitly addresses the challenge of differentiating high-quality CVD and HPHT synthetic diamonds from natural stones, validating the need for precise facet and clarity control during synthesis.
- Material Differentiation: Techniques reviewed highlight key distinctions between diamond types, such as the electrical conductivity of rare Boron-doped (Type II) diamonds vs. non-conductive natural stones.
- 6CCVD Value Proposition: The requirement for materials with perfect crystallographic structure, controllable doping (like Boron), and high surface finish (Ra < 1nm) directly necessitates the use of 6CCVDâs Optical Grade Single Crystal Diamond (SCD) and Boron-Doped Diamond (BDD).
Technical Specifications
Section titled âTechnical SpecificationsâThe following table extracts the key physical and gemological parameters necessary for quality assessment as detailed in the research.
| Parameter | Value | Unit | Context |
|---|---|---|---|
| Standard Quality Grade | GIA 4 Câs | N/A | Metrics for Color, Clarity, Cut, and Carat Weight |
| Required Facet Count | ≥ 58 | Facets | Benchmark for a perfectly cut diamond |
| Material Types Analyzed | Natural, CVD, HPHT | N/A | Differentiating synthetic vs. mined materials |
| Carat Weight Equivalence | 200 mg | Mass | Definition of 1 Carat (100 points) |
| Color Grade Reference | D (Colorless) to Z (Heavily Tinted) | Letter Grade | GIA classification system |
| Input Imaging Method | Infrared (IR) Camera | N/A | Used for initial image collection on dark pallets |
| Electrical Property Test | Conductivity | N/A | Used to identify Type II (Boron-doped) diamonds |
| Key Image Processing Techniques | Fuzzy Segmentation, Canny Edge Detection | N/A | Used for precise region and edge identification |
Key Methodologies
Section titled âKey MethodologiesâThe study leverages advanced computer vision to transition diamond quality assessment from subjective observation to quantitative analysis.
- Image Collection: Images of unstudded diamonds are captured using infrared cameras while the diamond is placed on a dark pallet. The viewing phase is restricted to a single, frontal perspective.
- Pre-processing: Input images are prepared to ensure a clean visual environment, typically ensuring a white, uniform background to simplify segmentation.
- Segmentation (Fuzzy + Canny): The diamond (Region of Interest) is separated from the background using a multi-step clustering process:
- Image is clustered based on fuzziness parameters and feature space.
- For each pixel (pij), the closest cluster (Cm) is identified and mapped to a preliminary segment (Sm).
- Multiple clusters with identical features are merged into a single segment.
- Canny edge detection is applied to precisely mark the boundaries and facets of all identified segments.
- Feature Extraction: Quantitative data is extracted post-segmentation, focusing on the 4 Câs:
- Color: RGB color values are extracted and compared against fixed GIA reference values.
- Clarity: Formation defects (âinclusionsâ and âblemishesâ) resulting from extreme formation conditions (heat and pressure) are analyzed.
- Cut: The shape, symmetry, and total number of facets are calculated based on the identified edges and regions.
- Carat Weight: Determined by the size and rarity attributes of the segmented image.
6CCVD Solutions & Capabilities
Section titled â6CCVD Solutions & CapabilitiesâThis research underscores the critical need for precision-engineered CVD diamond materials. 6CCVD is uniquely positioned to supply the materials necessary for replicating, validating, and extending this quality assurance methodology for demanding scientific and industrial applications.
Applicable Materials
Section titled âApplicable MaterialsâTo replicate the performance and quality standards demanded by the gemological industry, 6CCVD recommends specific grades of MPCVD material:
| Material Type | 6CCVD Product Line | Application in Quality Research |
|---|---|---|
| High Purity/Clarity Diamond | Optical Grade Single Crystal Diamond (SCD) | Essential for materials requiring perfect structural quality (high âClarityâ and âCutâ grades), such as optical windows, high-power lasers, and quantum applications. Guarantees defect-free analysis targets. |
| Electrically Conductive Diamond | Boron-Doped Diamond (BDD) | Used to study Type II diamond properties. Necessary for sensor development, electrochemical applications, and validating non-optical differentiation techniques (e.g., Moissanite/Type II electrical testing). |
| Large-Area Diamond | Polycrystalline Diamond (PCD) | Available in dimensions up to 125 mm. Ideal for developing large-scale, cost-effective detection systems or thermal management plates referenced in the paper. |
Customization Potential
Section titled âCustomization PotentialâThe methodology relies heavily on analyzing extremely precise cuts and material uniformity. 6CCVD offers unmatched capabilities tailored to these requirements:
- Precision Polishing: While the paper assesses facet quality, the baseline material must start with an ultra-smooth surface. 6CCVD provides SCD polishing services achieving surface roughness Ra < 1nm, critical for high-fidelity optical imaging and segmentation analysis. PCD can be polished to Ra < 5nm even at inch-scale dimensions.
- Custom Dimensions: We supply plates and wafers up to 125 mm (PCD) and custom SCD thicknesses (0.1 ”m to 500 ”m), enabling researchers to develop large-scale diamond testing platforms or unique sensor geometries.
- Advanced Metalization: The paper discusses electrical testing to differentiate diamond types. 6CCVD provides in-house custom metalization (including Ti, Pt, Au, Pd, W, Cu) to prepare surfaces for electrical conductivity measurements or thermal management studies.
Engineering Support
Section titled âEngineering SupportâUnderstanding the subtle differences between CVD synthesis types (Type I, Type II, BDD) and their resulting physical properties (optical, electrical, thermal) is critical for both quality assurance and device engineering.
6CCVDâs in-house PhD engineering team possesses deep expertise in the crystallographic and chemical vapor deposition processes that determine the final quality metrics analyzed by systems like the one described. We assist clients in material selection and optimization for similar projects, including:
- Controlling nitrogen incorporation for specific color centers or defect reduction.
- Achieving precise Boron doping levels for required electrical conductivity (Type II applications).
- Ensuring ultra-high SCD clarity for imaging and spectroscopy applications.
For custom specifications or material consultation, visit 6ccvd.com or contact our engineering team directly.
View Original Abstract
<p>The estimation of Quality of diamond plays a very important role in finding its price and add a market value. Quality of diamond is being estimated in the market today by just looking into the diamond thought naked or with a lens, but the quality estimated in this way is less accurate and varies from person to person in which the consumers are put into confusion whether the diamond is of good quality or not. It is sometimes difficult to identify whether the diamond is real or not. If we use a computer aided system then the estimation of quality of diamond can be estimated accurately and quickly. Thus, paper aims to develop such computer aided system which will estimate the quality of diamond based on Gemological Institute of America GIA standards. Yash Jain N | T. P. Deepa | Riya Nayan Shah | Kajal Jain "Segmentation of Front Viewed Single Phase Diamond" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd12897.pdf&lt;/p&gt;