https://github.com/kimiaak/specoptiblend

This open-source software aids in identifying the ideal ratio of each spectral data component for the reconstruction of a sample when only its spectral information is available. Here, it was used to reconstruct Western University's Purple color but, it can be applied to any other color.
https://github.com/kimiaak/specoptiblend

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This open-source software aids in identifying the ideal ratio of each spectral data component for the reconstruction of a sample when only its spectral information is available. Here, it was used to reconstruct Western University's Purple color but, it can be applied to any other color.

• Host: GitHub
• URL: https://github.com/kimiaak/specoptiblend
• Owner: KimiaaK
• Created: 2023-11-02T18:09:48.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-10T01:57:48.000Z (10 days ago)
• Last Synced: 2024-11-10T02:19:53.189Z (10 days ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 3.66 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Creating Custom 3D-Printing Material Colors Using Optical Modeling of Waste Plastic (SpecOptiBlend)

This open-source software aids in identifying the ideal ratio of each spectral data component for the reconstruction of a sample when only its spectral information is available.

Here, it was used to reconstruct Western University's Purple color but, it can be applied to any other color.

## A Background

1. Subtractive Color Mixing:

   - Light interacts with substances (dyes/pigments).

   - Certain wavelengths are absorbed, and others are reflected.

   - Results in perceived colors.

  

Subtractive Mixing:



Additive Mixing:



2. Kubelka-Munk Theory

   - It models how light interacts with an opaque substance.

   - It is used to predict how light is absorbed and scattered.

   - Absorption (K), and Scattering (s)

   - 

## Objectives

To reconstruct the reflectance curve of the target sample by finding the optimized proportion of each color in the mix to reach the lowest color difference and RMS.

- Reflectance ~> XYZ values ~> L*, a*,b*

- Objective Function (Finds proportions to minimize ∆𝐸 𝑎𝑛𝑑 𝑅𝑀𝑆 𝑏𝑎𝑠𝑒𝑑 𝑜𝑛 𝑘𝑢𝑏𝑒𝑙𝑘𝑎−𝑀𝑢𝑛𝑘 𝑣𝑎𝑙𝑢𝑒𝑠  𝑎𝑠 𝑖𝑛𝑖𝑡𝑖𝑎𝑙 𝑔𝑢𝑒𝑠𝑠 simultaneously)

- Add weights to crucial parts of the spectrum. (400-450 nm) and (620-700nm).

- Optimizations to compare:

   - L-BFGS-B

   - Nelder-Mead

   - SLSQP

- Reconstruct using the optimized proportions.

## Results

- Experiment Verification:

  - Reconstructed navy blue and western purple to confirm experiment results.

  - Reconstructed Lego Pink as an industrial Example.

- Impact of Color Variety:

  - Tested reconstruction accuracy using different color sets:

      - Reconstructing both target colors with only four colors: cyan, magenta, black, and green.

- Software Testing:

   - Utilized online color pickers to initiate reconstruction with RGB values.

1. Reconstruction of the Western Purple  using three optimization algorithms.

    - the reconstructed color using the plastics and Nelder-Mead method.  

    - the original purple used to reproduce.



2. Reconstruction of the Navy Blue using three optimization algorithms (8 initial colors).

    - the reconstructed color using the plastics and Nelder-Mead method.  

    - the original purple used to reproduce.



3. Reconstruction of the Lego Pink using the optimized algorithm (8 initial colors). (Nelder-Mead)



##Conclusion

1. Nelder-Mead Optimization provides the closest results to actual colors compared to other algorithms.

2. Limitations of Online RGB Values:

  -  Online RGB lacks spectral data, limiting its use in precise color mixing returning a DeltaE of 17 for Western Purple.

  -  Essential for initial reconstructions; comparison samples may not be directly available.

3. A greater number of colors improves accuracy due to enhanced data availability at each wavelength.