Stereoscopic Method For Highlighting The Variation Of Colors
Highlight and identify the variation of an unknown color from known colors for any binocular color combination.
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Photo Width:
pixels
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Choose a target color. |
Known Colors: |
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Color: |
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— OR —
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Use our color chart or color table to find a color.
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• Gamma correction is used for contrast enhancement (0 -.255), (No decimal before number).
• Threshold is used for segmenting objects (.0 -.255 or 1.0 - 255.0), (Decimal before number).
•  Binocular color combination ratio creates a binocular combination of two colors which mixes them to produce, highlight, or identify the variation of a third color and present that color, independently, one to each eye.
• We recommend .50 (.0-.255), (Decimal before number).
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Gamma correction:
Threshold:
Binocular color combination ratio:
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Choose a photo that contains your target color. |
From our Bing™ Wallpaper Archive, |
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The algorithm will try to highlight and identify your unknown color from known colors if possible. |
Choose the eye you believe is your dominate eye. |
Eye Preference / Ocular Dominance:
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• Photos must be .jpg, or .png, not exceed 5MB, and max width by height is (w)3840px (x) (h)3840px.
• To capture the exact shade of the unknown color from your cellphone or camera a digital photo taken must be 12 megapixels or greater and be a sharp zoom index of 1.0x or in that range for best results.
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• Larger width numbers, the larger the photo.
• Width can be any number between 1 and 3840.
• NoEffect highlights or identifies no colors with no Binocular color combination.
• Transparent highlights and identifies colors with no Binocular color combination.
• Colors highlights and identifies colors on the Ocular Dominance side of the photo.
• RGBY (Red-Green & Blue-Yellow) might change existing colors a the pixel level.
• Highlighting or identifying colors is based on high photo pixel bit depth and photo quality.
• Some matched colors may not be highlighted or identified based on pixel bit depth and photo quality.
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How the algorithm can help your eyesight.
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• The algorithm can test from picturesque data for visual acuity, color deficiency, contrast sensitivity, nearsightedness, farsightedness, blurry vision caused from digital eye strain and daily caffeine use.
• The algorithm can be used to highlight, identify, and interpret any unknown color from known colors from hi-res picturesque data and identify that unknown color from known colors.
• To make an accurate color identification the algorithm will highlight the variation of the unknown color first and try to match the color from known colors to identify.
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Example from a real-user who highlighted the variation of the color red for her right dominant eye. • The algorithm may highlight the variation other colors in image data that may contain your chosen color. • In this photo her sweater, lips, hair, skin contain the color red. |
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