Binarization
An image preprocessing technique that forces every pixel into one of two classes, pure black or pure white, eliminating intermediate gray values. This simplifies the input boundaries for subsequent image processing algorithms.
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Binarization is the process of converting a grayscale or color image into an image with only two pixel values, black and white (typically 0 and 255).
For assets intended for stickers or printing, binarization should use pure 0 and pure 255, with no gray levels in between.
Applying thresholding (binarization) to the image before tracing, with a threshold around 128, can eliminate grayscale gradients and make the tracing algorithm output single-layer, clean paths.
The author proposed a two-step processing strategy: first apply auto contrast or normalization to the grayscale image, then binarize at 128, which effectively removes gray edges. After reprocessing, all 11 rejected files passed, and among the subsequent 300 assets there were zero edge-related rejections.
All Facts (4)
Binarization is the process of converting a grayscale or color image into an image with only two pixel values, black and white (typically 0 and 255).
50%UnverifiedFor assets intended for stickers or printing, binarization should use pure 0 and pure 255, with no gray levels in between.
50%UnverifiedApplying thresholding (binarization) to the image before tracing, with a threshold around 128, can eliminate grayscale gradients and make the tracing algorithm output single-layer, clean paths.
50%UnverifiedThe author proposed a two-step processing strategy: first apply auto contrast or normalization to the grayscale image, then binarize at 128, which effectively removes gray edges. After reprocessing, all 11 rejected files passed, and among the subsequent 300 assets there were zero edge-related rejections.
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