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- W2610093756 abstract "This paper presents an approach of converting a digital image to a cross stitch pattern. The color space of the input image is quantized and classified into the nearest thread colors using k-NN classifier. Two different metrics are tested, i.e. CIE94 (which using LAB color space) and Euclidean Distance (which using RGB color space). The outputs are validated both quantitatively (using Color Coherent Vector/ CCV) and qualitatively (through human perception). The results have shown that CIE94 works best for grayscale and monochrome patterns, while Euclidean distance is more suitable for color patterns." @default.
- W2610093756 created "2017-05-05" @default.
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- W2610093756 date "2016-01-01" @default.
- W2610093756 modified "2023-09-23" @default.
- W2610093756 title "Digital color classification for colorful cross stitch threads using RGB+Euclidean Distance and LAB+CIE94" @default.
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- W2610093756 doi "https://doi.org/10.1109/icts.2016.7910290" @default.
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