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Convert images to binary black-and-white using global threshold, adaptive threshold, Otsu, or advanced local methods (Niblack, Sauvola, Wolf, NICK). Essential for document binarization and object segmentation.
Segment images using global, adaptive, Otsu, Niblack, Sauvola, Wolf, and NICK thresholding.
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Thresholding converts a grayscale image to binary (black and white) by comparing each pixel to a threshold value. Pixels above the threshold become white, below become black.
Otsu\
Adaptive thresholding is best for images with uneven lighting, shadows, or varying backgrounds. It calculates a different threshold for each local region of the image.
These are advanced local binarization methods from OpenCV ximgproc. They compute per-pixel thresholds using local mean and standard deviation. Sauvola and Wolf are generally better for document images. NICK works well with low-contrast text.