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Binarization is the process of converting a multi-valued image into a binary image, where each pixel is assigned one of two possible values, typically 0 or 1. This technique is commonly used in image processing and computer vision to simplify the representation of an image, making it easier to analyze and interpret. Binarization can be achieved through various methods, including thresholding, where a specific intensity value is used to separate the foreground from the background. Other methods involve adaptive thresholding, which adjusts the threshold value based on local image characteristics, and Otsu's method, which automatically determines the optimal threshold value by maximizing the between-class variance. Binarization is widely used in applications such as optical character recognition (OCR), document analysis, and medical imaging, where the conversion of images to binary form enhances the accuracy and efficiency of subsequent processing tasks.