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Threshold replacement in image processing techniques is significant because it allows for the segmentation of images based on pixel intensity levels. By setting a threshold value, pixels above or below this value can be replaced with specific colors or values, which helps in isolating objects or features of interest in an image. This process is crucial for tasks like object detection, image enhancement, and pattern recognition in various fields such as medicine, surveillance, and remote sensing.

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