Classic Otsu Image Segmentation Algorithm
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In the field of image segmentation, the classic Otsu algorithm is one of the most widely used methods. The core principle of this algorithm involves finding the valley between two peaks in the image's grayscale histogram and using this as the threshold to divide the image into two regions. This approach is typically implemented by calculating the image histogram and then determining the threshold that maximizes the inter-class variance between foreground and background regions. The main advantages of this method lie in its simplicity and computational efficiency. However, the algorithm's limitations are also evident - for images with uneven illumination or significant noise, the segmentation performance can be compromised. Consequently, researchers have developed numerous improved algorithms based on Otsu's method to better adapt to various image segmentation scenarios, including adaptations for multi-level thresholding and noise-resistant implementations.
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