Image Binarization Algorithms: Otsu, Kittler Minimum Error Thresholding, and Niblack Methods

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Image binarization algorithms including Otsu's method, Kittler minimum error thresholding, and Niblack binarization. These are classical algorithms for converting images to binary format. The implementations are custom-coded and thoroughly tested for correctness. The attachment contains detailed usage instructions with code examples and parameter explanations.

Detailed Documentation

This article introduces three classical image binarization algorithms: Otsu's method, Kittler minimum error thresholding, and Niblack binarization. These highly effective algorithms convert grayscale images into binary images by determining optimal threshold values through different statistical approaches. Otsu's method maximizes inter-class variance, Kittler's algorithm minimizes classification error probability, while Niblack adapts thresholds based on local mean and standard deviation. The implementations feature optimized calculation methods including histogram analysis and sliding window techniques for efficient processing. All algorithms have been custom-developed and rigorously tested to ensure computational accuracy and performance stability. The attached documentation provides comprehensive usage guidelines with code implementation details, parameter configuration examples, and practical application scenarios.

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