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Segmentação de limite

A segmentação de limiar é útil quando a tarefa principal é separar regiões escuras de claras, isolar objetos de primeiro plano ou preparar uma imagem binária para morfologia posterior, OCR, análise de contorno ou componentes conectados. É uma das etapas de pré-processamento mais comuns em visão computacional.

Segmente o primeiro plano do segundo plano com limites globais e adaptáveis para limpeza de documentos, geração de máscaras, separação de regiões e fluxos de trabalho de binarização.

All processing runs locally in your browser. Your files never leave your device — no upload, no server, no signup required.

Frequently Asked Questions

What is image thresholding?

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.

What is Otsu thresholding?

Otsu\

When should I use adaptive thresholding?

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.

What are Niblack, Sauvola, Wolf, and NICK?

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.

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