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Image Segmentation: Thresholding Techniques by dieuth is a document available to read on EtoBox.

This document summarizes different image thresholding techniques. It defines thresholding as a type of image segmentation that converts images to binary black and white. Six main types of thresholding are described: histogram-based, clustering-based, entropy-based, object attribute-based, spatial-based, and local-based. Basic, band, p-tile, optimal, and adaptive thresholding techniques are then explained in detail. Examples are provided to compare the performance of each technique on different types of imag

Author

dieuth

Language

EN