Cross-Entropy Based Image Thresholding

Mateusz Malik,

Przemysław Spurek,

Jacek Tabor

Abstrakt

This paper presents a novel global thresholding algorithm for the binarization of documents and gray-scale images using Cross-Entropy Clustering. In the first step, a gray-level histogram is constructed, and the Gaussian densities are fitted. The thresholds are then determined as the cross-points of the Gaussian densities. This approach automatically detects the number of components (the upper limit of Gaussian densities is required).

Słowa kluczowe: Cross-Entropy Clustering, thresholding, binarization, Otsu
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