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Cross-image co-occurrence matrix (CICM) implementation in Python.

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CICM

Implementation of a cross-image co-occurrence matrix (CICM) in python, which computes a version of the common gray-level co-ocurrence matrix (GLCM) between different images, or channels of the same image.

Python's package scikit-image implements the calculation of the GLCM matrix through method graycomatrix in the feature module. However, since this method only accepts one image as parameter, it is not possible to compare pixel co-occurrence between pixels from different images.

This repository provides a similar functionality as that of method graycomatrix, with the addition of a second image argument to compare pixels with. Run tests show average computation times in the order of O(n^5) as a function of the image size (constant gray level), and O(log(N)) as a function of the number of gray levels (for constant image size), which is fast enough for common image sizes.

Graph representing how computation times change, as a function of the number of gray levels, for method cicm compared with scikit-image's graycomatrix Graph representing how computation times change, as a function of the image size, for method cicm compared with scikit-image's graycomatrix

Performance graphs for method cicm compared with scikit-image's graycomatrix. Computation times as a function of the number of gray levels (left), and image size (right).

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