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. Author manuscript; available in PMC: 2017 Jun 5.
Published in final edited form as: Abdom Radiol (NY). 2016 May;41(5):854–861. doi: 10.1007/s00261-016-0646-6

Figure 3.

Figure 3

Example for the calculation of texture features from a grey-level co-occurrence matrix (GLCM). For the sake of simplicity, a 4 × 4 pixel grey-scale image with only three grey-levels (i.e. white, grey, and black) was chosen. In Step 1, a GLCM is deducted from this image by considering the relationship of every pixel to its neighborhood. We start with the co-occurrence of ‘black + black’, which occurs twice in the image, as indicated by the red circles. The absolute count of the different co-occurrences is recorded in a table, which - after its completion - is named the GLCM. In Step 2, the GLCM is normalized so that each cell doesn’t contain a count but the probability of every possible co-occurrence. These probabilities provide the basis for the calculation of the various ‘texture features’ according to the equations shown (Step 3).