How to calculate the contrast energy, entropy of an 3d volumetric image using GLCM feature extractactions method?

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Hla Hla
Hla Hla 2022 年 8 月 23 日
編集済み: Mandar 2023 年 2 月 6 日
Hello, I am using GLCM for the texture analysis of 3d volumetric image. But i do not solve this problem. Error occupy as follow:
Error using graycomatrix
Expected input number 1, I, to be two-dimensional.
Error in graycomatrix>ParseInputs (line 260)
validateattributes(I,{'logical','numeric'},{'2d','real','nonsparse'}, ...
Error in graycomatrix (line 167)
[I, Offset, NL, GL, makeSymmetric] = ParseInputs(varargin{:});

回答 (1 件)

Mandar
Mandar 2023 年 2 月 6 日
編集済み: Mandar 2023 年 2 月 6 日
The GLCM features can be is obtained by computing gray-level co-occurrence matrix using “graycomatrix”. Next, the “graycoprops” computes the properties such as Entropy, Homogeneity etc. by processing the matrix. Currently, “graycomatrix” function supports only 2-D intensity images as input. As a potential workaround, convert the 3-d image to the 2-d gray-level image then extract the GLCM features. In case of volumetric image, you may take the average along the one of the three dimension to get the 2-d representation using "mean" function. Refer the following documentation link to know more about GLCM properties.

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