Universiti Teknologi Malaysia Institutional Repository

Extended gray level co-occurrence matrix computation for 3D image volume

M. Salih, Nurulazirah and Dyah Ekashanti Octorina Dewi, Dyah Ekashanti Octorina Dewi (2017) Extended gray level co-occurrence matrix computation for 3D image volume. In: 2016 8th International Conference on Graphic and Image Processing, ICGIP 2016, 29 - 31 October 2016, Tokyo, Japan.

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Official URL: http://dx.doi.org/10.1117/12.2266977


Gray Level Co-occurrence Matrix (GLCM) is one of the main techniques for texture analysis that has been widely used in many applications. Conventional GLCMs usually focus on two-dimensional (2D) image texture analysis only. However, a three-dimensional (3D) image volume requires specific texture analysis computation. In this paper, an extended 2D to 3D GLCM approach based on the concept of multiple 2D plane positions and pixel orientation directions in the 3D environment is proposed. The algorithm was implemented by breaking down the 3D image volume into 2D slices based on five different plane positions (coordinate axes and oblique axes) resulting in 13 independent directions, then calculating the GLCMs. The resulted GLCMs were averaged to obtain normalized values, then the 3D texture features were calculated. A preliminary examination was performed on a 3D image volume (64 x 64 x 64 voxels). Our analysis confirmed that the proposed technique is capable of extracting the 3D texture features from the extended GLCMs approach. It is a simple and comprehensive technique that can contribute to the 3D image analysis.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:3D image volume, gray level co-occurrence matrix, Texture analysis, texture features
Subjects:R Medicine > RE Ophthalmology
Divisions:Biosciences and Medical Engineering
ID Code:97008
Deposited By: Widya Wahid
Deposited On:12 Sep 2022 12:15
Last Modified:12 Sep 2022 12:15

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