Intelligent Engineering Systems through Artificial Neural Networks Volume 18
24 Application of Adaptive Grayscale Morphological Operators for Image Analysis
Download citation file:
- Ris (Zotero)
- Reference Manager
Accurate analysis of scan images of natural geologic and earth systems is essential when evaluating pore size distributions in porous media for better prediction of contaminant and gas transport. The recent development of an adaptive structural element for use as a grayscale morphological operator in image analysis may prove useful for evaluating soil and geologic materials. The objective of this study was to illustrate the application of an adaptive grayscale morphological operator in evaluating four synthetic images representing differential ranges in pore radii and a set of computed tomography scan images from three management treatments affecting pore size distributions in soil. The morphological operator performs the erosion and dilation of image data and the surface area is estimated as a function of changing resolution of the operator. The rate of change of the surface area was used to estimate the multi-fractal dimension (signature) of the synthetic images as a function of changing resolution. Results show the benefits of this technique as a new analytical image analysis tool for evaluating size and distribution of particles. The upper signature differentiated pore size distributions for the three management treatments as a function of soil depth and was highly correlated with independently estimated porosity values. This tool can be used to evaluate size and spatial distributions of particles or pores within an image. Additional applications of this method include quantifying and analyzing image features from scans of soil and geologic materials.