Alternative Methods for Counting Overlapping Grains in Digital Images

Authors:
André R. Marçal
Affiliations:
Faculdade de Ciências, Universidade do Porto, DMA, Porto, Portugal 4169-007
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

Citing 5
Cited 0

Optimal reconstructive &tgr;-openings for disjoint and statistically modeled nondisjoint grains

Signal Processing
Digital Image Processing

Digital Image Processing
Computer and Robot Vision

Computer and Robot Vision
Digital Image Processing Using MATLAB

Digital Image Processing Using MATLAB
Image Analysis and Mathematical Morphology

Image Analysis and Mathematical Morphology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Standard granulometry methods are used to count the number of disjoint grains in digital images. For the case of overlapping grains, the standard method is not effective. Two alternative methods for counting overlapping grains in digital images are proposed. The methods are based on mathematical morphology and are suitable for grains of circular shape. The standard and overlapping methods were tested with a Monte-Carlo simulation using 32500 synthetic images with various grain sizes and quantities, as well as different levels of noise. The overall average counting error for all images tested with intermediate amount of noise (zero mean Gaussian noise with ï戮驴= 0.05) was 6.03% for the standard method, and 4.40% and 3.56% for the overlapping methods. The performance of the proposed methods was found to be much better than the standard method for images with significant overlap between grains.