Introduction In this post we repeat the ‘Experiment 02’ with the difference of generating high resolution images. We refer to high resolution as objects with a major axe about 136 pixels and a minor axe of 68 pixels (bigger ellipsoid in the image). We maintain the AR=2. We set scale with 136 pixels equivalent to 6 mm, simulating in …
Etiqueta: experiment
Hole analysis in image processing
Introduction In this post we want to propose the use of image processing in order to perform a complete hole analysis in porous materials. As fas as we know, features like structure, size and shape of holes become very important to define the acoustic behavior (ie. acoustic absorption) in all these kind composited materials. The …
How the image resolution affects the results?
Introduction How can the image resolution affect the statistical results on an image processing application? On your left you can observe the same object (an ellipsoid, AR=2) with different resolutions. Low resolution presents a major axe of 12 pixels and high resolution object is about 80 pixels. It seems to be evident (see previous posts, …
Number vs. Volume weighted distributions
Introduction As it was explained in a previous post, we ask the reader to present both number and volume weighted distributions for a three-particle composed material, with the following settings: A-type: high-resolution elliptical particles with major-axe of 12 mm, AR=2 B-type: high-resolution elliptical particles with major-axe of 10 mm, AR=3 C-type: high-resolution elliptical particles with major-axe of …
Number vs. Volume distributions
Introduction In this post we will analyze number vs. volume weighted distributions in a material composed by two different kinds of (synthetic) particles. In the image on the left we can check the differences between number and volume weighted particle size distributions for the same sample. As the number weighted shows how material is composed …
Feature extraction on ‘Blobs’ sample
This is our first experiment just to test our software IDE composed by ImageJ (image processing) and Matlab (statistical analysis). It is supposed that the reader knows the basics about how to operate with both ImageJ and Matlab‘s software. Sample presentation & image capture ImageJ is installed with sample images by default. To illustrate this example we use the ‘Blobs’ sample image (‘File–>Open …
Analysis of synthetic ‘rice kernels’ (low resolution)
Introduction In this post we will analyze a synthetically generated image (with Matlab) that contains objects (ellipsoids) very similar to rice kernels. As we will see, the low image resolution will result on a bad feature extraction and, consequently no valid conclusions can be extracted at the end… Individual objects We approximate the 2D projection of a …