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: image processing
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 …
‘ImageJ’ for image processing
The ImageJ software is a powerful freely available tool for image processing and analysis. It is developed and maintained by the National Institutes of Health (NIH). One of its most important benefits is the fact that it is cross platform as it was developed in Java. In addition ImageJ also offers a very active developers …
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 …