Analyze: Width Distribution using EDM

 Estimating the largest width as in the previous post [Link] is interesting but in most cases, we want a distribution of widths...

Analyze: Calculating the width of an object

After the length [Link], the other important parameter to measure is the width of the object of interest. This can be deduced from the euclidean distance map (EDM). Here are some examples...

Analyze: Pixel connectivity - Part II

Second part about pixel connectivity. How to precisely measure a length by counting pixels with Analyze > Analyze Particles... ?

Analyze: Pixel connectivity

In a previous post [Link], we were able to measure a distance between two points or the length of a sample by counting the number of pixels thanks to Analyze > Analyze Particles... . However, the result is directly dependent of the pixel connectivity...

Enhancement: Subtract Background

In ImageJ, non uniform illumination may be corrected with the function Process > Subtract Background...

Enhancement: Non uniform illumination

In the Image Enhancement series, the non uniform illumination is the second main defect that you must correct in your images.

Gray-level images

In this series dedicated to digital image, gray level images are the most common images used in ImageJ.

Enhancement: Brightness/Contrast and Histogram

The previous method based on the transfer function [Link] is powerful but you have to manually define the slope and the y-intercept of the transfer function. It is faster to directly modify the histogram.

Enhancement: Brightness/Contrast and Transfer Function

The brightness and contrast of an image can be enhanced by modifying the transfer function or playing with the pixel distribution of the histogram. Here is the first part with the transfer function...

Image Enhancement: TOC

Table of Contents of the series of posts dedicated to Image Enhancement.

Measuring the length of a sample

One of the simplest parameter to measure in a segmented - binary - image is the length of your sample (a molecule, cellular or subcellular components, fibers, etc.).
I'll describe two techniques (manual and automatic) to get such information.

Graphics: Marching Squares - OOP Script

In this improved version of the Marching Squares algorithm - see description [Link] - I use an Object-Oriented Programming (OOP) approach...

Graphics: Marching Cubes - Results

From the script marchingCubes.js of the previous post [Link], here are some examples of isosurfaces rendered with Blender...

Graphics: Marching Cubes - Implementation

A javascript implementation of the Marching cubes algorithm...

Graphics: Marching Squares - No doubles

The previous implementation of the marching squares [Link] generates a lot of vertices because each segment line is defined by its own starting and ending points however all these line segments  are interconnected - forming a polyline - and this is not taken into account in the implementation. Here is a new version to reduce the number of vertices.

Graphics: Marching Squares

After describing the principle of the Marching Squares algorithm in a previous post [Link], it is time to implement it...

Graphics: Marching Squares - Javascript implementation

Last post of this series dedicated to Contoured Lines with the whole Javascript implementation of the Marching Squares algorithm described here [Link] and there [Link]...

Graphics: Marching Squares - Rendering with Blender

In the previous post, we wrote a Javascript program to compute the contour lines of an object of interest and save the results - a set of (X,Y) coordinates - in a Wavefront OBJ file.
The last step is to render this geometry in Blender [Link] - a very powerful and popular 3D software...

Learning Tomography: Data Collection

Even though this blog is not focused on the experimental devices, it is interesting to have some ideas about the experimental data collection. I created videos to explain the various strategies used in science...