Book Image

Image Processing with ImageJ

Book Image

Image Processing with ImageJ

Overview of this book

Digital image processing is an increasingly important field across a vast array of scientific disciplines. ImageJ's long history and ever-growing user base makes it a perfect candidate for solving daily tasks involving all kinds of image analysis processes. Image Processing with ImageJ is a practical book that will guide you from the most basic analysis techniques to the fine details of implementing new functionalities through the ImageJ plugin system, all of it through the use of examples and practical cases. ImageJ is an excellent public domain imaging analysis platform that can be very easily used for almost all your image processing needs. Image Processing with ImageJ will start by showing you how to open a number of different images, become familiar with the different options, and perform simple analysis operations using the provided image samples. You will also learn how to make modifications through ImageJ filters and how to make local measurements using the selections system. You will also find the instructions necessary to record all the steps you perform so they can be saved and re-run on the same image to ensure analysis reproducibility. Finally, you will get to know some different ImageJ plugins and will learn how to implement your own.
Table of Contents (13 chapters)
Image Processing with ImageJ
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Particle analysis


A potentially useful task in many imaging fields, especially in microscopy, is the automatic detection and measurement of the particles present in a given image. Consider the following one, taken from the original set of tuberculosis images that we have presented previously (tuberculosis_full.tif):

Note that the zoom level has been reduced to show the whole image on the page. If you open that image on ImageJ, you can see that there are many small green objects: those are the Mycobacterium tuberculosis bacilli, and we want to count them. How many of them are there in the image? One way of accomplishing that task is to count them manually. That can be hard even for a single image, and think about having to count hundreds of them. So, let's see if we can get ImageJ to do the job for us.

In the first place, note that this is an RGB color image. When we run the cursor over the image, a triplet of values is shown on the status bar on the main window (one for each Red, Green, and...