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

The macro recorder


The great thing about ImageJ macros is that you don't need any prior programming experience to code them. We will also be doing some programming in any case, but the important thing to note here is that non-technical users can create their own macros effortlessly.

Remember the example that ended the previous chapter and helped us in understanding how the particle analyzer is used. Imagine that you do the analysis, store the results, and forget about it. Six months from now we need to go back to the original data and repeat the analysis (for instance, because some journal reviewers asked us to change some parameter or recheck the original procedure). Chances are that we will get an approximate result, but not the exact one, as there are several parameters that need to be set and you might not remember them. Also, suppose you need to analyze not one but hundreds of images. The semi-automatic method we used is good enough for a few images, but it is still very slow for analyzing...