Book Image

Image Processing with ImageJ - Second Edition

Book Image

Image Processing with ImageJ - Second Edition

Overview of this book

Advances in image processing have been vital for the scientific and technological communities, making it possible to analyze images in greater detail than ever before. But as images become larger and more complex, advanced processing techniques are required. ImageJ is built for the modern challenges of image processing – it’s one of the key tools in its development, letting you automate basic tasks so you can focus on sophisticated, in depth analysis. This book demonstrates how to put ImageJ into practice. It outlines its key features and demonstrates how to create your own image processing applications using macros and ImageJ plugins. Once you’ve got to grips with the basics of ImageJ, you’ll then discover how to build a number of different image processing solutions. From simple tasks to advanced and automated image processing, you’ll gain confidence with this innovative and powerful tool – however and whatever you are using it for.
Table of Contents (17 chapters)
Image Processing with ImageJ Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
2
Basic Image Processing with ImageJ
Index

Feature extraction


As we saw in the earlier sections, filters can be used to isolate different frequencies using filters. By convolving an image with a Mexican hat filter, high frequencies are preserved, while using the box filter has the opposite effect. The difference between the filters in this section and the filters in the previous section is in specificity. The Mexican hat filter had no preference for direction. When there was an edge with sharp contrast (quick change in intensity), the filter had a strong effect. However, sometimes, you are only interested in a specific type of edge. Let's assume that we only want to detect vertical edges. The Mexican hat filter will give us all the edges in all directions, not just the vertical ones. This will be the topic of the following section.

Edge detection

To detect only vertical edges, we need to create a kernel that emphasizes pixels that are in a vertical orientation. The following kernels can detect different orientations of edges:

To perform...