Book Image

iOS Application Development with OpenCV 3

By : Joseph Howse
4 (1)
Book Image

iOS Application Development with OpenCV 3

4 (1)
By: Joseph Howse

Overview of this book

iOS Application Development with OpenCV 3 enables you to turn your smartphone camera into an advanced tool for photography and computer vision. Using the highly optimized OpenCV library, you will process high-resolution images in real time. You will locate and classify objects, and create models of their geometry. As you develop photo and augmented reality apps, you will gain a general understanding of iOS frameworks and developer tools, plus a deeper understanding of the camera and image APIs. After completing the book's four projects, you will be a well-rounded iOS developer with valuable experience in OpenCV.
Table of Contents (13 chapters)
iOS Application Development with OpenCV 3
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Chapter 5. Classifying Coins and Commodities

Previously, in Chapter 4, Detecting and Merging Faces of Mammals, we used Haar or LBP cascades to classify the faces of humans and cats. We had a very specific classification problem because we wanted to blend faces, and conveniently, OpenCV provided pretrained cascade files for human and cat faces. Now, in our final chapter, we will tackle the broader problem of classifying a variety of objects without a ready-made classifier. Perhaps we could train a Haar or LBP cascade for each kind of object, but this would be a long project, requiring a lot of training images. Instead, we will develop a detector that requires no training and a classifier that requires only a few training images. Along the way, we will practice the following tasks:

  1. Segment an image into foreground and background regions based on pixel colors. The result of the segmentation is a binary image called a mask. Each pixel in the mask is marked as either foreground (black) or background...