Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence
Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence by Dmitrijs Cudihins
English | 2018 | ISBN: 1788998796 | 202 Pages | EPUB | 10 MB

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking.
Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code.
This book begins by introducing you to Julia’s image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia’s interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned.
By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.
What you will learn

  • Analyze image metadata and identify critical data using JuliaImages
  • Apply filters and improve image quality and color schemes
  • Extract 2D features for image comparison using JuliaFeatures
  • Cluster and classify images with KNN/SVM machine learning algorithms
  • Recognize text in an image using the Tesseract library
  • Use OpenCV to recognize specific objects or faces in images and videos
  • Build neural network and classify images with MXNet