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  • Book Overview & Buying Hands-On Computer Vision with Julia
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Hands-On Computer Vision with Julia

Hands-On Computer Vision with Julia

By : Dmitrijs Cudihins
4 (1)
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Hands-On Computer Vision with Julia

Hands-On Computer Vision with Julia

4 (1)
By: Dmitrijs Cudihins
Buy this Book

Overview of this book

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.
Table of Contents (11 chapters)
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Preface
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Preface
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Who this book is for
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What this book covers
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To get the most out of this book
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Get in touch
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1
Getting Started with JuliaImages
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Getting Started with JuliaImages
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Technical requirements
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Setting up your Julia
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Reading images
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Saving images
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Using test images
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Previewing images
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Cropping, scaling, and resizing
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Rotating images
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Summary
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Questions
2
Image Enhancement
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Image Enhancement
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Technical requirements
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Images as arrays
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Applying image filters
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Summary
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Questions
3
Image Adjustment
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Image Adjustment
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Technical requirements
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Image binarization
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Fundamental operations
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Derived operations
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Summary
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Questions
4
Image Segmentation
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Image Segmentation
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Technical requirements
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Supervised methods
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Unsupervised methods
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Summary
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Questions
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Further reading
5
Image Representation
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Image Representation
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Technical requirements
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Understanding features and descriptors
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BRIEF – efficient duplicate detection method
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ORB, rotation invariant image matching
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BRISK – scale invariant image matching
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FREAK – fastest scale and rotation invariant matching
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Summary
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Questions
6
Introduction to Neural Networks
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Introduction to Neural Networks
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Technical requirements
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Introduction
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First steps with the MNIST dataset
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Multiclass classification with the CIFAR-10 dataset
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Classifying cats versus dogs
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Reusing your models
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Summary
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Questions
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Further reading
7
Using Pre-Trained Neural Networks
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Using Pre-Trained Neural Networks
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Technical requirements
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Introduction to pre-trained networks
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Predicting image classes using Inception V3
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Predicting an image class using MobileNet V2
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Extracting features generated by Inception V3
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Extracting features generated by MobileNet V2
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Transfer learning with Inception V3
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Summary
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Questions
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Further reading
8
OpenCV
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OpenCV
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Technical requirements
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Troubleshooting installation of Open CV
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First steps with OpenCV
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Image capturing from web camera
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Face detection using Open CV
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Object detection using MobileNet-SSD
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Summary
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Questions
9
Assessments
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Assessments
10
Other Books You May Enjoy
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Other Books You May Enjoy
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Image Adjustment

This chapter will guide you through the ImageMorphology package.

Morphological transformations are simple mathematical operations applied to a binary or grayscale image. They are used to remove small noise; shrink, separate, or identify an object; and increase the object size or background space.

The following topics will be covered in this chapter:

  • Image erosion and dilation
  • Image opening and image closing
  • Top-hat and bot-hat operations
  • Applying and combining techniques
CONTINUE READING
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Tech Concepts
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Programming languages
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Hands-On Computer Vision with Julia
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