Book Image

Hands-On Computer Vision with Julia

By : Dmitrijs Cudihins
Book Image

Hands-On Computer Vision with Julia

By: Dmitrijs Cudihins

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)
9
Assessments

Derived operations

Opening and closing are the other two primary operators of mathematical morphology. They are both derived from the two base operations—erosion and dilation. Like those functions, they are normally used on binary or grayscale images.

From a technical perspective, opening and closing can be described in the following ways:

  • Opening: This is the dilation of the erosion
  • Closing: This is the erosion of the dilation

It is essential to note that erosion is not the inverse of dilation. In general, eroding and dilating produces an image different than the original, and identical results are created by chance.

As with base morphological operators, the exact operation is determined by a structuring element, which in Julia is fixed to a 3x3 block.

Image opening

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