Book Image

Computer Vision for the Web

By : Foat Akhmadeev
Book Image

Computer Vision for the Web

By: Foat Akhmadeev

Overview of this book

This book will give you an insight into controlling your applications with gestures and head motion and readying them for the web. Packed with real-world tasks, it begins with a walkthrough of the basic concepts of Computer Vision that the JavaScript world offers us, and you’ll implement various powerful algorithms in your own online application. Then, we move on to a comprehensive analysis of JavaScript functions and their applications. Furthermore, the book will show you how to implement filters and image segmentation, and use tracking.js and jsfeat libraries to convert your browser into Photoshop. Subjects such as object and custom detection, feature extraction, and object matching are covered to help you find an object in a photo. You will see how a complex object such as a face can be recognized by a browser as you move toward the end of the book. Finally, you will focus on algorithms to create a human interface. By the end of this book, you will be familiarized with the application of complex Computer Vision algorithms to develop your own applications, without spending much time learning sophisticated theory.
Table of Contents (13 chapters)

Basic edge detection


For most Computer Vision applications, you process an image but you do not actually need to get all the information from it. For example, sometimes you just need to get the shape information to find an appropriate object. There is a huge topic in the field of image processing called edge detection. Methods related to that topic, search for points where pixel brightness changes dramatically. The extracted information aims to capture changes in the properties of an image. To understand the concept better and to see how the basic edge information can be extracted from an image, we will discuss different edge filters (or operators) starting with the Sobel filter.

The Sobel filter

The Sobel operator or Sobel filter is common and widely used. It helps to detect edges and transitions in images. The Sobel operator uses two kernels during the processing—one for horizontal changes in brightness and another for vertical changes. Its kernel values are focused not on the current pixel...