Book Image

OpenGL ES 3.0 Cookbook

By : Parminder Singh
Book Image

OpenGL ES 3.0 Cookbook

By: Parminder Singh

Overview of this book

<p>"Write once, use anywhere" is truly the power behind OpenGL ES and has made it an embedded industry standard. The library provides cutting-edge, easy-to-use features to build a wide range of applications in the gaming, simulation, augmented-reality, image-processing, and geospatial domains.</p> <p>The book starts by providing you with all the necessary OpenGL ES 3.0 setup guidelines on iOS and Android platforms. You'll go on to master the fundamentals of modern 3D graphics, such as drawing APIs, transformations, buffer objects, the model-view-project analogy, and much more. The book goes on to deal with advanced topics and offers a wide range of recipes on the light shading, real-time rendering techniques with static and procedure textures to create stunning visualizations and runtime effects.</p>
Table of Contents (21 chapters)
OpenGL ES 3.0 Cookbook
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Detecting scene edges with the Sobel operator


Edge detection is an image-processing technique used to detect boundaries in an image. It is widely used in the field of computer vision, data visualization, and surface topology. For example, the pencil sketch effect of an image is nothing, but an application of edge detection algorithm. This recipe will demonstrate the edge detection technique using the Sobel operator or filter.

A Sobel filter measures the change in the gradient of an image in which it recognizes the regions of an image where the frequency of the color transition is higher. These higher transition regions shows sharp changes in the gradient that eventually correspond to the edges. The Sobel operator uses convolution kernels to detect the edge portions in the image. A convolution kernel is a matrix that contains predefined weights that formulate the calculation of the current pixel based on the neighboring pixels intensity and weights contained in the convolution matrix itself...