Learning OpenCV 3 Computer Vision with Python - Second Edition
OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the development of all sorts of real-world applications, including security and surveillance.
Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.
|Course Length||7 hours 58 minutes|
|Date Of Publication||28 Sep 2015|
|Basic I/O scripts|
|Project Cameo (face tracking and image manipulation)|
|Cameo – an object-oriented design|
|Converting between different color spaces|
|The Fourier Transform|
|Custom kernels – getting convoluted|
|Modifying the application|
|Edge detection with Canny|
|Contours – bounding box, minimum area rectangle, and minimum enclosing circle|
|Contours – convex contours and the Douglas-Peucker algorithm|
|Line and circle detection|