Build practical applications of computer vision using the OpenCV library with Python. This book
discusses different facets of computer vision such as image and object detection tracking and
motion analysis and their applications with examples. The author starts with an introduction to
computer vision followed by setting up OpenCV from scratch using Python. The next section
discusses specialized image processing and segmentation and how images are stored and processed
by a computer. This involves pattern recognition and image tagging using the OpenCV library.
Next you'll work with object detection video storage and interpretation and human detection
using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating
complex deep learning models with CNN and RNN. The author finally concludes with recent
applications and trends in computer vision. After reading this book you will be able to
understand and implement computer vision and its applications with OpenCV using Python. You
will also be able to create deep learning models with CNN and RNN and understand how these
cutting-edge deep learning architectures work. What You Will Learn Understand what computer
vision is and its overall application in intelligent automation systems Discover the deep
learning techniques required to build computer vision applications Build complex computer
vision applications using the latest techniques in OpenCV Python and NumPy Create practical
applications and implementations such as face detection and recognition handwriting
recognition object detection and tracking and motion analysis Who This Book Is ForThose who
have a basic understanding of machine learning and Python and are looking to learn computer
vision and its applications.
