Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.

Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this book will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects.
Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used Computer Vision techniques to build your own Open CV projects from scratch.
By the end of this book, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.

Osoby które kupowały "OpenCV By Example. Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3", wybierały także:

• Windows Media Center. Domowe centrum rozrywki 66,67 zÅ‚, (8,00 zÅ‚ -88%)
• Ruby on Rails. Ćwiczenia 18,75 zÅ‚, (3,00 zÅ‚ -84%)
• Przywództwo w Å›wiecie VUCA. Jak być skutecznym liderem w niepewnym Å›rodowisku 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Scrum. O zwinnym zarzÄ…dzaniu projektami. Wydanie II rozszerzone 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Od hierarchii do turkusu, czyli jak zarzÄ…dzać w XXI wieku 58,64 zÅ‚, (12,90 zÅ‚ -78%)

Spis treści

OpenCV By Example. Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3 eBook -- spis treści

• 1. Getting Started with OpenCV
• 2. Introduction to OpenCV basics
• 3. Learning Graphical User interface and basic filtering
• 4. Delving into Histogram and filters
• 5. Automating Optical Inspection, Object segmentation and detection
• 6. Learning Object Classification
• 7. Detecting Face Parts and Overlaying Masks
• 8. Video surveillance and Background removal
• 9. Learning Object Tracking
• 10. Developing Segmentation algorithms for Text Recognition
• 11. Text recognition with Tesseract