by Kathiravan Natarajan | Released October 2018 | ISBN: 9781788293846

Detect and track objects in images and videos. Perform accurate and reliable processing tasks with Computer vision using OpenCVAbout This VideoGet a thorough understanding of the OpenCV library and all its functionalities, with practical examples.Build a strong foundation for Computer Vision by transforming images and videos using various tools and techniquesPerform image analysis by controlling, automating, recognizing, and precisely measuring data.In DetailComputer vision solves imaging problems that cannot be solved using ordinary systems and sensors. OpenCV is one of the most popular Computer Vision libraries and helps you write faster code.This course begins with the basics of loading and working with images. You will detect colored objects in your images easily. You will also use tools to build and apply filters in your photos and track objects in a video.By the end of the course, you will have a firm grasp of Computer Vision techniques using OpenCV libraries. This course will be your gateway to the world of data science.The code bundle is placed at: https://github.com/PacktPublishing/Learn-Computer-Vision-with-Python-and-OpenCV-Video Show and hide more

1. Chapter 1 : Get Started with OpenCV Libraries
   • The Course Overview 00:01:28
   • OpenCV Installation and Its Prerequisites 00:05:06
   • Exploring Images Using OpenCV 00:04:26
   • Mathematical Operations on Images 00:07:08
   • Image Transformations – Color Spaces, Resizing, Rotation, Thresholding 00:07:04
   • Image Transformations – Smoothing and Histograms 00:08:54
2. Chapter 2 : Detect Colored Objects in Images
   • Fourier Transform on Images 00:04:08
   • Morphological Operations for Cleaning 00:03:56
   • Drawing Geometric Functions on Images 00:03:44
   • Image Gradients and Edge Detection 00:03:36
   • Image Contours 00:04:51
   • Image Segmentation Using Watershed Algorithm 00:04:10
3. Chapter 3 : Feature Detection Algorithms
   • Contrast Enhancement Using Histogram Equalization 00:03:18
   • Understanding Features 00:01:59
   • Harris Corner Detection 00:02:12
   • Face Detection Using Haar Cascades 00:02:10
4. Chapter 4 : Video Analysis
   • Getting Started with Videos 00:02:38
   • Background Subtraction 00:02:16
   • Theory Behind Optical Flow 00:02:02
   • Optical Flow Using Lucas-Kanade and Dense Optical Flow 00:02:34
   • Object Tracking Using Meanshift and Camshift 00:02:43
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