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Learn Computer Vision and Image Processing in LabVIEW

Video Description

Learn computer vision and image processing from scratch in LabVIEW and build 9 vision-based apps

About This Video

  • Students completing the course will have the knowledge to create functional and useful Image processing apps.
  • Complete with working files, datasets and code samples, you’ll be able to work alongside the author as you work through each concept, and will receive a verifiable certificate of completion upon finishing the course.

In Detail

Learning the fundamentals of image processing puts a powerful and very useful tool at your fingertips. Learning computer vision in LabVIEW is easy to learn, has excellent documentation, and is the base for prototyping all types of vision-based algorithms. Jobs in image processing are plentiful, and being able to learn computer and machine vision will give you a strong background to more easily pick up other computer vision tools such as OpenCV, Matlab, SimpleCV and so on. Suitable for beginning programmers, through this course of 26 lectures and over 4 hours of content, you’ll learn all about computer vision and establish a strong understanding of the concept behind image processing algorithms. Each chapter closes with exercises in which you will develop your own vision-based apps, putting your new learned skills into practical use immediately. Starting with the installation of the LabVIEW Vision Development Toolkit, this course will take you through the main and fundamental image processing tools used in industry and research. At the end of this course you will be able to create the following apps:

App 1 - Counting M&Ms in an image,

App 2 - Colour segmentation and tracking,

App 3 - Coin blob detection

App 4 - Blob range estimation

App 5 - Lane detection and ruler width measurement

App 6 - Pattern or template matching to detect complex objects

App 7 - Object tracking

App 8 - Barcode recognition

App 9 - Optical character recognition (OCR)

With these basic and advanced algorithms mastered, the course will take you through the basic operation of the theory behind each algorithm as well how they applied in real-world scenarios.

Table of Contents

  1. Chapter 1 : Basics of LabVIEW Vision Development Module
    1. Introduction to LabVIEW Computer and Machine Vision Course 00:02:33
    2. Download & Install LabVIEW development Module 00:06:59
    3. What is Computer Vision and Machine Vision 00:08:06
    4. [Exercise] Acquiring Images from Camera 00:07:20
    5. [Exercise] Overlaying Text and Converting to LabVIEW VI 00:05:59
  2. Chapter 2 : Color Processing
    1. Introduction to Color Processing 00:05:42
    2. [Exercise] First App - Count M&Ms in an image 00:09:07
    3. [Exercise] Second App - Color Segmentation and Tracking 00:12:18
  3. Chapter 3 : Basic Feature Detection
    1. Introduction to Feature Detection 00:05:14
    2. [Exercise] Third App - Coin Blob Detection 00:07:05
    3. [Exercise] Fourth App - Blob Range Estimation 00:14:38
  4. Chapter 4 : Lines and Edges
    1. Introduction to Edge Detection 00:08:01
    2. [Exercise] Fifth App - Ruler Edge Measure and Simple Lane Detection 00:08:34
  5. Chapter 5 : Advanced Feature Detection
    1. Advanced Feature Detection - Template Matching 00:07:02
    2. Advanced Feature Detection - Optical Flow 00:02:37
    3. Advanced Feature Detection - Optical Character Recognition (OCR) 00:02:18
    4. Advanced Feature Detection - Bar Code Recognition (OCR) 00:01:34
    5. Advanced Feature Detection - Feature Correspondence 00:04:16
    6. [Exercise] Sixth App - Pattern Matching 00:08:59
    7. [Exercise] Seventh App - Object Tracking 00:03:35
    8. [Exercise] Eigth App - Barcode Recognition 00:05:21
    9. [Exercise] Ninth App - Optical Character Recognition (OCR) 00:05:14
  6. Chapter 6 : Conclusion and Bonus Section
    1. A 3-Step Vehicle Detection Framework for Range Estimation Using a Single Camera 00:11:36
    2. The Kalman Filter - Pokemon Example 00:09:30