Learn Computer Vision and Image Processing in LabVIEW

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16
Dec

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COURSE DESCRIPTION

Learn the basic concepts, tools, and functions that you will need to build fully functional vision-based apps with LabVIEW and LabVIEW Vision Development Toolkit.

Together we will build a strong foundation in Image Processing with this tutorial for beginners.

  • LabVIEW Vision Development Toolkit Download and Installation
  • Basic Feature Detection
  • Circle, Color and Edge Detection Algorithms
  • Advance Feature Detection – Pattern Matching, Object Tracking, OCR, BarCodes

LEARNING OUTCOMES

Suitable for beginning programmers, through this course of 26 lectures and over 4 hours of content, you’ll learn all of the 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 – Color 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 – Bar code 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.

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. We also offer a full  30 Day Money Back Guarantee if you are not happy with this course, so you can learn with no risk to you.

Course Curriculum

Total learning: 32 lessons / 3 quizzes Time: 10 weeks
  • Basics of LabVIEW Vision Development Module  0/7

  • Color Processing  0/5

    • Introduction to Color Processing6m
      Preview
    • [Exercise] First App – Count M&Ms in an image9m
    • [Exercise] Second App – Color Segmentation and Tracking12m
    • Color, Segmentation and Detection Slides30m
    • Color Processing 0 hours
  • Basic Feature Detection  0/5

    • Introduction to Feature Detection5m
    • [Exercise] Third App – Coin Blob Detection7m
    • [Exercise] Fourth App – Blob Range Estimation15m
    • Feature Detection Slides-422093h:-6m
    • Feature Detection 0 hours
  • Lines and Edges  0/3

    • Introduction to Edge Detection8m
    • [Exercise] Fifth App – Ruler Edge Measure and Simple Lane Detection9m
    • Lines and Edges Slides-422093h:-6m
  • Advanced Feature Detection  0/11

    • Advanced Feature Detection – Template Matching7m
    • Advanced Feature Detection – Optical Flow3m
    • Advanced Feature Detection – Optical Character Recognition (OCR)2m
    • Advanced Feature Detection – Bar Code Recognition (OCR)2m
    • Advanced Feature Detection – Feature Correspondence4m
    • [Exercise] Sixth App – Pattern Matching9m
    • [Exercise] Seventh App – Object Tracking4m
    • [Exercise] Eigth App – Barcode Recognition6m
    • [Exercise] Ninth App – Optical Character Recognition (OCR)6m
    • Advanced Feature Detection Slides30m
    • Additional Quiz 10 hours
  • Conclusion and Bonus Section  0/4

    • Cool Resources for Students1m
    • A 3-Step Vehicle Detection Framework for Range Estimation Using a Single Camera12m
    • Image processing on FPGA using LabVIEW [Journal Article]30m
    • The Kalman Filter – Pokemon Example10m

Instructors

Ritesh Kanjee has over 7 years in Printed Circuit Board (PCB) design as well in image processing and embedded control. He completed his Masters Degree in Electronic engineering and published a paper for IEEE called Vision-based adaptive Cruise control using Pattern matching (on Google Scholar). His work was implemented in LabVIEW. He works as an Embedded Electronic Engineer in defence research. He has experience in FPGA design with programming in both VHDL and Verilog.

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