About Embedded Linux and computer vision Program

OpenCV, simpleCV etc are very useful libraries for toying around with images. You can get interesting results without a lot of effort. But the more serious you get about image recognition, the more you find that you can't use them globally across the image. Finding the yellow car in the parking spot is a good example of the usefulness of the library and also its simplistic capabilities. It recognized a yellow patch in the image and it doesn't recognize a car in a general way.

Linux has been adapted for use in embedded environments, focusing primarily on the architecture of ARM. We provide the course to shed light on installing a cross-development environment, how to build a compact Linux version for an embedded device, how to install it on the target system, and how to test its operation.
This course is aimed at engineers who want to use the Linux system in new embedded projects and people who support the development of such systems by customers.
In five days, the course will introduce you to the architecture of an embedded Linux system through theory and practical laboratories, how to build such a system, how to take advantage of open source components to implement system features and reduce development costs, and how to develop and debug your own applications in an embedded environment.


Embedded Linux and computer vision Program Highlights

Course Duration

33 Working days
9 Weekends

Learners

50000

Delivery Mode

Classroom Training

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WHO WILL BENEFIT

Engineering Student
Working Professionals
Industry Experts
Post Graduate Students
Embedded Developers
Enthusiasts
People looking to enhance their Skillsets

COURSE CURRICULUM




Introduction

  • alt text Introduction to Linux and Computer vision
  • alt textIntroduction to computer vision approach
  • alt textRequirements for computer vision
  • alt textPreparation for computer vision libraries
  • alt text Setting up computer for compiling libraries
  • alt text Cmake
  • alt text Python-dev and build essential libraries
  • alt textOpenCV introduction with python

Image and video Basics with
OpenCV & SimpleCV

  • alt text Understanding Routing Tables
  • alt textLoading Image source
  • alt text Loading video source
  • alt text Drawing and writing on Image
  • alt textImage operations
  • alt text Image Arithmetic and Logic Operations
  • alt text Image Thresholding
  • alt text Blurring and smoothing


Advance Operations in image & video
with OpenCV & SimpleCV

  • alt text Morphological Transformations
  • alt text Canny edge detection and gradients
  • alt text Template matching
  • alt textGrabcut foreground extraction
  • alt text Corner detection
  • alt textFeature matching (Homography)
  • alt textMOG background detection
  • alt textHaar Cascade Object training
  • alt text Eye & Face detection
  • alt textCreating your own Haar


NOTE:

  • alt textThe sample programs is also been taught in development with C++ also. Development of the application with OpenCV is also been taught during the course.
  • alt textThe Course is taught in porting CV libraries to various target boards on demand.