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.

Embedded Linux and computer vision Program Highlights

Course Duration

33 Working days
9 Weekends



Delivery Mode

Classroom Training

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



  • Introduction to Linux and Computer vision
  • Introduction to computer vision approach
  • Requirements for computer vision
  • Preparation for computer vision libraries
  • Setting up computer for compiling libraries
  • Cmake
  • Python-dev and build essential libraries
  • OpenCV introduction with python

Image and video Basics with
OpenCV & SimpleCV

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

Advance Operations in image & video
with OpenCV & SimpleCV

  • Morphological Transformations
  • Canny edge detection and gradients
  • Template matching
  • Grabcut foreground extraction
  • Corner detection
  • Feature matching (Homography)
  • MOG background detection
  • Haar Cascade Object training
  • Eye & Face detection
  • Creating your own Haar


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