Introduction to Camera Systems

BY
Skill Lync

Mode

Online

Duration

8 Weeks

Fees

₹ 40000

Inclusive of GST

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 40,000  (Inclusive of GST)

The fees for the course Introduction to Camera Systems is -

HeadAmount
Programme feesRs. 40,000

 

certificate availability

Yes

certificate providing authority

Skill Lync

The syllabus

Week 1: Camera Construction

  • Introduction to Geometrical Construction
  • Introduction to Optical Construction 
  • Introduction to Camera Types
  • Camera Sensor Types – CCD, CMOS 
  • Camera Sensor Types – RGGB, RCCB, RCCC
  • Different Lens Types – Normal vs Fisheye
  • Optical Parameters – Exposure Time, Shutter, White Balance, Gain

Week 2: Camera Models

  • Different Camera Models
  • Pin hole model, Perspective model, fisheye model
  • Lens Distortion – Barrel /Radial, Pin Cushion
  • Depth Of Field , Field of View 
  • Effects on changing aperture

Week 3: Camera Calibration

  • Camera Calibration
  • Introduction to Camera Parameters
  • Calibration Techniques 
  • Calibration for Intrinsic vs Extrinsic 
  • Image Undistortion

Week 4: Projective Geometry

  • Introduction to Projective Geometry
  • What is Lost / Preserved ?
  • Vanishing Lines & Points
  • Dimensionality Reduction
  • World to Image Projection
  • Orthographic Projection

Week 5: Stereo Vision

  • Introduction To Stereo Vision
  • Basic Idea of Stereo
  • Epipolar Geometry
  • Image rectification
  • Stereo Correspondence
  • Disparity Maps
  • Depth Maps

Week 6: Camera Systems

  • Low FOV Long range cameras
  • Stereo Camera 
  • FLIR  Camera
  • Fisheye Camera – Continental
  • Camera Parameters
  • Different Uses for each of them

Week 7: Image Pre-Processing

  • Image Color Spaces
  • Color Space conversions (RAW -> RGB, RGB-> GRAYSCALE, RGB->YUV , …)
  • Image Digitization, Sampling, Quantization
  • Image Interpolation, Extrapolation
  • Image Normalization
  • Image Noise – Salt and Pepper noise, Gaussian Noise , Impulse Noise
  • Image Erosion/Dilution

Week 8: Image Processing -1 (Transformations)

  • Basic Transformations and Filtering
  • Domain Transformations
  • Noise Reduction
  • Filtering as Cross Correlation
  • Convolution

Week 9: Image Processing -2

  • Basic Image Filtering and Detection techniques
  • Corners Detection
  • Edge Detection
  • Contour Detection
  • Image Thresholding Histogram
  • Histogram Equalization

Week 10: Image Processing -3

  • Features and Image Matching
  • Image Features, Invariant Features (Geometrical, Photometric Invariance) 
  • Image Descriptors
  • HOG
  • SIFT  
  • SURF 
  • Image Stitching

Week 11: Image Processing - 4

  • Introduction to Structure from Motion (SFM)
  • Epipolar Constraint and Essential Matrix
  • 3d Reconstruction 
  • Bundle Adjustment
  • SVD approach to SFM
  • SLAM example

Week 12: Introduction to Embedded Systems

  • Camera Interfaces. Ex : GMSL, LVDS
  • Communication Protocol – I2C 
  • Camera Initialization Sequence 
  • Automated Exposure Gain (AEG) Control 
  • Vision Processing Units (VPU) 
  • Graphic Processing units

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