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- 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
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- Introduction to Camera Systems
Introduction to Camera Systems
Quick Facts
| particular | details | |||
|---|---|---|---|---|
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Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 40,000 (Inclusive of GST)
The fees for the course Introduction to Camera Systems is -
| Head | Amount |
| Programme fees | Rs. 40,000 |
certificate availability
Yes
certificate providing authority
Skill Lync
The syllabus
Week 1: Camera Construction
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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