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    Introduction to Camera Systems

    BY
    Skill Lync

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    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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