MOOC - Computer Vision Expert
Computer Vision Fundamentals
The second unit of this job role provides insights on the underlying principles of computer vision as well as its main characteristics.
Image Processing and Manipulation:
This learning element focus on the different aspects of image processing and manipulation, addressing important practices like image interpolation, aliasing, image enhancement, singular value decomposition, singular value equalization, filtering and many other.
CVE.U2.E4.PC1
The student is able to understand and distinguish the different types of image processing methods, namely, analogue and digital image processing.
CVE.U2.E4.PC2
The student comprehends what sampling, quantization, and image interpolation are.
CVE.U2.E4.PC3
The student understands the differences between image resize and remapping.
CVE.U2.E4.PC4
The student understands what aliasing is and is able to distinguish between spatial aliasing and anti-aliasing.
CVE.U2.E4.PC5
The student understands and defines spatial domain methods and frequency domain methods.
CVE.U2.E4.PC6
The student knows important concepts for image enhancement in spatial domain like point processing and mask processing.
CVE.U2.E4.PC7
The student understands what contrast stretching is.
CVE.U2.E4.PC8
The student knows some commonly used transformation functions used in contrast enhancement.
CVE.U2.E4.PC9
The student understands what histogram and histogram processing is and knows how histogram equalization works.
CVE.U2.E4.PC10
The student understands how Singular Value Decomposition (SVD) and Singular Value Equalization (SVE) works.
CVE.U2.E4.PC11
The student knows arithmetic and logic operations and understands their differences.
CVE.U2.E4.PC12
The student understands image subtraction and image averaging process.
CVE.U2.E4.PC13
The student understands the differences between linear and nonlinear spatial filtering.
CVE.U2.E4.PC14
The student is able to define and differentiate convolution and correlation.
CVE.U2.E4.PC15
The student understands the differences between linear and nonlinear smoothing filters as well as statistical filters.
CVE.U2.E4.PC16
The student is able to define and understand Laplacian, gradient and sobel operator.