Image and Video processing (DE) (L-T-P-C: 3–0–2-4)
Pre-requisites: Design and Analysis of Algorithms. Fundamentals of Discrete Mathematics, Fourier Transform, Probability and Statistics is desired.
- Introduction and applications of image and video processing. Fundamentals of Digital Image and Video; acquisition, sampling and quantization. Representation of digital images as matrices, types of images (binary, grayscale, color, indexed).
- Basic topology: neighbors and neighborhoods, adjacency, connectivity, Regions and boundaries.
- Image enhancement: Intensity transformations and Spatial filtering, Histogram equalization, Averaging, Smoothing, Laplacian filters etc.
- Image restoration: Types of Noise and removal methods – Mean filter, Median, Min, Max, Midpoint, Adaptive filters etc.
- Basics of filtering in the frequency domain: The Fourier transform – basic definitions and examples. Steps for filtering in the frequency domain.
- Binary mathematical morphology: Erosion and Dilation, Opening and Closing, The Hit or Miss Transformations, extraction of connected components.
- Image and Video Segmentation – Edge Detection and enhancement, Thresholding, Edge based and Region based Segmentation techniques.
- Object detection in videos: Basics of background modeling and foreground detection, connected component labeling,
- Case study of applications like automated video surveillance.
- “Digital Image Processing” by R.C. Gonzalez and R.E. Woods, Pearson Education, 3rd ed.
- “Image Processing, Analysis, and Machine Vision”, M. Sonka, V. Hlavac, and R. Boyle. Cengage Learning, 2009.
- “Computer Vision: Algorithms and Applications” by Richard Szeliski, Springer, 2010.
- “Fundamentals of Digital image processing”, by Anil K. Jain, PHI, 2010
- Journal/Conference papers and Reference manuals of Image/Video processing tools.
Beyond the obvious applications in entertainment and scientific visualization, digital images and video have become a central component of net-centered computing, human/computer interfaces, and databases, as well as data analysis for domains such as biometrics, surveillance and remote sensing. This course offers fundamentals of digital image and video processing and algorithms for most of the work currently underway in this field. Through this course, students will get a clear impression of the breadth and practical scope of digital image and video processing and develop conceptual understanding which will enable them to undertake further study, research and/or implementation work in this area.
At the end of the course the students will be able to:
- Describe the fundamentals of image and video processing and their applications
- Develop familiarity and implement basic image and video processing algorithms.
- Select and apply appropriate technique to real problems in image and video analysis.