Course

PROFESSIONAL ELECTIVES

Electives Electives in Computer Vision

Unit I

Digital Image Fundamentals: Image Acquisition-Image Sampling and Quantization – Intensity Transformations – Histogram Processing – Spatial Filtering for enhancement and restoration. Filtering in Frequency Domain for enhancement and restoration.

Unit II

Image Segmentation: Edge Detection – Thresholding- Region Based Segmentation, quadtree, Image pyramids, Color image processing. Case study in Deep learning based segmentation: U-Net, Mask-RCNN

Unit III

Image Description- shape and texture descriptors. Morphological Image Processing: Erosion – Dilation – Opening – Closing – Hit-or-Miss Transform. Case Studies from real world applications.

Course Objectives

• This course introduces basics of binary, gray scale and color image processing.
• This course concentrates on digital image processing techniques in spatial and frequency domain which are relevant to image enhancement, restoration and segmentation applications.
• This course introduces representation and description of digital images.

Course Outcomes

CO1: Understand fundamental principles of image processing and perform basic operations on pixels.

CO2: Apply the image processing algorithms and filters in spatial domain for image enhancement and restoration.

CO3: Analyze images in the frequency domain and explore the frequency domain filters for image enhancement and

restoration.

CO4: Apply segmentation algorithms on Images and analyze their performance for real world applications.

CO5: Apply appropriate representation and perform morphological processing on images.

CO-PO Mapping

Evaluation Pattern: 70:30

*CAT – Can be Quizzes, Assignments, and Reports

*CAL – Can be Lab Assessments, Project, and Report

**End Semester can be theory examination/ lab-based examination/ project presentation

Textbook(s)

Gonzalez RC, Woods RE. “Digital Image Processing”. Fourth edition;2017.

Reference(s)

 Pratt W K. “Digital Image Processing”, Fourth Edition, John Wiley & Sons;2007.

Castleman K R. “Digital Image Processing”, Prentice Hall;1996.

Sandipan Dey, “Hands-On Image Processing with Python Expert Techniques for Advanced Image Analysis and Effective Interpretation of Image Data”, Packt Publishing, 2018 .

Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins. “Digital Image Processing Using MATLAB®”. Prentice Hall; 2004.

Russ JC, Russ JC. “Introduction to Image Processing and Analysis”. CRC press; 2007.