Digital Image Processing Lab (CS-325)
Course Type: Core
Batch: 3rd Year CSE, B.Tech and Dual Degree
Course Credits: 01
Course Objectives
- Describe and explain basic principles of digital image processing.
- Design and implement algorithms that perform basic image processing (e.g., noise removal and image enhancement).
- Design and implement algorithms for advanced image analysis (e.g., image compression, image segmentation).
- Assess the performance of image processing algorithms and systems.
Pre-requisites
There are no official pre-requisites for this course.
Venue
Programming Laboratory 4, Department of Computer Science and Engineering
Time Slot
Thrusday: 02:00 PM - 04:00 PM
Friday: 02:00 PM - 04:00 PM
List of Experiments
- Implement the spatial image enhancement functions on a bitmap image – Mirroring (Inversion).
- Implement the spatial image enhancement functions on a bitmap image – Rotation (Clockwise).
- Implement the spatial image enhancement functions on a bitmap image – Enlargement (Double Size).
- Implement a) Low Pass Filter and b) High Pass Filter.
- Implement a) Arithmetic Mean Filter and b) Geometric Mean Filter.
- Implement Smoothing and Sharpening of an eight-bit color image.
- Implement a) Boundary Extraction Algorithm and b) Graham's Scan Algorithm.
- Implement a) Edge Detection and b) Line Detection.
- Implement Image Segmentation using the Otsu and Thresholding methods.
- Implement data compression using the JPEG algorithm.
Course Outcomes
Upon successful completion of the course, the students will be able to:
- CO1: Analyze general terminology of digital image processing.
- CO2: Examine various types of images, intensity transformations, and spatial filtering.
- CO3: Develop Fourier transform for image processing in the frequency domain.
- CO4: Implement image processing and analysis algorithms.
- CO5: Apply image processing algorithms in practical applications.