Foreground-Background Segmentation and Foreground Region Area Calculation

In the second assignment of Professor Wenkai Lu's Digital Image Processing course, students are required to perform foreground-background segmentation and calculate the area of foreground regions. This assignment focuses on learning techniques to separate foreground objects from background elements in digital images and quantitatively measure foreground areas through computational methods. Key implementation aspects include: - Applying segmentation algorithms such as thresholding, edge detection, or region-based methods to distinguish foreground from background - Using connected component analysis to identify distinct foreground regions - Calculating pixel area counts for each segmented region using morphological operations - Implementing algorithms that handle various image types and lighting conditions The practical coding component involves: - Working with image processing libraries (such as OpenCV or MATLAB Image Processing Toolbox) - Developing functions for image binarization using optimal threshold selection methods - Implementing region labeling algorithms to identify connected foreground components - Creating area calculation routines that account for pixel dimensions and scaling factors Through this hands-on assignment, students gain deeper understanding of fundamental digital image processing concepts and techniques, while developing practical skills to solve real-world image analysis problems. The project enhances proficiency in algorithm implementation and strengthens comprehension of how computational methods can extract meaningful information from visual data.