CMSC 178IP

Digital Image Processing

Fundamentals of digital image processing and computer vision

Course Overview
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Course Syllabus
Schedule, grading, policies & resources
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Fundamentals 3 modules
1
Introduction to Digital Image Processing
Module 1
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2
Storage and Compression
Module 2
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3
Image Processing Fundamentals
Module 3
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Image Enhancement 2 modules
4
Image Enhancement and Filtering
Module 4
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5
Image Restoration
Module 5
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Transformations & Features 2 modules
6
Geometric Transformations
Module 6
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7
Feature Extraction
Module 7
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Segmentation 1 modules
8
Segmentation and Morphology
Module 8
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Deep Learning 3 modules
9
Computer Vision & Deep Learning I
Module 9
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10
Computer Vision & Deep Learning II
Module 10
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11
Generative Models
Module 11
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📋
DIP Research Project — Up to 5 members per group · 2nd Sem 2025-2026
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CMSC 178IP - Finals Examination

Take-Home Practical Exam in Jupyter Notebook

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Total Points

100 points (+ 10 bonus)

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Recommended Time

3-4 hours (self-paced)

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Deadline

1 week from release

Exam Structure

Part 1 Image Fundamentals 20 pts
Part 2 Processing & Filtering 20 pts
Part 3 Features & Segmentation 20 pts
Part 4 Deep Learning (CNN) 20 pts
Part 5 Generative Models 20 pts
Bonus PCB Defect Detection Pipeline +10 pts

Instructions

  • Download the Jupyter Notebook and open in Google Colab or your local Jupyter environment
  • Complete all code cells marked with # TODO
  • Answer all analysis questions in your own words
  • LLM usage is permitted for coding help, but reflections must be your own understanding
  • Export as PDF and submit both .ipynb and .pdf files
📥 Download Notebook

Download the Jupyter Notebook to complete in Google Colab or your local environment.

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Access Exam Notebook

Choose how you want to access the exam notebook. Open in Colab to run code interactively, view on GitHub, or download directly.

Recommended: Open in Colab, then save a copy to your Drive.