DIP+CV · Programming Exercises (EPs)

CHAPTER 01

• EP01_01 — 📏 Three distance metrics in DIP
• EP01_02 — 📊 Predictive Performance — ML Metrics in CV
• EP01_03 — 📈 Mean Average Precision (mAP) — Precision-Recall Curve
• EP01_04 — 🖼️ Reading and Information from a Matrix Image
• EP01_05 — 🔄 Negative of a Grayscale Image
• EP01_06 — 🎨 RGB → Grayscale Conversion (ITU-R BT.601)
• EP01_07 — ⚫ Manual Thresholding: Binary Image
• EP01_08 — 🎨 Intensity Range Remapping
• EP01_09 — 🏁 Checkerboard Pattern: Chess Matrix
• EP01_10 — 📄 Metadata: Reading a PGM File
• EP01_11 — 📈 Neighborhood Analysis: 1D Maximum Filter

CHAPTER 02

• EP02_01 — ☀️ Brightness and Contrast Adjustment
• EP02_02 — 🔬 Spatial Subsampling
• EP02_03 — 🎨 Gray Level Quantization
• EP02_04 — 📐 Distance Transform in Binary Images
• EP02_05 — ➡️ Image Translation
• EP02_06 — 🔄 Image Rotation
• EP02_07 — 🔍 Resizing (Scaling)
• EP02_08 — 🔀 Shear Transformation
• EP02_09 — 🧩 Generic Affine Transformation
• EP02_10 — 🎯 Perspective Correction (Homography)
• EP02_11 — 🏆 Perspective Correction (Homography) in a Real Image

CHAPTER 03

• EP03_01 — ➕ Saturated Addition of a Constant
• EP03_02 — 🔀 Alpha Blending of Two Images
• EP03_03 — 🎭 Image Inversion (Photographic Negative)
• EP03_04 — 📊 Histogram Equalization (L bits)
• EP03_05 — 🔲 Binary AND Mask Application
• EP03_06 — 🌫️ N×N Mean Filter Kernel
• EP03_07 — 🔍 Laplacian Operator (w4) for Edge Enhancement
• EP03_08 — 🧭 Sobel Gradient: Gx and Gy
• EP03_09 — 📡 3×3 Median Filter
• EP03_10 — ✨ Unsharp Masking (USM)

CHAPTER 04

• EP04_01 — 🎚️ Global Thresholding with a Fixed Threshold
• EP04_02 — 📊 Otsu’s Automatic Thresholding
• EP04_03 — 🌱 Flat Binary Dilation (mm.dil0)
• EP04_04 — 🪨 Binary Erosion by Flat Structuring Element (mm.ero0)
• EP04_05 — 🧹 Morphological Opening (Noise Removal)
• EP04_06 — 🧩 Morphological Closing (Filling of Gaps)
• EP04_07 — ⛰️ Weighted Dilation and Erosion (mm.dil1 / mm.ero1)
• EP04_08 — 🌋 Morphological Gradient, Top-hat, and Black-hat
• EP04_09 — 🗺️ Distance Transform and the Object’s “Core”
• EP04_10 — 🪙 Blob Separation, Labeling, and Descriptors

CHAPTER 05

• EP05_01 — 🟢 Ideal Low-Pass Filter by Distance in the Spectrum
• EP05_02 — 🟡 Notch Filter: Removing Periodic Peaks
• EP05_03 — 🟠 DCT Quantization: The True Source of Compression
• EP05_04 — 🔴 Implementing the 2D DFT from the Definition
• EP05_05 — 🏆 Complete JPEG Pipeline: DCT, Quantization, and Reconstruction

CHAPTER 06

• EP06_01 — 🟢 Segmentation Evaluation by IoU ( Intersection over Union )
• EP06_02 — 🟢 Marker Filtering by Circularity
• EP06_03 — 🟡 Classification of Markings on Answer Sheets (OMR)
• EP06_04 — 🟡 Median Angular Slope Estimator ( Deskew )
• EP06_05 — 🟠 Background Normalization by Division (Illumination Correction)
• EP06_06 — 🔴 Local Variance Map for Texture Detection
• EP06_07 — 🟣 Industrial Inspection Pipeline: Registration by Translation and Subtraction
• EP06_08 — ⚫ QRCode Segmentation and Real Decoding with OpenCV

CHAPTER 07

• EP07_01 — 🟢 Step-by-Step k-NN Classifier
• EP07_02 — 🟡 Z-score Normalization and Robustness of k-NN to Distinct Scales
• EP07_03 — 🟡 Evaluation via Confusion Matrix
• EP07_04 — 🟠 Manual Encoding of the LBP Descriptor
• EP07_05 — 🔴 Histogram of Orientations for an HOG Cell
• EP07_06 — 🟣 Complete Pipeline : Descriptors + k-NN + Multi-Class Evaluation
• EP07_07 — ⚫ Real Classification of a Texture Mosaic via LBP + k-NN

CHAPTER 08

• EP08_01 — 🟢 Hamming Distance and Binary Descriptor Matching
• EP08_02 — 🟢 Homography and RANSAC: Voting by Inliers
• EP08_03 — 🟢 Integral Image: Rectangular Sums in Constant Time
• EP08_04 — 🟢 IoU and Non-Maximum Suppression (NMS)
• EP08_05 — 🟡 Connected Component Labeling: Instance Segmentation
• EP08_06 — 🟡 Bounding Boxes , Centroids, and Instance Properties with mm.measure
• EP08_07 — 🟡 Salt-and-Pepper Noise Removal and Object Measurement
• EP08_08 — 🟡 Grayscale Image and Dynamic Thresholding
• EP08_09 — 🟠 Illumination Gradient and Adaptive Thresholding
• EP08_10 — 🔴 Low Contrast and Object Separation Topics ( Watershed / Distance)
• EP08_11 — 🔴 Classification and Validation of Objects with Bounding Box Ground Truth
• EP08_12 — 🔴 Instance Segmentation on Real Images: Geometric Objects

CHAPTER 09

• EP09_01 — 🟢 Manual 2D Convolution (Forward Pass of a Learned Layer)
• EP09_02 — 🟢 Manual Pooling (Maximum and Average)
• EP09_03 — 🟡 Counting Trainable Parameters of a CNN
• EP09_04 — 🟡 Intersection over Union (IoU) and Non-Maximum Suppression (NMS)
• EP09_05 — 🟠 Segmentation Evaluation: Pixel-wise IoU and Dice
• EP09_06 — 🔴 Integrated Pipeline: From Detection to Real-World Measurement