Description
Chapter 1: Introduction to Single Board Computers and RPi Chapter Goal: Brief intro into SBCs and RPi No of pages Sub -Topics 1. SBCs 2. Raspberry Pi 3. Raspberry Pi Imager and setup 4. Configuring the Pi Chapter 2: Introduction to Python and Digital Image Processing Chapter Goal: Brief acquaintance with the subject of the book No of pages: Sub – Topics: 1. History of Python 2. Features 3. Installation of Python on Raspberry Pi 4. IDEs for Python 5. Digital Image Processing Chapter 3: Getting Started with Image Processing Chapter Goal: Getting to understand the basics No of pages: Sub – Topics: 1. Image Sources (Standard Image Datasets) 2. Various Cameras for RPi 3. Pillow Basics 4. Tk Basics 5. Reading and displaying images with Pillow and Tk 6. Image Properties Chapter 4: Basic Operations on Images Chapter Goal: Getting to know Pillow No of pages: Sub – Topics: 1. Image module a) Image channels b) Mode Conversion c) Blending d) Resizing e) Rotation f) Crop and paste g) Alpha composition h) Mandelbrot set i) Noise and gradient 2. ImageChops module 3. ImageOps module Chapter 5: Advanced Operations on Images Chapter Goal: Filtering and Enhancements 1. Image filter (will cover more filters in the second edition) 2. Image enhancements (will cover additional effects) 3. Color quantization 4. Histogram and equalization Chapter 6: Scientific Python Chapter Goal: Introduction to the Scientific Python 1. The SciPy stack 2. NumPy, SciPy, and Matplotlib 3. Image Processing with NumPy and Matplotlib Chapter 7: Transformations, Interpolation, and Measurements Chapter Goal: Transformations and Measurements 1. Transformations and Interpolations a) Affine_transform b) Geometric_transform c) Map_coordinates d) Rotate e) Shift f) Spline_filter g) Spline_filter1d h) Zoom 2. Measurements a) Center_of_mass b) Extrema c) Find_objects d) Histogram e) Label f) Labeled_comprehension g) Maximum h) Maximum_position i) Mean j) Median k) Minimum l) Minimum_position m) Standard_deviation n) Sum_labels o) Variance p) Watershed_ift Chapter 8: Filters and their Application Chapter Goal: Study Various types of filters 1. Kernels, Convolution, Filters 2. Correlation 3. Low Pass Filters a) Blurring Filter (Gaussian, Gaussian 1D, uniform, uniform 1D, percentile, rank) b) Noise Removal (Gaussian, Median, Maximum, Minimum, rank) 4. High Pass filters a) Prewitt b) Sobel c) Laplacian d) Gaussian Gradient Magnitude e) Gaussian Laplace 5. Fourier Filters Chapter 9: Morphology, Thresholding, and Segmentation Chapter Goal: Study operations 1. Morphology a) Distance transform b) Structuring Element (generate_binary_structure) c) Binary Morphological Operations d) Greyscale Morphological Operations e) More Morphological Operations 2. Thresholding and Segmentation Chapter 10: pgmagik Chapter Goal: Learn pgmagic library in detail 1. Installation 2. Creating images 3. Draw text 4. Image filter and transformation 5. Bezier curve 6. Blob 7. Circle 8. Animation
