Description
Book SynopsisUnderstand the concepts of image processing with Python 3 and create applications using Raspberry Pi 4. This book covers image processing with the latest release of Python 3, using Raspberry Pi OS and Raspberry Pi 4B with the 8 GB RAM model as the preferred computing platform.
This second edition begins with the installation of Raspberry Pi OS on the latest model of Raspberry Pi and then introduces Python programming language, IDEs for Python, and digital image processing. It also illustrates the theoretical foundations of Image processing followed by advanced operations in image processing. You''ll then review image processing with NumPy, and Matplotlib followed by transformations, interpolation, and measurements of images.
Different types of filters such as Kernels convolution filters, low pass filters, high pass filters, and Fourier filters are discussed in a clear, methodical manner. Additionally, the book examines variou
Table of Contents
Chapter 1: Introduction to Single Board Computers and RPiChapter Goal: Brief intro into SBCs and RPiNo of pages Sub -Topics1. SBCs2. Raspberry Pi3. Raspberry Pi Imager and setup4. Configuring the Pi
Chapter 2: Introduction to Python and Digital Image ProcessingChapter Goal: Brief acquaintance with the subject of the bookNo of pages:Sub - Topics: 1. History of Python2. Features3. Installation of Python on Raspberry Pi4. IDEs for Python5. Digital Image Processing
Chapter 3: Getting Started with Image ProcessingChapter Goal: Getting to understand the basicsNo of pages:Sub - Topics: 1. Image Sources (Standard Image Datasets)2. Various Cameras for RPi3. Pillow Basics4. Tk Basics5. Reading and displaying images with Pillow and Tk6. Image Properties
Chapter 4: Basic Operations on ImagesChapter Goal: Getting to know PillowNo of pages:Sub - Topics: 1. Image modulea) Image channelsb) Mode Conversionc) Blendingd) Resizinge) Rotationf) Crop and pasteg) Alpha compositionh) Mandelbrot seti) Noise and gradient2. ImageChops module3. ImageOps module
Chapter 5: Advanced Operations on ImagesChapter Goal: Filtering and Enhancements 1. Image filter (will cover more filters in the second edition)2. Image enhancements (will cover additional effects)3. Color quantization4. Histogram and equalization
Chapter 6: Scientific Python
Chapter Goal: Introduction to the Scientific Python1. The SciPy stack2. NumPy, SciPy, and Matplotlib3. Image Processing with NumPy and Matplotlib
Chapter 7: Transformations, Interpolation, and Measurements Chapter Goal: Transformations and Measurements1. Transformations and Interpolationsa) Affine_transformb) Geometric_transformc) Map_coordinatesd) Rotatee) Shiftf) Spline_filterg) Spline_filter1dh) Zoom2. Measurementsa) Center_of_massb) Extremac) Find_objectsd) Histograme) Labelf) Labeled_comprehensiong) Maximumh) Maximum_positioni) Meanj) Mediank) Minimuml) Minimum_positionm) Standard_deviationn) Sum_labelso) Variancep) Watershed_ift
Chapter 8: Filters and their ApplicationChapter Goal: Study Various types of filters1. Kernels, Convolution, Filters 2. Correlation3. Low Pass Filtersa) Blurring Filter (Gaussian, Gaussian 1D, uniform, uniform 1D, percentile, rank)b) Noise Removal (Gaussian, Median, Maximum, Minimum, rank)4. High Pass filtersa) Prewittb) Sobelc) Laplaciand) Gaussian Gradient Magnitudee) Gaussian Laplace5. Fourier Filters
Chapter 9: Morphology, Thresholding, and SegmentationChapter Goal: Study operations1. Morphologya) Distance transformb) Structuring Element (generate_binary_structure)c) Binary Morphological Operationsd) Greyscale Morphological Operations
e) More Morphological Operations2. Thresholding and Segmentation
Chapter 10: pgmagikChapter Goal: Learn pgmagic library in detail1. Installation2. Creating images3. Draw text4. Image filter and transformation5. Bezier curve6. Blob7. Circle8. Animation
