Raspberry Pi Image Processing Programming

Understand 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 various image processing techniques such as Morphology, Thresholding, and Segmentation, followed by a chapter on live webcam input with OpenCV, an image processing library with Python. The book concludes with an appendix covering a new library for image processing with Python, pgmagik, followed by a few important tips and tricks relevant to RPi.

WHAT YOU'LL LEARN

* Get started with Raspberry Pi and Python
* Understand Image Processing with Pillow
* See how image processing is processed using Numpy and Matplotlib
* Use Pi camera and webcam

WHO THIS BOOK IS FOR

Raspberry Pi and IoT enthusiasts, and Python and Open Source professionals

ASHWIN PAJANKAR earned a Master of Technology in Computer Science Engineering from IIIT Hyderabad and has over 25 years of programming experience. He started his journey in programming and electronics at the tender age of 7 with a MS-DOS computer and BASIC programming language. He is now proficient in Assembly programming, C, C++, Java, Shell Scripting, JavaScript, Go Programming, HTML, and Python. His other technical expertise includes single board computers such as Raspberry Pi and Banana Pro, and microcontroller boards (Arduino), and embedded boards (BBC Micro Bit). He has worked extensively on domains such as Software/Product Testing, Software Automation, Databases, Data Analytics, Computer Vision, and Web Development.

Ashwin is currently a freelance online instructor teaching programming and electronics to more than 8200 professionals. He also regularly conducts live programming boot camps for software professionals. His growing Youtube channel has an audience of more than 11000 subscribers. He has published more than 20 books on programming and electronics with many international publications, including Apress and regularly reviews books on programming written by other authors.

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 PillowNo 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) Mediank) 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. Morphologya) 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