Please Enter ISBN, Title or Author’s Name
img
img
img
logo
logo
and more...

Hands-On Image Processing with Python: Expert techniques for advanced image analysis and effective interpretation of image data

img
Author: Sandipan Dey
ISBN:1789343739
ISBN-13: 9781789343731
List Price: $44.99 (up to 9% savings)
Prices shown are the lowest from
the top textbook retailers.

View all Prices by Retailer

Details about Hands-On Image Processing with Python: Expert techniques for advanced image analysis and effective interpretation of image data:

Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks.

Key Features

  • Practical coverage of every image processing task with popular Python libraries
  • Includes topics such as pseudo-coloring, noise smoothing, computing image descriptors
  • Covers popular machine learning and deep learning techniques for complex image processing tasks

Book Description

Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python.

The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing.

By the end of this book, we will have learned to implement various algorithms for efficient image processing.

What you will learn

  • Perform basic data pre-processing tasks such as image denoising and spatial filtering in Python
  • Implement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in Python
  • Do morphological image processing and segment images with different algorithms
  • Learn techniques to extract features from images and match images
  • Write Python code to implement supervised / unsupervised machine learning algorithms for image processing
  • Use deep learning models for image classification, segmentation, object detection and style transfer

Who this book is for

This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.

Table of Contents

  1. Getting started with Image Processing
  2. Sampling Fourier Transform
  3. Convolution and Frequency domain Filtering
  4. Image Enhancement
  5. Image Enhancement using Derivatives
  6. Morphological Image Processing
  7. Extracting Image Features and Descriptors
  8. Image Segmentation
  9. Classical Machine Learning Methods
  10. Learning in Image Processing - Image Classification with CNN
  11. Object Detection, Deep Segmentation and Transfer Learning
  12. Additional Problems in Image Processing

Need Computer Vision & Pattern Recognition tutors? Start your search below:
Need Computer Vision & Pattern Recognition course notes? Start your search below: