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Programming Computer Vision with Python by Jan Erik Solem


Download This PDF Book : Programming Computer Vision with Python: Tools and algorithms for analyzing images 1st Edition by Jan Erik Solem.

Today, images and video are everywhere. Online photo-sharing sites and social networks have them in the billions. Search engines will produce images of just about any conceivable query. 

Practically all phones and computers come with built-in cameras. It is not uncommon for people to have many gigabytes of photos and videos on their devices. 

Programming a computer and designing algorithms for understanding what is in these images is the field of computer vision. Computer vision powers applications like image search, robot navigation, medical image analysis, photo management, and many more. 

The idea behind this book is to give an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers, and enthusiasts. 

The Python programming language, the language choice of this book, comes with many freely available, powerful modules for handling images, mathematical computing, and data mining. When writing this book, I have used the following principles as a guideline. The book should: 

Be written in an exploratory style and encourage readers to follow the examples on their computers as they are reading the text. 

Promote and use free and open software with a low learning threshold. Python was the obvious choice. 

Be complete and self-contained. This book does not cover all of computer vision but rather it should be complete in that all code is presented and explained. The reader should be able to reproduce the examples and build upon them directly. 

Be broad rather than detailed, inspiring and motivational rather than theoretical. In short, it should act as a source of inspiration for those interested in programming computer vision applications.

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. 

You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.

Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. 

This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.

Learn techniques used in robot navigation, medical image analysis, and other computer vision applications

Work with image mappings and transforms, such as texture warping and panorama creation

Compute 3D reconstructions from several images of the same scene

Organize images based on similarity or content, using clustering methods

Build efficient image retrieval techniques to search for images based on visual content

Use algorithms to classify image content and recognize objects

Access the popular OpenCV library through a Python interface

Table of Contents:

1. Basic Image Handling and Processing

2. Local Image Descriptors 

3. Image to Image Mappings

4. Camera Models and Augmented Reality

5. Multiple View Geometry

6. Clustering Images.

7. Searching Images

8. Classifying Image Content 

9. Image Segmentation

10. OpenCV

A. Installing Packages  

B. Image Datasets 

C. Image Credits 

About the Author

Jan Erik Solem is a Python enthusiast and a computer vision researcher and entrepreneur. He is an applied mathematician and has worked as associate professor, startup CTO, and now also book author. 

He sometimes writes about computer vision and Python on his blog janeriksolem net He has used Python for computer vision in teaching, research and industrial applications for many years. He currently lives in San Francisco.

About The Book:

Publisher ‏ : ‎ O'Reilly Media; 1st edition (July 10, 2012)

Language ‏ : ‎ English

Pages ‏ : ‎ 264 

File: PDF, 60 MB


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