Programming Computer Vision with Python PDF free download

Details about Programming Computer Vision with Python

261 Pages – 2012 – 68.8 MB – 4535 Downloads – English

Programming Computer Vision with Python PDF

Programming Computer Vision with Python PDF free download – What You Will Learn

  • Hands-on programming with images using Python.
  • Computer vision techniques behind a wide variety of real-world applications.
  • Many of the fundamental algorithms and how to implement and apply them yourself.

The code examples in this book will show you object recognition, content-based image retrieval, image search, optical character recognition, optical flow, tracking, 3D reconstruction, stereo imaging, augmented reality, pose estimation, panorama creation, image segmentation, de-noising, image grouping, and more.

Chapter 1, “Basic Image Handling and Processing”

Introduces the basic tools for working with images and the central Python modules used in the book. This chapter also covers many fundamental examples needed for the remaining chapters.

Chapter 2, “Local Image Descriptors”

Explains methods for detecting interest points in images and how to use them to find corresponding points and regions between images.

Chapter 3, “Image to Image Mappings”

Describes basic transformations between images and methods for computing them. Examples range from image warping to creating panoramas.

Chapter 4, “Camera Models and Augmented Reality”

Introduces how to model cameras, generate image projections from 3D space to image features, and estimate the camera viewpoint.

Chapter 5, “Multiple View Geometry”

Explains how to work with several images of the same scene, the fundamentals of multiple-view geometry, and how to compute 3D reconstructions from images.

Chapter 6, “Clustering Images”

Introduces a number of clustering methods and shows how to use them for grouping and organizing images based on similarity or content.

Chapter 7, “Searching Images”

Shows how to build efficient image retrieval techniques that can store image representations and search for images based on their visual content.

Chapter 8, “Classifying Image Content”

Describes algorithms for classifying image content and how to use them to recognize objects in images.

Chapter 9, “Image Segmentation”

Introduces different techniques for dividing an image into meaningful regions using clustering, user interactions, or image models.

Chapter 10, “OpenCV”

Shows how to use the Python interface for the commonly used OpenCV computer vision library and how to work with video and camera input.

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