Computer vision handbook

Across three volumes, this handbook presents comprehensive coverage of all aspects of computer vision from image formation to scene understanding.
Volume 2 (From Image to Pattern) examines image transforms, image restoration, image segmentation, and points of interest.

Therefore, it includes ,an introduction to Python and the OpenCV library to perform Computer Vision tasks on images and videos.
Furthermore, the course covers numerical processing and image manipulation using the NumPy library before moving to image processing with OpenCV.

Computer vision aims to mimic the human visual system.
The objective is to build artificial systems which can extract information from images, i.e., objective is to make computers understand images and videos.
The image data may be a video sequence, depth images, views from multiple cameras, or multi-dimensional data from image sensors.

The book includes ,programming exercises and questionnaires at the end of each chapter.
From mathematical concepts to image recognition, image segmentation, and the basic components of a Computer Vision system, the book covers a wide range of related CV topics.
Why should you read it.
This is a great, easy-to-read guide on a difficult subject.