Digital Image Processing and Analysis: Computer Vision and Image Analysis

This course will teach you how to develop computer vision application algorithms using software tools. It will also cover the underlying processes needed for image analysis and provide you with concepts to develop your own algorithms. The course includes software tools for analysis and development.

Format: Hardback
Length: 420 pages
Publication date: 18 January 2023
Publisher: Taylor & Francis Ltd

Computer vision is a rapidly growing field that has the potential to revolutionize various industries, from healthcare to transportation. Developing computer vision application algorithms is crucial for leveraging this technology's full potential. In this article, we will explore the steps you can take to learn how to develop computer vision application algorithms.

Understanding the Basics:

Before diving into the intricacies of computer vision, it is essential to have a solid understanding of the underlying principles and concepts. This includes understanding image processing, computer graphics, and machine learning. You should also be familiar with popular programming languages such as Python, C++, and Java, as they are commonly used in computer vision.

Choosing the Right Tools:

There are numerous software tools available for analysis and development in computer vision. Some of the most popular ones include OpenCV, TensorFlow, and PyTorch. Each tool has its strengths and weaknesses, and choosing the right one depends on your specific needs and preferences.

Implementing Image Analysis:

Once you have chosen the right software tools, you need to implement image analysis algorithms. This involves processing images to extract features such as edges, corners, and shapes. You can also use machine learning algorithms to classify images and perform tasks such as object detection and recognition.

Developing Your Own Algorithms:

To develop your own computer vision application algorithms, you need to have a good understanding of the underlying principles and concepts. This includes understanding image processing, computer graphics, and machine learning. You should also be familiar with popular programming languages such as Python, C++, and Java, as they are commonly used in computer vision.

Software Tools Provided:

Several software tools are provided to help you develop computer vision application algorithms. Some of the most popular ones include OpenCV, TensorFlow, and PyTorch. These tools offer a wide range of features and functionalities that can help you build powerful and efficient computer vision applications.

In conclusion, developing computer vision application algorithms is a challenging but rewarding task. By understanding the basics, choosing the right tools, implementing image analysis algorithms, developing your own algorithms, and utilizing software tools provided, you can build powerful and efficient computer vision applications that can revolutionize various industries.

Weight: 1574g
Dimension: 221 x 286 x 30 (mm)
ISBN-13: 9781032071299
Edition number: 4 ed