Digital Image Processing and Analysis: Two Volume Set

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: Mixed media product
Length: 928 pages
Publication date: 18 January 2023
Publisher: Taylor & Francis Ltd

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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 optimization techniques, such as gradient descent and backpropagation, and designing efficient data structures. You should also be able to experiment with different algorithms and evaluate their performance using metrics such as accuracy, precision, and recall.

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, making it easier for you to implement image analysis algorithms and develop your own algorithms.

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 using software tools provided, you can leverage the power of computer vision to create innovative solutions for various industries. Whether you are a beginner or an experienced developer, there is always room to grow and improve your skills in this field.

Weight: 1950g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032071282
Edition number: 4 ed