Introduction to Computer Vision
Computer Vision is concerned with the understanding and interpretation of images and video. In order to effectively achieve this, a solid understanding of how images are formed and how they can be manipulated is required. In this lesson, we will explore how images are formed and how they can be processed by computers.
Images can be formed in a variety of ways, but for the purposes of computer vision, we will focus on digital images. A digital image is formed by sampling a continuous image at regular intervals, and then representing each sample as a digital value. Each sample is known as a pixel, and the digital value represents the intensity of the pixel. The number of pixels in an image is determined by its resolution, which is typically measured in pixels per inch (PPI) or dots per inch (DPI).
Once an image has been captured, it can be processed by computers to enhance or modify it. Some common image processing techniques include:
Filtering: Filtering is the process of altering the pixel values in an image to achieve a desired effect. For example, a blur filter can be applied to an image to make it appear softer or more out of focus.
Enhancement: Enhancement techniques are used to improve the quality of an image. For example, an image can be enhanced by increasing its contrast or adjusting its brightness.
Feature Extraction: Feature extraction involves identifying specific features in an image, such as edges or corners, and extracting them as separate entities. These features can then be used for further analysis or processing.
In this lesson, we have explored how images are formed and how they can be processed by computers. A solid understanding of these concepts is essential for anyone working in the field of computer vision.
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