Computer vision is the field of computer science that deals with enabling machines to interpret, process and analyze images or video data. The process of computer vision involves a combination of hardware and software components that work together to extract information from digital images or video streams.
1. Image acquisition: The first step in computer vision is to acquire a digital image or video stream using a camera or other imaging device.
2. Pre-processing: This step involves filtering the image or video stream to remove any unwanted noise, enhance the image quality, and ensure that the image is suitable for analysis.
3. Feature extraction: The next step involves extracting meaningful features from the image, such as contours, edges, colors, and textures. These features are then used to identify patterns and objects in the image.
4. Object recognition: Object recognition involves identifying and labeling objects in the image or video stream. This is usually done using machine learning algorithms that have been trained on large datasets of images.
5. Understanding and interpretation: Once the objects in an image have been recognized, the next step is to understand and interpret the scene. This involves analyzing the spatial relationships between objects, identifying the context in which the scene is taking place, and making inferences based on previous knowledge and experience.
6. Output and decision making: Finally, the output of the computer vision system is used to make decisions and take actions. For example, a computer vision system might be used to identify defects in a manufacturing process or to guide a self-driving car through traffic.
How computer vision work
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