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What Is a Vision System? > Extracting Features and Information
Extracting Features and Information
Once the image is filtered by removing some of the noise and narrowing the field to just the region of interest, the next step is to extract the relevant features. It is up to the programmer to translate those features into more applicable information. In the car example, it is not possible to tell the system to look for a car. Instead, the algorithm looks for car-like features, such as a rectangular license plate, or rough parameters on size, shape, and color. Then the program assumes that something matching those features must be a car.
Some commonly used features covered in this book include:
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Color information: looking for changes in color to detect objects.
