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In image processing, it is often necessary to find edges of shapes. Images are, by nature, complex maps of pixels, and thus can be very difficult for a computer to interpret and reduce into simple information. The Laplace operator is a tool used to solve some of these problems. | In image processing, it is often necessary to find edges of shapes. Images are, by nature, complex maps of pixels, and thus can be very difficult for a computer to interpret and reduce into simple information. The Laplace operator is a tool used to solve some of these problems. | ||
| − | Consider, for example, a self-driving car. This vehicle must be able to interpret | + | Consider, for example, a self-driving car. This vehicle must be able to interpret from an image what another object is, such as a car, stop sign, or pedestrian. Thus, edge detection is an important aspect of image processing. The Laplace operator is the perfect tool for this. |
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[[Walther_MA271_Fall2020_topic9|Back to main page]] | [[Walther_MA271_Fall2020_topic9|Back to main page]] | ||
Revision as of 21:30, 6 December 2020
Applications: Image Processing
In image processing, it is often necessary to find edges of shapes. Images are, by nature, complex maps of pixels, and thus can be very difficult for a computer to interpret and reduce into simple information. The Laplace operator is a tool used to solve some of these problems.
Consider, for example, a self-driving car. This vehicle must be able to interpret from an image what another object is, such as a car, stop sign, or pedestrian. Thus, edge detection is an important aspect of image processing. The Laplace operator is the perfect tool for this.
