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Canny Edge Detection

Module by: Richard Hall, Jared Flatow. E-mail the authors

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Summary: Introduction to Canny Edge Detection and its application to Seeing using Sound.

Introduction to Edge Detection

Edge detection is the process of finding sharp contrasts in intensities in an image. This process significantly reduces the amount of data in the image, while preserving the most important structural features of that image. Canny Edge Detection is considered to be the ideal edge detection algorithm for images that are corrupted with white noise. For a more in depth introduction, see the Canny Edge Detection Tutorial.

Canny Edge Detection and Seeing Using Sound

The Canny Edge Detector worked like a charm for Seeing Using Sound. We used a Matlab implementation of the Canny Edge Detector, which can be found at http://ai.stanford.edu/~mitul/cs223b/canny.m. Here is an example of the results of filtering an image with a Canny Edge Detector:

Figure 1: Before Edge Detection
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Figure 2: After Edge Detection
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Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

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Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

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Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

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