#### Summary of Image Formation

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Let’s recap the important points from the topics we have covered about image formation and perspective projection.

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Let’s recap the important points from the topics we have covered about image formation and perspective projection.

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Let’s recap the important points from the topics we have covered about light, wavelength, spectrums, light sources, reflection, reflectance functions, cone cells, tristimulus and chromaticity space.

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Let’s recap the important points from the topics we have covered about image features, blobs, connectivity analysis, and blob parameters such as centroid position, area, bounding box, moments, equivalent ellipse, and perimeter.

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Let’s recap the important points about spatial operators. Linear operators can be used to smooth images and determine gradients. Template matching can be used to find a face in a crowd. Non-linear operators such as rank filters can be used for noise removal, and mathematical morphology treats shapes according to their compatibility with a structuring […]

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Let’s recall the key techniques we’ve covered including monadic and dyadic image processing operations and efficient ways to write these in MATLAB using vectorization.

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Let’s recap some of the most important topics we’ve covered about treating an image as a matrix within MATLAB which we can display or index into.

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Vision is useful to us and to almost all forms of life on the planet, perhaps robots could do more if they could also see. Robots could mimic human stereo vision or use cameras with superhuman capability such as wide angle or panoramic views.

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We recap the important points from this masterclass.

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We recap the important points from this masterclass.

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We revisit the important points from this masterclass.