Summary of Color
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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 light, wavelength, spectrums, light sources, reflection, reflectance functions, cone cells, tristimulus and chromaticity space.
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As the illumination level changes so do the red, green and blue tristimulus values, but they are linearly related. We can separate brightness from chromaticity which is a two dimensional representation of color. We discuss briefly the effect of gamma encoding on the color reproduction process.
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We use MATLAB and some Toolbox functions to find tomatoes on a bush. We convert the color image to chromaticity coordinates, select the pixels that belong to the tomatoes and the perform blob analysis to find the location of the tomatoes.
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Let’s recap the basics of homogeneous coordinates to represent points on a plane.
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We discuss the structure of a right-handed 3D coordinate frame and the spatial relationship between its axes which is encoded in the right-hand rule.
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We can describe the relationship between a 3D world point and a 2D image plane point, both expressed in homogeneous coordinates, using a linear transformation – a 3×4 matrix. Then we can extend this to account for an image plane which is a regular grid of discrete pixels.
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Let’s recap the important points from the topics we have covered about homogeneous coordinates, image formation, camera modeling and planar homographies.
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For an image stored as a variable in the MATLAB workspace let’s look at how we access the values of individual pixels in an image using their row and column coordinates. Using the MATLAB colon operator we can extract an intensity profile, extract a submatrix which is a region of the image, flip the image […]
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If we want to process images the first thing we need to do is to read an image into MATLAB as a variable in the workspace. What kind of variable is an image? How can we see the image inside a variable? How do we refer to to individual pixels within an image.
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As we did for the simple planar robots we can invert the Jacobian and perform resolved-rate motion control.