#### Spatial Operators – Handling Edge Pixels

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We run into problems when we take all of the pixels in a box around an input pixel and that pixel is close to one of the edges of the image. Let’s look at some strategies to deal with edge pixels.

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We run into problems when we take all of the pixels in a box around an input pixel and that pixel is close to one of the edges of the image. Let’s look at some strategies to deal with edge pixels.

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When we look at an image we discern objects, and these tend to be groups of similar pixels surrounded by a distinctive edge. We look at intensity profiles in images and use spatial operators with kernels such as the Sobel kernel to find the intensity gradients in an image, and from these find edges in […]

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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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MATLAB normally deals with matrices of floating point numbers. An image is typically represented by an array of small integer values, pixel value or greyscale values, which have a limited dynamic range and special rules for arithmetic.

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We can use MATLAB to display a profile of brightness along a line in the image.

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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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So far we have taken a linear combination of pixels in the box around the input pixel, but non-linear operations like sorting and ranking the pixel values also prove to be very useful. We look at the median filter which is much better at removing salt and pepper noise from image than simple smoothing.

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We can also describe a blob by its contour or perimeter. Let’s look at how we determine the length of a blob’s perimeter using crack code and chain code. We can use the perimeter length to determine another scale and invariant shape parameter called circularity which indicates how compact, or circle-like, the blob is.

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Many scenes, particularly of man-made environments, have very dominant lines due to the edges of objects. The Hough transform is a common technique for finding dominant lines, and we ill examine how it works and apply it to a real 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.