Texture2-1

Texture2-1 - Texture Texture Edge detectors find...

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Texture
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Texture Edge detectors find differences in overall intensity. Average intensity is only simplest difference. many slides from David Jacobs
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Issues: 1) Discrimination/Analysis (Freeman)
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2) Synthesis
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Other texture applications 3. Texture boundary detection. Segmentation 4. Shape from texture.
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Gradient in the spacing of the barrels (Gibson 1957)
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Texture gradient associated to converging lines (Gibson1957)
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What is texture? Something that repeats with variation. Must separate what repeats and what stays the same. Model as repeated trials of a random process The probability distribution stays the same. But each trial is different.
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Simplest Texture Each pixel independent, identically distributed (iid). Examples: Region of constant intensity. Gaussian noise pattern. Speckled pattern
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Texture Discrimination is then Statistics Two sets of samples. Do they come from the same random process?
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Simplest Texture Discrimination Compare histograms. Divide intensities into discrete ranges. Count how many pixels in each range. 0-25 26-50 225-250 51-75 76-100
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How/why to compare Simplest comparison is SSD, many others. Can view probabilistically. Histogram is a set of samples from a probability distribution. With many samples it approximates distribution.
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This note was uploaded on 01/12/2012 for the course CMSC 733 taught by Professor Staff during the Spring '08 term at Maryland.

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Texture2-1 - Texture Texture Edge detectors find...

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