Using the Autocorrelation Function in NIH-Image to Determine Shape-Preferred Orientations
Cameron Davidson
, Carleton College
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This activity is part of the On the Cutting Edge Peer Reviewed Teaching Activities collection.
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Carleton College Teaching Activity Collection through its collaboration with the SERC Pedagogic Service.
Summary
Students learn how to use the autocorrelation function in NIH-Image to quantify shape-preferred orientations. Students develop understanding of what the autocorrelation function does by using synthetic images and then apply this knowledge to real rocks.
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Context
Audience
Undergraduate structural geology course; typically juniors and seniors.
Skills and concepts that students must have mastered
Students should be comfortable using spreadsheets to organize, manipulate, and graph data; basic understanding of shape-preferred orientation in rocks (e.g. foliation).
How the activity is situated in the course
Designed to be completed in a four-hour laboratory period. However, students are given a week to complete the activity.
Goals
Content/concepts goals for this activity
- Learn how to use NIH-Image to quantify shape-preferred orientations in images.
- Discover how autocorrelation images vary with aspect ratio of particles and the amount of preferred orientation (fabric intensity).
- Apply this understanding to rocks.
Higher order thinking skills goals for this activity
Collecting and manipulating real data; making decisions on what the data mean.
Other skills goals for this activity
Making figures, writing figure captions, presenting data and interpretations in narrative form.
Description of the activity/assignment
This activity can be completed individually or in small groups. The first part of the activity focuses on exploration and discovery of how autocorrelation function (ACF) images correspond to real images. The students are given six synthetic images with particles of known aspect ratio and shape preferred orientation. They follow a detailed recipe for generating ACF's, construct a figure comparing images and ACF's, and are asked to write a short narrative describing the qualitative relationship between an image and ACF shape. The students then learn how to measure the ellipticity of ACF contours and plot these data to discover the relationship between shape preferred orientation and ACF ellipticity. After completing the discovery part of the activity, the students apply this knowledge to images of thin sections from the Quottoon pluton near Prince Rupert, British Columbia. In addition, they learn how to measure ACF grain size and plot these data and ACF ellipticity as a function of distance from the Coast shear zone, a major oblique-slip shear zone that defines the western border of the Quottoon pluton. Finally, the students are asked to discuss the relationship between shape preferred orientation, ACF grain size, and the Coast shear zone.
Determining whether students have met the goals
The students construct and hand in three figures, complete with figure captions. For each figure, they write a short narrative describing and interpreting the figure.
More information about assessment tools and techniques.Teaching materials and tips
- Activity Description/Assignment (Acrobat (PDF) 1.3MB Jun14 04)
- Solution Set ( 723kB Jun14 04)
Excel spreadsheet, plus Adobe Illustrator version of pdf images in the Activity Description file above.
Other Materials
Supporting references/URLs
Davidson, C., Rosenberg, C., and Schmid, S.M., 1996, Synmagmatic folding of the base of the Bergell pluton, Central Alps: Tectonophysics, v. 265, p. 213-238.
Panozzo Heilbronner, R. 1992. The auto correlation function: an image processing tool for fabric analysis: Tectonophyscis, v. 212, p. 351-370.
Panozzo Heilbronner, R. 1992. The auto correlation function: an image processing tool for fabric analysis: Tectonophyscis, v. 212, p. 351-370.