Using Matlab for Thin Section Analysis Sam DeNicola Fall Semester, 2014 EPS 109.
Post on 17-Dec-2015
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EDU>> MineralAnalysis('hblendeplagiometals.jpg')How many different minerals are there in the rock sample? : 3Name of 1 Mineral Species : PlagioclaseName of 2 Mineral Species : HornblendeName of 3 Mineral Species : Opaque MetalsPlease estimate how many different distinct mineral colors thereare in the rock sample in order to filter the image : 4Creating filtered image for easier processing Please select the characteristic colors for Plagioclase and then press "Enter"Please select the characteristic colors for Hornblende and then press "Enter"Please select the characteristic colors for Opaque Metals and then press "Enter"Creating masks for images Creating isolated images of crystals of Plagioclase using the image mask... Creating isolated images of crystals of Hornblende using the image mask... Creating isolated images of crystals of Opaque Metals using the image mask...
Method for analysis• Read image input by user with Matlab
function imread• Allow for user input of number of
minerals present in thin section, and number of distinct colors seen in the slide.
• Use number of colors to create a filtered image
• Have user select characteristic colors for each named mineral
• Iterate through the image checking each pixel’s RGB values against user’s selections
• Create BW image mask coloring all pixels white where the colors matched, leaving the rest black• Slightly filter images to get rid of
noise• Count white pixels for data
• Use pixel count and Matlab functions to provide analysis
Sample command line
BackgroundMinerals in thin section can have characteristic colors in plane polarized light. They also have characteristic ranges of birefringence colors in cross-polarized light that depend on the mineral grain orientation on the slide and the crystalline structure of the given mineral. Birefringence is defined as the difference between the largest and smallest refractive index of a mineral.
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