Matlab functions


Name
Description
Link
ComputeFeatures
Wrapper function to compute LBP features
ComputeFeatures.m
DoClassification
Performs supervised classification
DoClassification.m
EvaluateCrossAccuracy.m Estimates classification accuracy EvaluateCrossAccuracy.m
FeatureSelection.m
Performs feature selection (DLBP, LDLBP)
FeatureSelection.m
GenerateTrainAndTestNumbers.m
Generates random subdivisions into train and test set
GenerateTrainAndTestNumbers.m
GetFileNames.m Returns the names of the files contained in a directory
GetFileNames.m
ltp.m
Local Ternary Patterns
ltp.m
NearestMeanClassifier.m
Nearest mean classification
NearestMeanClassifier.m
SCRIPT.m
Sample script
SCRIPT.m

Dependencies

The following additional Matlab toolboxes and functions are required to run the code. The dependencies should be accessible to Matlab at execution time.



Instructions

  1. Create a new directory (e.g.: ./mydir);
  2. Save the Matlab functions listed above in ./mydir;
  3. Install the required toolboxes;
  4. Create the following empty subdirectories:
    • ./mydir/Classification;
    • ./mydir/Datasets;
    • ./mydir/Features;
    • ./mydir/Labels;
    • ./mydir/LaTeX;
  5. Download and unzip the images from here. Make sure to maintain the following structure:
    • ./mydir/Datasets/ALOT/{000,060,120,180}/...
    • ./mydir/Datasets/BRODATZ/{00,10,...,90}/...
    • ./mydir/Datasets/KYLBERG_SINTORN/{000,040,...,320}/...
    • ./mydir/Datasets/MONDIAL_MARMI/{00,05,10,...,90}/...
    • ./mydir/Datasets/OUTEX_45/{00,05,10,...,90}/...
    • ./mydir/Datasets/VECTORIAL/{00,10,...,90}/...
    • ./mydir/Datasets/PAP_SMEAR/{00}/...
    • ./mydir/Datasets/2D_HeLa/{00}/...
  6. Download and unzip in ./mydir the TRAIN and TEST numbers;
  7. Launch SCRIPT.m;
  8. Retrieve the results in LaTeX format in /mydir/LaTeX.



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