org.openimaj.image.processing.face.feature.ltp

Interface LTPWeighting

All Superinterfaces:

ReadableBinary, ReadWriteableBinary, WriteableBinary

All Known Implementing Classes:

GaussianWeighting, TruncatedWeighting

@Reference(type=Article,
           author={"Xiaoyang Tan","Triggs, B."},
           title="Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions",
           year="2010",
           journal="Image Processing, IEEE Transactions on",
           pages={"1635 ","1650"},
           month="june ",
           number="6",
           volume="19",
           customData={"keywords","CAS-PEAL-R1;Gabor wavelets;PCA;distance transform based matching;extended Yale-B;face recognition;kernel-based feature extraction;local binary patterns;local spatial histograms;local ternary patterns;local texture feature set enhancement;local texture-based face representations;multiple feature fusion;principal component analysis;robust illumination normalization;face recognition;feature extraction;image enhancement;image fusion;image representation;image texture;principal component analysis;wavelet transforms;Algorithms;Biometry;Face;Humans;Image Enhancement;Image Interpretation, Computer-Assisted;Imaging, Three-Dimensional;Lighting;Pattern Recognition, Automated;Reproducibility of Results;Sensitivity and Specificity;Subtraction Technique;","doi","10.1109/TIP.2010.2042645","ISSN","1057-7149"})
public interface LTPWeighting
extends ReadWriteableBinary

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Method Summary

Methods

Modifier and Type	Method and Description
float	weightDistance(float distance) Determine the weighting scheme for the distances produced by the EuclideanDistanceTransform.

Methods inherited from interface org.openimaj.io.ReadableBinary

binaryHeader, readBinary

Methods inherited from interface org.openimaj.io.WriteableBinary

binaryHeader, writeBinary

Method Detail

weightDistance

float weightDistance(float distance)

Determine the weighting scheme for the distances produced by the EuclideanDistanceTransform.

Parameters:

distance - the unweighted distance in pixels

Returns:

the weighted distance