Illumination robust face representation based on intrinsic geometrical information

collaboration: keywords: Illumination robust face representation; intrinsic geometrical information; naturalistic human-robot interaction system; human-computer interaction system; binary non-subsampled contourlet transform; B-NSCT; multidirectional contour information; multiscale contour information; facial texture; CMU PIE databases; Yale B databasescollaboration: keywords: Illumination robust face representation; intrinsic geometrical information; naturalistic human-robot interaction system; human-computer interaction system; binary non-subsampled contourlet transform; B-NSCT; multidirectional contour information; multiscale contour information; facial texture; CMU PIE databases; Yale B databasescollaboration: keywords: Illumination robust face representation; intrinsic geometrical information; naturalistic human-robot interaction system; human-computer interaction system; binary non-subsampled contourlet transform; B-NSCT; multidirectional contour information; multiscale contour information; facial texture; CMU PIE databases; Yale B databasescollaboration: keywords: Illumination robust face representation; intrinsic geometrical information; naturalistic human-robot interaction system; human-computer interaction system; binary non-subsampled contourlet transform; B-NSCT; multidirectional contour information; multiscale contour information; facial texture; CMU PIE databases; Yale B databasescollaboration: keywords: Illumination robust face representation; intrinsic geometrical information; naturalistic human-robot interaction system; human-computer interaction system; binary non-subsampled contourlet transform; B-NSCT; multidirectional contour information; multiscale contour information; facial texture; CMU PIE databases; Yale B database

Image Quality Assessment Based on Contourlet and ESD Method

In recent years, the development of the digital image processing promotes the research of the image quality assessment (IQA). A novel metric for full-reference image quality assessment is presented. The metric combined the contourlet transform with the energy of structural distortion (ESD), namely the CT-ESD. The calculation of the ESD is carried out in each subband of the contourlet transform. Then the comparisons between the reference and the distorted images on each subband are integrated by weighting sum. The superiority of the contourlet transform integrates well into new IQA metric. Experiments performed on the database TID2013 demonstrate that the CT-ESD can achieve high consistency with the subjective evaluation

Segmentation Of Retinal Vasculature Using Contourlet Enhancement For Early Detection Of Diabetic Retinapthy

In this project we use contourlet transform rather than wavelet transform because the contourlet transform was proven to require less number of coefficient compared to wavelet and contourlet also have the ability to detect directional signal. The enhanced blood vessel will be extract by BottomHat. This transformation works by isolating dark object on light surrounding