no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak kr. Basu
Therefore this paper describes an efficient approach of human face recognition based on wavelet transform from thermal IR images.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak kr. Basu
Image processing methods are used to pre-process the captured thermogram, from which different physiological features based on blood perfusion data are extracted.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
Secondly face features are extracted from the croped region, which will be taken as the input of the back propagation feed forward neural network in the third step and classification and recognition is carried out.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
In the first approach, the training images and the test images are processed with Haar wavelet transform and the LL band and the average of LH/HL/HH bands sub-images are created for each face image.