Feature extraction Of Heterogeneous Face images using SIFT and MLBP algorithm
Farinaparveen Khan , R K Krishna
Face Recognition, Heterogeneous Face Recognition, Gaussian, Difference of Gaussian, CSDN, SIFT, MLBP.
— Humans often use the faces to recognize and similar recognition can enable automatically now by advancement in computing capabilities. The recognition process has now been matured into a science of sophisticated mathematical representation and matching process than early face recognition have been used simple geometric models. Face recognition has received a great deal of attention over the last few years because of its many applications in various domains. The main objective is to extract the distinctive invariance features from the Heterogeneous images that can be use to perform reliable matching between probe and gallery images. The features are highly distinct, so that single feature can be correctly matched with high probability against a large database of features from many images. Initially we remove the noise from the image. To remove the noise present in the image we use three filters. Then to extract distinct features by using SIFT and MLBP.