Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
The appearance of a face image is severely affected by illumination conditions that hinder the automatic face recognition process. To recognize faces under varying illuminations, ...
We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient ba...
We present a spatially variant framework for correcting uneven illumination and color cast, problems commonly associated with digitized books. The core of our method is a color im...
In this paper enhancement of a digital image is done by detecting the noisy and noiseless region of the image. The noisy regions are smoothed and the noiseless regions are sharpen...