… novel Joint Pixel and Feature Alignment (JPFA) framework for crossdataset palmprint recognition
through two-stage alignment, ie., pixel… For the first stage, on pixel level, fake images are …

… For cross-dataset palmprint recognition, two datasets … Joint Pixel and Feature Alignment
(JPFA) framework for cross-dataset palmprint recognition through two-stage alignment, ie., pixel-…

… a joint constrained LSR (JCLSR) model to enhance the palmprint recognition performance.
Fig… Then, all ROIs were resized to 128 × 128 pixels in our experiments. Fig. 6(d) shows some …

… Then, for each pixel of the palmprint image, we calculate the convolution value differences
on each pair of neighboring directions. Finally, we concatenate 12 convolution value …

… exiting coding-based palmprint recognition methods even the … -based palmprint recognition
methods, all the pixels in each … all pixels to determine the feature, even including the pixels …

… pixels, we first form a multiview including both texture- and direction-view feature containers
for hand-print images. Then, we aim to jointly … ×110 pixels and uniformly resize the palmprint …

… palmprint and palmvein can be captured simultaneously by using specially designed devices,
the joint use of palmprint … most of pixels in the palmvein map are non-palmvein pixels. For …

… most powerful features for palmprint recognition [14]. Unlike most direction-based descriptors
that directly extract the principal direction feature from single pixel of the convolution result, …

… [10] proposed a novel Joint Pixel and Feature Alignment (JPFA) framework to … palmprint
recognition. However, those methods just consider the cross-dataset palmprint recognition …

… image whose cloud points have a one-to-one correspondence to the pixels in the 2-D
counterpart. (d) Obtained 3-D ROI by extracting the cloud points corresponding to the pixels in 2-D …