deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications

of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae

of the latents recovered at crime scenes are those of palms. Most of the available high resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae

resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution

Palmprint verification is a relatively new but promising personal authentication technique for its high accuracy and fast matching speed. Two dimensional (2D) palmprint recognition has been well studied in the past decade, and recently three dimensional (3D) palmprint recognition techniques were

This paper presents principle line based palm print matching model as principle lines are easily extracted in even in low resolution images. This paper proposes use of histogram of Radon transform (HRT) to extract the features of palm. However the HRT is sensitive to the rotation and scaling due

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Abstract: Nowadays, high resolution palmprint images are used for recognition. The features that can be extracted from a high resolution palmprint image include the minutiae points. In this paper, instead of full palmprints, partial palmprints are used for matching. Partial refers to a part

palmprints belong to the same hand by computing a matching score between the corresponding sets of feature points of the two palmprints. The two sets of feature points/orientations are matched using our previously developed point matching technique which takes into account the non-linear deformations as well

translation, rotation and distortion between two palmprint images will introduce much error in palmprint matching. However, an accurate registration of palmprint images is too time-consuming. In this paper, we propose a modified complex wavelet structural similarity index (CW-SSIM) to compute the matching