Jianjiang Feng's Homepage

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Handbook D. Maltoni, D. Maio, A. K. Jain, J. Feng, Handbook of Fingerprint Recognition (Third Edition), Springer, 2022.
2D fingerprint pose estimation 2D fingerprint pose estimation
Estimation of fingerprint pose has applications in fingerprint feature extraction, quality estimation, matching, and indexing.
3D fingerprint reconstruction 3D fingerprint reconstruction
3D fingerprint is the original form of fingerprint, containing the most complete feature information. We explore how to use low-cost sensors (such as, a single camera, various touch-based fingerprint sensors) to capture 3D fingerprints.
Rectification of distorted fingerprint Rectification of distorted fingerprint
Recognition rate can be improved by estimating the distortion field from a distorted fingerprint and then rectifying it into a normal fingerprint.
Latent fingerprint feature extraction Latent fingerprint feature extraction
Automatic feature extraction in latent fingerprints is extremely challenging due to poor quality of most latents, such as unclear ridge structures, overlapped lines and letters, and overlapped fingerprints.
Separating overlapped fingerprints Separating overlapped fingerprints
Overlapped fingerprints are not unusual in latent fingerprints taken from crime scenes. However, separating overlapped fingerprints into individual fingerprints is a very challenging problem for both existing automatic fingerprint recognition systems and human fingerprint experts. We proposed algorithms for separating overlapped fingerprints.
Altered fingerprint Fingerprint quality assessment
Fingerprint quality assessment is important for capturing high quality fingerprints and detecting uncooperative behaviors. We propose several algorithms to detect low quality fingerprints caused by different factors.
Fingerprint reconstruction Fingerprint reconstruction from minutiae
The compactness of minutiae representation has created an impression that minutiae does not contain sufficient information to allow the reconstruction of the original fingerprint image. This opinion is challenged by the proposed fingerprint reconstruction technique. The proposed technique also has other uses, such as reconstructing latent prints using minutiae marked by human experts, and improving the performance of fingerprint recognition systems with limitted storage space.
Dense registration of fingerprints Dense registration of fingerprints
Dense registration is useful for fingerprint matching and mosaicking.
Small Fingerprint Matching Small Fingerprint Matching
Latent fingerprint matching Latent fingerprint matching
Latent fingerprint identification is of critical importance for identifying suspects. Poor quality of ridge impressions, small finger area and large non-linear distortion are the main difficulties in latent fingerprint matching, compared to plain or rolled fingerprint matching.
Latent palmprint Latent palmprint matching
Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, have a complex background and many creases.
Ridge Matching Ridge skeleton matching
The most popular fingerprint representation is based on minutiae points, which is a compact and lossy representation of ridge skeleton, the Level 2 representation of fingerprints. Here we explore matching ridge skeletons directly for the purpose of completely utilizing the discriminating power of Level 2 features in fingerprints.
Global descriptors Global descriptors
Minutia descriptor Minutia descriptors
Establishing minutiae correspondence between two fingerprints is difficult due to unknown alignment, nonlinear deformation, noise, and occlusion. Designing robust minutia descriptors is a way to facilitate this problem.
Synthetic palmprint Statistical modeling of friction ridge patterns
Statistical modeling of friction ridge patterns is a fundamental problem and can be used in both synthesis and analysis of friction ridge patterns.

3D finger pose estimation 3D finger angle estimation
Estimation of 3D finger angle (orientation) can be used in human computer interaction.
Text entry via fingerprint recognition Text entry via fingerprint recognition
By turning all fingers into a keyboard, PrinType can be used for text entry in VR/AR, text entry of blind people, and continuous authentication.
Shear Shear input via fingerprint deformation
Lateral, longitudinal and rotational deformations are extracted from fingerprint images and mapped to 3DOF control commands.

Vessel segmentation Vesssel segmentation
Vessel landmark Detection of vesssel landmarks
Vessel registration Vesssel registration
Pneumonia Diagnosis of pneumonia
LAA Segmentation of left atrial appendage

Tracking Multi-object tracking
Human analysis from point cloud Human analysis from point cloud