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Users post images on Social media, highlighting miniature objects holding in their hands. These posts may contain fingers in the uploaded photograph. Few of these photographs also contain clearly visible ridge-valley details. Using hashtags #miniature, #myhand, and #finger, we collect Social-Media Posted Finger-selfie (SMPF) database. The database consists of 1,000 images, each of which is collected from public Instagram posts. These images are handpicked so that ridge-valley details in proximal phalanx is visible.
The database can be downloaded from here.
IIITD SmartPhone Finger-selfie Database v2 (ISPFDv2) consists of more than 17,000 finger-selfies and 2432 livescan fingerprint images obtained from 304 unique fingers. The finger-selfie images are taken using two smartphones: OnePlus One (OPO) and Micromax Canvas Knight, while, livescan fingerprints are acquired using Secugen Hamster IV at 500 PPI. Indoor images are captured in both constrained and uncontrolled environments, while in outdoor conditions, images are captured without flash during daylight and with flash during the night. Auto-focus is always kept at ON status. Based on the challenges considered, the database is divided into four subsets.
The database can be downloaded from here.
The Unconstrained Fingerphoto Database (UNFIT database) consists of fingerphotos captured using 45 different smartphones. It has data for 115 subjects, collected for both index and middle finger, separately and together. Hence, there are a total of 230 classes. This database covers many challenges present in a real-world unconstrained environment such as illumination, motion blur, affine variations, and optional usage of camera flash. The database also includes ground truth annotations of the location of the finger(s).
The database can be downloaded from here.
Children Multimodal Biometric Database (CMBD) consists of iris, fingerprint, and face images of over 100 children (age range of 18 months to 4 years), acquired over two sessions. The iris images are captured using Cross-Match iris scanner, fingerprints are captured using Cross-Match L-scan slap fingerprint scanner and face images are captured using Nikon D90 DSLR. It has data for 106 across both the session and for all 3 modalities. However, to protect the identities of the participants, we have provided iris and fingerprint images only.
The database can be downloaded from here.
Spoofed Fingerphoto Database consists of spoofed fingerphotos images captured using OnePlus One and Nokia while spoofed using iPad, Laptop, Nexus and printout. It has data for 128 classes(64 subjects * 2 fingers). This database contains spoofed images across 2 illumination variations and 2 background variations.
The database can be downloaded from here.
IIITD SmartPhone Fingerphoto Database v1 (ISPFDv1) consists of fingerphotos and live scan images captured using Lumidgm Sensor. It has data for 64 subjects, collected for both right index and right middle finger, hence making a total of 128 classes. This database covers illumination and background variation challenges.
The database can be downloaded from here.
IIITD Multi-surface Latent Fingerprint Database (IIITD MSLFD) consists of 551 latent fingerprints from 51 subjects lifted from eight different surfaces. The eight surfaces are: 1) Ceramic plate, 2) Ceramic mug, 3) Transparent glass, 4) Steel glass, 5) Compact disc, 6) Compact disc mailer (CD mailer), 7) Paperback book cover, and 8) Hardbound book cover. The corresponding slap fingerprint (4+4+2 prints) gallery images are captured using CrossMatch L-Scan Patrol at 500 dpi.
The database can be downloaded from here.
MOLF database has 19,200 fingerprints collected using from 100 subjects using five different capture methods: (i) Lumidigm Venus IP65 Shell, (ii) Secugen Hamster-IV, (iii) CrossMatch L-Scan Patrol, (iv) Latent fingerprints, and (v) simultaneous latent fingerprints lifted using black powder dusting process.
The database can be downloaded from here.
Simultaneous Latent Fingerprint(SLF) Database consists of simultaneous latent fingerprint of 15 subject along with their mated 500ppi optical slap fingerprints. Simultaneous latent fingerprint are obtained using black powder dusting technique with a plain tile as background. Optical fingerprints are captured using Crossmatch LScan Patrol.
The database can be downloaded from the following link.
The IIIT-D latent fingerprint database is an exclusive database consisting of only latent fingerprint impressions of all 10 fingers of 15 subjects. Multiple instances are captured for every fingerprint, enabling latent to latent fingerprint comparison. The latent fingerprints are lifted from two different backgrounds - card and tile- trying to simulate different environments from which they are lifted. Also, the dryness of the skin friction ridge is varied to obtain multiple impressions of varying quality and information. There are in total 1046 latent fingerprints. Mated 500ppi and 1000ppi fingerprint sensor images are available. The 500ppi are slap images captured using Crossmatch L1scan. The 1000ppi images are captured using SecuGen Hamster IV. This database is made public to facilitate researchers to publish results over a common database.
The database can be downloaded from the following link.
The Rural Indian Fingerprint Database comprises images captured from both rural and urban population of India.