• Biometrics fusion recognition is a newly arisen and active research topic in recent years. In 2010, the Group of Machine Learning and Applications, Shandong University (SDUMLA) set up the Homologous Multi-modal Traits Database which is named SDUMLA-HMT Database. The SDUMLA-HMT database consists of face images from 7 view angles, finger vein images of 6 fingers, gait videos from 6 view angles, iris images from an iris sensor, and fingerprint images acquired with 5 different sensors. The database includes real multimodal data from 106 individuals.

Database Description


  • The face database is aiming at real-world applications of face recognition. In order to simulate real-world settings, we capture faces with different poses, facial expressions, accessories and illuminations.
  • Finger Vein

  • Finger vein recognition is a recently developed research hotspot. We include in SDUMLA-HMT a finger vein database which, to the best of our knowledge, is the first open finger vein database.      The device used to capture finger vein images is designed by Joint Lab for Intelligent Computing and Intelligent Systems of Wuhan University. In the capturing process, each subject was asked to provide images of his/her index finger, middle finger and ring finger of both hands, and the collection for each of the 6 fingers is repeated for 6 times to obtain 6 finger vein images. Therefore, our finger vein database is composed of 3,816 images. Every image is stored in "bmp" format with 320×240 pixels in size,and thus, the finger vein database takes up around 0.85G Bytes in total.
  • Gait

  • Three variations, including view angle, accessory and motion type, are considered in the gait data acquisition process. For each subject, we first captured 6 background videos using the 6 cameras before his/her walking. Then the subject was asked to walk naturally along the walking direction for 6 times. After that, the subject was asked to carry a bag and walked twice again. The bag could be a knapsack, a satchel, or a handbag chosen according to the subject's preference. Furthermore, we also recorded twice of the subject's running videos.As a result, there are totally 66 videos recorded for the subject.The gait database is composed of 6×11×106=6,996 videos in total and each video records about 2 to 3 gait cycles. All the videos are stored in “avi” format encoded with XviD codec. The frame size is 320×240 pixels, and the frame rate is 25 frames per second. The total size of the gait database is about 1.6G Bytes.
  • Iris

  • We collected the iris data with an intelligent iris capture device developed by University of Science and Technology of China under near infrared illumination. To avoid reflection, the subjects were asked to take off their glasses and to keep the distance between the eye and the device within 6cm to 32cm. Every subject provided 10 iris images, i.e., 5 images for each of the eyes. Therefore,the iris database is composed of 2×5×106=1,060 images. Every iris image is saved in 256 gray-level “bmp” format with 768 × 576 pixels in size. The total size of our iris database is about 0.5G Bytes.
  • Multi-sensor Fingerprint

  • The multi-sensor fingerprint database includes fingerprint images captured from thumb finger, index finger and middle finger of both hands. In order to explore the sensor interoperability, we captured each of the 6 fingers with 5 different type of sensors, i.e., AES2501 swipe fingerprint scanner developed by Authentec Inc, FPR620 optical fingerprint scanner and FT-2BU Capacitive fingerprint scanner both developed by Zhongzheng Inc, URU4000 optical fingerprint scanner developed by Zhongkong Inc and ZY202-B optical fingerprint scanner developed by Changchun Institute of Optics, Fine Mechanics and Physics, China Academy of Sciences. It is to be noted that 8 impressions were captured for each of the 6 fingers using each of the 5 sensors.The multi-sensor fingerprint database contains 6×5×8×106=25,440 fingerprint images in total. Every fingerprint image is saved in 256 gray-level “bmp” format but the size varies according to the capturing sensors.The total size of the multi-sensor fingerprint database is about 2.2G Bytes.
    PS:The fingerprint images are named in the format of “fingeridx_n.bmp”, where fingeridx = (1, 2, …, 6) is the finger index (i.e., 1 for left thumb, 2 for left index, 3 for left middle, 4 for right thumb, 5 for right index, and 6 for right middle), and n is the repeated impression index ranging from 1 to 8.
  • More Information

    The Announcement of the Copyright

    • All rights of the SDUMLA-HMT are reserved. The database is only available for research and noncommercial purposes. Commercial distribution or any act related to commercial use of this database is strictly prohibited. A clear acknowledgement should be made for any public work based on the database such as" We would like to express our thanks to the MLA Lab of Shandong University for SDUMLA-HMT Database." and please add our related works in the references.Yilong Yin,Lili Liu, and Xiwei Sun. SDUMLA-HMT: A Multimodal Biometric Database. The 6th Chinese Conference on Biometric Recognition (CCBR 2011), LNCS 7098, pp. 260-268, Beijing, China, 2011.

    How to Get the Database

    Contact Information

    • Professor Yilong Yin

    • Machine Learning and Data Mining Lab
    • Department of Computer Science and Technology
    • Shandong University, Jinan, Shandong, P.R. China

    • E-mail:
    • Fax: +86531 88391367