公开(公告)号：AU2009246750A1

公开(公告)日：2009-11-19

申请号：AU2009246750

申请日：2009-04-13

Applicant: IBM

Inventor： RATHA NALINI KANTA ,  AGGARWAL GAURAV ,  JEA TSAI-YANG ,  BOLLE RUDOLF MAARTEN

IPC: G06K9/00

Abstract: Techniques for generating a gradient characterization for a first fingerprint image are provided. One or more fingerprint feature points are selected from the first fingerprint image. A region is obtained for each of the one or more selected fingerprint feature points. The region is a representation of an area proximate a given fingerprint feature point. Each of the obtained regions is divided into a plurality of sub-regions. A histogram is generated for each of the plurality of sub-regions. For each of the one or more selected fingerprint feature points, the one or more generated histograms are combined into a concatenated histogram. The concatenated histogram is used for identification purposes.

公开(公告)号：GB2356961A

公开(公告)日：2001-06-06

申请号：GB0029202

申请日：2000-11-30

Applicant: IBM

Inventor： BOLLE RUDOLF MAARTEN ,  DORAI CHITRA ,  RATHA NALINI K

IPC: A61B5/117 ,  A61B5/11 ,  G06K9/00 ,  G06T7/00 ,  G07C9/00

Abstract: A resultant biometric is a combination of a traditional biometric and some controlled change to the traditional biometric. Resultant finger- or palm prints, for example, are consecutive print images where the subject exerts force, torque and/or rolling (controlled change) over an image acquisition interval of time. The physical way the subject distorts the images is the behavioural part of the resultant biometric, the finger or palm print is the physiological part of the resultant biometric. An undistorted print image in combination with an expression of the distortion trajectory which can be computed from the sequence of distorted print images, forms a more compact representation of the resultant fingerprint. A template representing the resultant print biometrics is derived from the traditional template representing the finger- or palm print plus a template representing the trajectory. Other traditional biometrics also lend themselves to temporal modification.

公开(公告)号：DE69518947T2

公开(公告)日：2001-03-22

申请号：DE69518947

申请日：1995-02-24

Applicant: IBM

Inventor： BOLLE RUDOLF MAARTEN ,  CONNELL JONATHAN HUDSON ,  HAAS NORMAN ,  MOHAN RAKESH ,  TAUBIN GABRIEL

IPC: G06T1/00 ,  G06K9/46 ,  G06T7/00 ,  G07G1/00 ,  G06K9/00 ,  B07C5/10

Abstract: The present system and apparatus uses image processing to recognize objects within a scene. The system includes an illumination source for illuminating the scene. By controlling the illumination source, an image processing system can take a first digitize image of the scene with the object illuminated a higher level and a second digitized image with the object illuminated at a lower level. Using an algorithm, the object(s) image is segmented from a background image of the scene by a comparison of the two digitized images taken. A processed image (that can be used to characterize features) of the object(s) is then compared to stored reference images. The object is recognized when a match occurs. The system can recognize objects independent of size and number and can be trained to recognize objects that it was not originally programmed to recognize.

公开(公告)号：AT196695T

公开(公告)日：2000-10-15

申请号：AT95102666

申请日：1995-02-24

Applicant: IBM

Inventor： BOLLE RUDOLF MAARTEN ,  CONNELL JONATHAN HUDSON ,  HAAS NORMAN ,  MOHAN RAKESH ,  TAUBIN GABRIEL

IPC: G06T1/00 ,  G06K9/46 ,  G06T7/00 ,  G07G1/00 ,  G06K9/00 ,  B07C5/10

Abstract: The present system and apparatus uses image processing to recognize objects within a scene. The system includes an illumination source for illuminating the scene. By controlling the illumination source, an image processing system can take a first digitize image of the scene with the object illuminated a higher level and a second digitized image with the object illuminated at a lower level. Using an algorithm, the object(s) image is segmented from a background image of the scene by a comparison of the two digitized images taken. A processed image (that can be used to characterize features) of the object(s) is then compared to stored reference images. The object is recognized when a match occurs. The system can recognize objects independent of size and number and can be trained to recognize objects that it was not originally programmed to recognize.