Automatic target detection system
Method and apparatus for dual resolution analysis of a scene
Dual resolution method and apparatus for use in automated classification of pap smear and other samples
Pattern recognition apparatus and method
Fovea-centered eye fundus scanner
Image-data reduction technique
Modularly expansible system for real time processing of a TV display, useful in particular for the acquisition of coordinates of known shape objects
Image recognition audience measurement system and method Patent #: 4858000
ApplicationNo. 432013 filed on 11/06/1989
US Classes:382/115, Personnel identification (e.g., biometrics)382/226, Sequential decision process (e.g., decision tree structure)382/228Statistical decision process
ExaminersPrimary: Boudreau, Leo H.
Assistant: Fox, David T.
Attorney, Agent or Firm
International ClassG06K 009/00
AbstractA time series of successive relatively high-resolution frames of image data, any frame of which may or may not include a graphical representation of one or more predetermined specific members (e.g., particular known persons) of a given generic class (e.g. human beings), is examined in order to recognize the identity of a specific member if that member's image is included in the time series. The frames of image data may be examined in real time at various resolutions, starting with a relatively low resolution, to detect whether some earlier-occurring frame includes any of a group of image features possessed by an image of a member of the given class. The image location of a detected image feature is stored and then used in a later-occurring, higher resolution frame to direct the examination only to the image region of the stored location in order to (1) verify the detection of the aforesaid image feature, and (2) detect one or more other of the group of image features, if any is present in that image region of the frame being examined. By repeating this type of examination for later and later occurring frames, the accumulated detected features can first reliably recognize the detected image region to be an image of a generic object of the given class, and later can reliably recognize the detected image region to be an image of a certain specific member of the given class.