The present invention provides a method and apparatus for the production and labeling of objects in a manner suitable for the prevention and detection of counterfeiting. Thus, the system incorporates a variety of features that make unauthorized reproduction difficult. In addition, the present invention provides an efficient means for the production of labels and verification of authenticity, whereby a recording apparatus which includes a recording medium, having anisotrophic optical domains, along with a means for transferring a portion of the recording medium to a carrier, wherein a bulk portion of the recording medium has macroscopically detectable anisotrophic optical properties and the detecting apparatus thereon.

Authentication method and system

A system and method for recognizing and interpreting diagrammatic and graphical representations in a computer. A user specifies a problem by inputting a graphical or diagrammatic representation of the problem. A recognition process according to the invention identifies symbols in the representation, identifies relationships between the symbols, and generates an adjacency matrix corresponding to a graph that represents information obtained from the identified symbols and their relationships to each other. The adjacency matrix may be simplified and used to produce computer-readable output for execution by other program components to solve the problem. With this invention, users can easily use their Tablet PCs, smart pens, other pen-centric computers or any other such input mechanisms (such as WACOM tablets or mouse) to “draw” their problem and solve it.

Recognition and interpretation of graphical and diagrammatic representations

A method and apparatus for determining a digital signature from an article made of paper, cardboard, plastic or many other material types. A coherent light source directs a beam to illuminate the article and a detector arrangement collects data points from light scattered from many different parts of the article to collect a large number of independent data points, typically 500 or more. By collecting a large number of independent signal contributions specific to many different parts of the article, a digital signature can be computed that is unique to the area of the article that has been scanned. This measurement can be repeated whenever required to test authenticity of the article. Using this method, it has been discovered that it is essentially pointless to go to the effort and expense of making specially prepared tokens, since unique characteristics are measurable a in a straightforward manner from a wide variety of every day articles.

Authenticity verification methods, products and apparatuses

Utilizing an image on a computing device to serve as a template for locking/unlocking the computing device. The image includes a plurality of portions that are defined and thereafter identified and presented to a user via a touch screen. A user selects portions/zones that are defined within the image in a specified sequence and this sequence is stored as a lock/unlock code for unlocking the computing device. In an embodiment, in addition to the specified sequence of selections, a movement or sequence of movements may be also be stored as part of the lock/unlock code.

Image-based unlock functionality on a computing device

Image based login procedures for computer systems include: (a) displaying a first image on a computer screen; (b) receiving user input indicating a portion of the first image; (c) determining if the user input corresponds to a first acceptable user input for user authentication; and (d) proceeding with the authentication procedure when this user input corresponds to the first acceptable user input for user authentication. Additionally or optionally, when proceeding with this authentication procedure, the systems and methods further may include: displaying a second image on the screen; receiving new user input indicating a portion of the second image; and determining if this new input corresponds to a second acceptable user input for user authentication.

Image or pictographic based computer login systems and methods

Pattern recognition, for instance optical character recognition, is achieved by defining a minimal bounding rectangle around a pattern, dividing the pattern into a grid of boxes, comparing a vector derived from this partitioned pattern to vectors similarly derived from known patterns, choosing a set of Pareto non-inferior candidate patterns, and selecting a recognized pattern from the set of candidates. The vectors include pixel density matrices, matrices of horizontal connectivity of boxes, and matrices of vertical connectivity of boxes.

Malitsky Sofya

Papers

Multifont optical character recognition using a box connectivity approach