Morphotrust Usa, LLC

Electro-optical Sciences, Inc.

Other

Idemia Identity & Security USA LLC

Mela Sciences, Inc.

Idemia Public Security France

Alexandru Bogdan

Adam Jacobs

Dina Gutkowicz-Krusin

Marek Elbaum

Michael Greenebaum

Brian K Martin

Rein-Lien Hsu

Joseph R Mayer

Brian Martin

A system for authenticating a subject identification document includes instructions causing a processor to receive a first image of the document, depicting, in RGB color space, the document illuminated by UV light, and transform the first image to a second image in YCbCr color space. The instructions cause the processor to divide the second image into regions of interest (ROIs), and, for each ROI, generate a color profile descriptor including first data elements associated with pixel color in the YCbCr color space, and second data elements associated with pixel intensity of pixels within the ROI. The instructions also cause the processor to generate a score for the second image based on a comparison of the color profile descriptor for each ROI to a corresponding ROI of an enrolled document template, and compare the score to a threshold to determine whether the document is authenticated.

Systems and methods for document authentication

A document inspection system performs texture analysis on a portion of a first image that represents a first document and on a portion of a second image that represents a second document; performing. Feature vectors for the regions from the first and second documents are compared. If the feature vectors have a threshold degree of similarity, they may be identified as being sufficiently related. This may have applicability, for example, in determining with a first document is valid because reflects sufficiently-similar characteristics to those of a reference document.

Document authentication

A method for detecting images of fraudulently generated or photocopied secure credential documents using texture analysis includes receiving, by one or more processors, an image of a secure credential document from a computer device. The one or more processors segment the image of the secure credential document into multiple regions. For each region of the multiple regions, the one or more processors extract local high-resolution texture features from the image of the secure credential document. The one or more processors generate a score based on the local high-resolution texture features using a machine learning model. The score is indicative of a likelihood that the image of the secure credential document is fraudulently generated or photocopied. The one or more processors transmit a message to a display device indicating that the image of the secure credential document is fraudulently generated or photocopied.

Detection of fraudulently generated and photocopied credential documents

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for facial recognition using fractal features are disclosed. In one aspect, a method includes the actions of accessing data encoding a facial image, the facial image including a face. The actions further include generating a hierarchical graphical model of the face in the facial image, the hierarchical graphical model including more than nodes from at least one level, each level approximating the face within a contour. The actions further include applying a bank of filters to the face at a particular node, each filter spanning more than one scale and at least one direction. The actions further include analyzing filter responses from the bank of filters applied at each direction to obtain a similarity measure that consolidates filter responses from filters applied at more than one scale. The actions further include generating a vector representation.

Facial recognition using fractal features

Among other things, a texture of an image is characterized by deriving lacunarity measures from the image based on a wavelet analysis.

Characterizing a texture of an image

A light image is conveyed from a biological tissue through a flexible optical system to an image receiver, where it is converted to a form which may be entered into a computer. The computer segments the image by generating a segmentation mask defining the boundary of a region of interest in at least one spectral band, estimates at least one rotationally and translationally invariant statistical measure of coefficient distributions of the multiscale wavelet maxima representations of the digital images in at least one spectral band, characterizes the condition of the tissue based on the estimated values, and outputs the characterization of the condition of the tissue.

Multispectral imaging and characterization of biological tissue

Systems and methods for the multispectral imaging of skin tissue enables automatic characterization of the condition of a region of interest of the skin, based on direct digital imaging of the region of interest or the digitization of color photographic slides of the region of interest, illuminated by appropriately filtered light. Preferably, a digital image at a low spectral band is automatically segmented and that segmented mask is used to segment the other images by a digital processor. Parameters are estimated through wavelet maxima representations. Parameters related to the texture, asymmetry, blotchiness and border irregularities are also automatically estimated. The region of interest is automatically characterized by the digital processor, based on those parameters. The region of interest may include a skin lesion, in which case the present invention enables the characterization of the lesion as malignant or benign. The region of interest may also include wounds or burns.

Growing community of inventors

New York, NY, United States of America

Alexandru Bogdan