Method and Apparatus of Authenticating Documents Having Embedded Landmarks

A computer-implemented method of authenticating documents, comprising:

• capturing, sequentially at a first set of placement angles that are different from each other, a first set of photo images of one or more security features of a known authentic document that is placed under an illumination condition, wherein the known authentic document is of a document genre, and wherein the one or more security features, when illuminated, are visible, partially or fully, at the first set of placement angles;
• for each of the first set of photo images, estimating, by using a computer-implemented machine learning algorithm, an angle of the known authentic document being held at the time when the photo image was captured, and aggregating the angle in association with the photo image of the first set of photo images into a first set of estimated angles, and storing the first set of estimated angles along with the first set of photo images;
• training a computer vision algorithm to learn and model a set of document's angular responses of the document genre under the illumination condition based on the first set of photo images and the first set of estimated angles, wherein the training deduces at least one piece of descriptive information about each security feature of the one or more security features based on the first set of photo images and the first set of estimated angles, and produces a learned model encoded with the set of document's angular responses of the document genre under the illumination condition that contains the at least one piece of descriptive information about each security feature of the one or more security features;
• capturing, sequentially at a second set of placement angles that are different from each other, a second set of photo images of a security feature of a first unknown document that is placed under the illumination condition, wherein the first unknown document is of the document genre and whose authenticity is to be determined, and wherein the second set of placement angles are mechanically secured, by an automated angle adjustment means, to be equal to values of the first set of estimated angles;
• storing the second set of placement angles along with and in association with the second set of photo images;
• and
• determining the authenticity of the first unknown document by applying the learned model on the second set of images and the second set of placement angles, wherein the applying the model at least involves comparing a piece of descriptive information about the security feature of the second unknown document that is encoded in the learned model as a part of the document's angular responses of the document genre under the illumination condition, with a piece of information about the security feature of the first unknown document extracted from the second set of the photo images and the second set of placement angles, wherein the comparing step produces a first confidence value, and if the first confidence value is below a pre-determined confidence threshold, the first unknown document is determined to be unauthentic, otherwise the first unknown document is determined to be authentic with regard to the security feature of the first unknown document.

A computer-implemented method of authenticating documents, comprising:

• retrieving, from a database, a first set of photo images of one or more security features of one or more known authentic documents of a document genre, wherein the first set of photo images are pre-captured, sequentially at a first set of placement angles that are different from each other, on the one or more security features of the one or more known authentic documents that are placed under an illumination condition, wherein the one or more security features, when illuminated, are visible, partially or fully, at the first set of placement angles;
• for each of the first set of photo images, estimating, by using a computer-implemented machine learning algorithm, an angle of the one or more known authentic documents being held when the photo image was captured, and aggregating the estimated angle in association with the photo image of the first set of photo images into a first set of estimated angles, and storing the first set of estimated angles along with the first set of photo images;
• training a computer vision algorithm to learn and model a set of document's angular responses of the document genre under the illumination condition based on the first set of photo images and the first set of estimated angles, wherein the training deduces at least one piece of descriptive information about each security feature of the one or more security features based on the first set of photo images and the first set of estimated angles, and produces a learned model encoded with the set of document's angular responses of the document genre under the illumination condition that contain the at least one piece of descriptive information about each security feature of the one or more security features;
• capturing, sequentially at a second set of placement angles that are different from each other, a second set of photo images of a security feature of a first unknown document that is placed under the illumination condition, wherein the first unknown document is of the document genre and whose authenticity is to be determined;
• for each of the second set of photo images, estimating, by using the computer-implemented machine learning algorithm, an angle of the first unknown document being held at the time when the photo image was captured, and aggregating the angle in association with the photo image of the second set of photo images into a second set of estimated angles, and storing the second set of estimated angles along with the second set of photo images;
• and
• determining the authenticity of the first unknown document by applying the learned model on the second set of images and the second set of estimated angles, wherein the applying the model at least involves comparing a piece of descriptive information about the security feature of the first unknown document that is encoded in the learned model as a part of the document's angular responses of the document genre under the illumination condition, with a piece of information about the security feature of the first unknown document extracted from the second set of the photo images and the second set of estimated angles, wherein the comparing step produces a first confidence value, and if the first confidence value is below a pre-determined confidence threshold, the first unknown document is determined to be unauthentic, otherwise the first unknown document is determined to be authentic with regard to the security feature of the first unknown document.

A computer-implemented method of authenticating documents, comprising:

• retrieving, from a database, a first set of photo images of one or more security features of one or more known authentic documents of a document genre, wherein the first set of photo images are pre-captured, sequentially at a first set of placement angles that are different from each other, on the one or more security features of the one or more known authentic documents that were placed under an illumination condition, wherein the one or more security features, when illuminated, are visible, partially or fully, under the illumination condition;
• for each of the first set of photo images, estimating, by using a computer-implemented machine learning algorithm, an angle of the one or more known authentic documents being held when the photo image was captured, and aggregating the angle in association with the photo image of the first set of photo images into a first set of estimated angles, and storing the first set of estimation angles along with the first set of photo images;
• training a computer vision algorithm to learn and model a set of document's angular responses of the document genre under the illumination condition based on the first set of photo images and the first set of estimated angles, wherein the training deduces at least one piece of descriptive information about each security feature of the one or more security features based on the first set of photo images and the first set of estimated angles, and produces a learned model encoded with the set of document's angular responses of a document type under the illumination condition that contains the at least one piece of descriptive information about each security feature of the one or more security features;
• capturing, sequentially at a second set of placement angles that are different from each other, a second set of photo images of a security feature of a first unknown document that is placed under the illumination condition, wherein the first unknown document is of the document genre and whose authenticity is to be determined, and wherein the second set of placement angles are mechanically secured, by an automated angle adjustment means, to be equal to values of the first set of estimated angles;
• storing the second set of placement angles along with and in association with the second set of photo images;
• and
• determining the authenticity of the first unknown document by applying the learned model on the second set of images and the second set of placement angles, wherein the applying the model at least involves comparing a piece of descriptive information about the security feature of the first unknown document that is encoded in the learned model as a part of the document's angular responses of the document genre under the illumination condition, with a piece of information about the security feature of the first unknown document extracted from the second set of the photo images and the second set of placement angles, wherein the comparing step produces a first confidence value, and if the first confidence value is below a pre-determined confidence threshold, the first unknown document is determined to be unauthentic, otherwise the first unknown document is determined to be authentic with regard to the security feature of the first unknown document.

A system for authenticating one or more documents, comprising:

• one or more light sources providing an illumination condition, one or more output devices providing intermediate or final outcome of the authenticating documents and prompting end-user instructions for operating the system, a photographing device taking photo images of the one or more documents under the illumination condition, one or more computer processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices, one or more databases, and computer readable program instructions, stored in at least one of the one or more computer-readable, tangible storage devices for execution by at least one of the one or more computer processors via at least one of the one or more memories, to perform operations, the operations comprising:
• capturing, sequentially at a first set of placement angles that are different from each other, a first set of photo images of one or more security features of a known authentic document that is placed under an illumination condition, and wherein the one or more security features, when illuminated, are visible, partially or fully, at the first set of placement angles;
• for each of the first set of photo images, estimating, by using a computer-implemented machine learning algorithm, an angle of the known authentic document being held at the time when the photo image was captured, and aggregating the angle in association with the photo image of the first set of photo images into a first set of estimated angles, and storing the first set of estimated angles along with the first set of photo images;
• training a computer vision algorithm to learn and model a set of document's angular responses of a document genre under the illumination condition based on the first set of photo images and the first set of estimated angles, wherein the training deduces at least one piece of descriptive information about each security feature of the one or more security features based on the first set of photo images and the first set of estimated angles, and produces a learned model encoded with the set of document's angular responses of the document genre under the illumination condition that contains the at least one piece of descriptive information about each security feature of the one or more security features;
• capturing, sequentially at a second set of placement angles that are different from each other a second set of photo images of a security feature of a first unknown document that is placed under the illumination condition, and wherein the first unknown document is of the document genre and whose authenticity is to be determined;
• for each of the second set of photo images, estimating, by using the computer-implemented machine learning algorithm, an angle of the first unknown document being held at the time when the photo image was captured, and aggregating the angle in association with the photo image of the second set of photo images into a second set of estimated angles, and storing the second set of estimated angles along with the second set of photo images;
• and
• determining the authenticity of the first unknown document by applying the learned model on the second set of photo images and the second set of estimated angles, wherein the applying the model at least involves comparing a piece of descriptive information about the security feature of the first unknown document that is encoded in the learned model as a part of the set of document's angular responses of the document genre under the illumination condition, with a piece of information about the security feature of the first unknown document extracted from the second set of the photo images and the second set of estimated angles, wherein the comparing step produces a first confidence value, and if the first confidence value is below a pre-determined confidence threshold, the first unknown document is determined to be unauthentic, otherwise the first unknown document is determined to be authentic with regard to the security feature of the first unknown document.