A method for template matching can include iteratively selecting a template set of points to project over a centerline of a candidate symbol; conducting a template matching analysis; assigning a score to each template set; and selecting a template set with a highest assigned score. For example, the score can depend on proximity of the template points to a center and/or boundaries of a principal tracing path of the symbol. Additionally, one or more template sets having a top rank can be selected for a secondary analysis of proximity of the template points to a boundary of a printing of the symbol. The method can further include using the template with the highest score to interpret the candidate symbol.

A method for template matching can include iteratively selecting a template set of points to project over a centerline of a candidate symbol; conducting a template matching analysis; assigning a score to each template set; and selecting a template set with a highest assigned score. For example, the score can depend on proximity of the template points to a center and/or boundaries of a principal tracing path of the symbol. Additionally, one or more template sets having a top rank can be selected for a secondary analysis of proximity of the template points to a boundary of a printing of the symbol. The method can further include using the template with the highest score to interpret the candidate symbol.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an active lighting system. In one aspect, a method includes receiving a first image of the physical document having a first glare signature and a second image of the physical document having a second glare signature that is different from the first glare signature; determining a first glare map of the first image and a second glare map of the second image; comparing the first glare map to the second glare map; and generating the digital image based on the comparison of the first and second glare maps.

A method for template matching can include iteratively selecting a template set of points to project over a centerline of a candidate symbol; conducting a template matching analysis; assigning a score to each template set; and selecting a template set with a highest assigned score. For example, the score can depend on proximity of the template points to a center and/or boundaries of a principal tracing path of the symbol. Additionally, one or more template sets having a top rank can be selected for a secondary analysis of proximity of the template points to a boundary of a printing of the symbol. The method can further include using the template with the highest score to interpret the candidate symbol.

Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

The invention relates to a method for verifying a character to be displayed on a screen, compared to a reference character. The character to be displayed and the reference character each comprise at least several characteristic points. The method comprises: a) determining a barycenter of the characteristic points of the character to be displayed, b) computing geometric coordinates of each characteristic point of the character to be displayed in a coordinate system centered on the determined barycenter, and c) computing a deviation between the character to be displayed and the reference character, as a function of the geometric coordinates computed for the character to be displayed and predetermined geometric coordinates for the reference character. The character to be displayed is considered correct only if the computed deviation is below the predetermined threshold.

An information processing apparatus includes a receiver that receives an input image to be recognized and a processor configured to, by executing a program, align the input image with a template image in such a way as to match a recognition area of the input image and a recognition area defined on the template image, perform a process for recognizing the recognition area of the aligned input image, generate a check image including the template image and the aligned input image, and display the check image and a result of the process for recognizing the recognition area of the aligned input image such that a correspondence between the check image and the result is recognizable.

The present disclosure relates to a system and method for matching a signature extracted from an electronic document (e.g., extracted as .jpg, .gif .png, etc.) with one or more other signatures. The system determines various signature attributes including a number of black pixels in the extracted image, the slopes of four different lines that bound the signature in the extracted image, and a normalized width to height ratio. Two (or more) signatures are considered a match if the attributes match to within specified tolerances. Individual attributes have their own tolerances. These tolerances are adjustable independent of the other tolerances for other attributes.

The invention relates to a method for verifying a character to be displayed on a screen, compared to a reference character. The character to be displayed and the reference character each comprise at least several characteristic points. The method comprises: a) determining a barycenter of the characteristic points of the character to be displayed, b) computing geometric coordinates of each characteristic point of the character to be displayed in a coordinate system centered on the determined barycenter, and c) computing a deviation between the character to be displayed and the reference character, as a function of the geometric coordinates computed for the character to be displayed and predetermined geometric coordinates for the reference character.

The character to be displayed is considered correct only if the computed deviation is below the predetermined threshold.

Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.