The present disclosure is directed to systems and methods for strike through detection and, more particularly, to systems and methods for detecting a strike through in an address block of a mailpiece. The method is implemented in a computing device and includes: generating edges of lines within a text block identified through optical character recognition processes; locating text lines within the text block; characterizing the edges within the text lines and outside of the text lines; and grouping identified edges of the characterized edges outside of the text lines into co-linear groups.

An image processing apparatus includes circuitry to set first upper limit values for vertical and horizontal sizes of a character included in image data for erecting direction determination, segment the image data in units of character into a plurality of rectangular areas, determine, in the image data, a plurality of first rectangular areas each of which satisfies the first upper limit values, perform character recognition on characters in the plurality of first rectangular areas in four directions of a +X direction, a −X direction, a +Y direction, and a −Y direction, calculate degrees of certainty of the four directions, determine whether a direction having a highest degree of certainty among the calculated degrees of certainty of the four directions is an erecting direction of the image data to output a determination result, and perform, along the erecting direction, character recognition on characters in a plurality of second rectangular areas of the image data, the plurality of second rectangular areas satisfying second upper limit values for the vertical and horizontal sizes smaller than the first upper limit values for erecting direction determination.

An object is to provide a polygon detection device, a polygon detection method, and a polygon detection program to accurately detect a polygon resembling a reference polygon from an image. The polygon detection device acquires a ratio among lengths of sides of a reference polygon included in an appearance of a predetermined object. The polygon detection device acquires a photographic image of the predetermined object. The polygon detection device detects line segments from the acquired photographic image. The polygon detection device forms at least one polygon based on the detected line segments. The polygon detection device identifies, from the formed polygon, a polygon corresponding to the reference polygon based on a degree of similarity between a ratio among lengths of sides of the formed polygon and the acquired ratio among the lengths of sides of the reference polygon, among from the formed polygon.

An object is to provide a polygon detection device, a polygon detection method, and a polygon detection program to accurately detect a polygon resembling a reference polygon from an image. The polygon detection device acquires a ratio among lengths of sides of a reference polygon included in an appearance of a predetermined object. The polygon detection device acquires a photographic image of the predetermined object. The polygon detection device detects line segments from the acquired photographic image. The polygon detection device forms at least one polygon based on the detected line segments. The polygon detection device identifies, from the formed polygon, a polygon corresponding to the reference polygon based on a degree of similarity between a ratio among lengths of sides of the formed polygon and the acquired ratio among the lengths of sides of the reference polygon, among from the formed polygon.

A training image in accordance with a way a hane occurs, which is found in actual handwriting, is generated. Among line segments constituting a handwritten character in a character image representing the handwritten character, a line segment at which a handwritten hane may occur is detected. Then, by performing processing to add a simulated hane to the end portion of the detected line segment, a training image is generated.

Systems and methods for performing OCR of a series of images depicting text symbols. An example method comprises: receiving a current image of a series of images of an original document, wherein the current image at least partially overlaps with a previous image of the series of images; performing optical symbol recognition (OCR) of the current image to produce an OCR text and a corresponding text layout; identifying, using the OCR text and the corresponding text layout, a plurality of textual artifacts in each of the current image and the previous image, wherein each textual artifact is represented by a sequence of symbols that has a frequency of occurrence within the OCR text falling below a threshold frequency; identifying, in each of the current image and the previous image, a corresponding plurality of base points, wherein each base point is associated with at least one textural artifact of the plurality of textual artifacts; identifying, using coordinates of matching base points in the current image and the previous image, parameters of a coordinate transformation converting coordinates of the previous image into coordinates of the current image; associating, using the coordinate transformation, at least part of the OCR text with a cluster of a plurality of clusters of symbol sequences, wherein the OCR text is produced by processing the current image and wherein the symbol sequences are produced by processing one or more previously received images of the series of images; identifying, for each cluster, a median string representing the cluster of symbol sequences; and producing, using the median string, a resulting OCR text representing at least a portion of the original document.

A method for image processing that includes: obtaining a mask of a connected component (CC) from an image; generating a stroke width transform (SWT) image based on the mask; calculating multiple stroke width parameters for the mask based on the SWT image; identifying a hole in the CC of the mask; calculating a stroke width estimate for the hole based on the stroke width values of pixels in the SWT image surrounding the hole; generating a comparison of the stroke width estimate for the hole with a limit based on the multiple stroke width parameters for the mask; and generating a revised mask by filling the hole in response to the comparison.

Determining a label from an image is disclosed, including: obtaining an image; determining a first portion of the image associated with a special mark; determining a second portion of the image associated with a label based at least in part on the first portion of the image associated with the special mark; and applying character recognition to the second portion of the image associated with the label to determine a value associated with the label.

One embodiment of the present invention sets forth a technique for extracting data from an architectural drawing. The technique includes performing one or more operations via one or more machine learning models to extract a first image of a floorplan area from the architectural drawing. The technique also includes generating a boundary segmentation based on the first image of the floorplan area, wherein the boundary segmentation includes one or more boundary types for one or more portions of the floorplan area.

One embodiment of the present invention sets forth a technique for extracting data from an architectural drawing. The technique includes performing one or more operations via one or more machine learning models to extract a first image of a floorplan area from the architectural drawing. The technique also includes generating a boundary segmentation based on the first image of the floorplan area, wherein the boundary segmentation includes one or more boundary types for one or more portions of the floorplan area.