A method, system, and apparatus for license plate relighting comprises collecting an image of a license plate, performing license plate recognition on the image of the license plate; calculating a confidence metric for the license plate recognition; and performing a shadow detection and relighting method if the confidence metric is below a predetermined threshold, comprising identifying a shaded region of said license plate, determining if the shaded region is actually shaded, and relighting the actually shaded region.

Embodiments disclosed herein provide for systems and methods of separating characters associated with ligatures in digitized documents. The systems and methods provide for a ligature detection engine configured to identify the ligatures, and a ligature processing engine configured to identify and remove the glyphs attaching the separate characters forming the ligature.

In some implementations, a device may process an image to identify one or more first lines of the image that extend in a first dimension. The device may process the image to identify one or more second lines of the image that extend in a second dimension orthogonal to the first dimension. The device may identify portions of the one or more first lines that do not intersect with the one or more second lines. The device may process the image to obtain a version of the image in which the portions of the one or more first lines are removed.

A handwritten content removing method and device and a storage medium. The handwritten content removing method comprises: acquiring an input image of a text page to be processed, the input image comprising a handwritten region, which comprises a handwritten content (S10); identifying the input image so as to determine the handwritten content in the handwritten region (S11); and removing the handwritten content in the input image so as to obtain an output image (S12).

An image processing system according to the present embodiment acquires a processing target image read from an original that is handwritten and specifies one or more handwritten areas included in the acquired processing target image. In addition, for each specified handwritten area, the present image processing system extracts from the processing target image a handwritten character image and a handwritten area image indicating an approximate shape of a handwritten character. Furthermore, for a handwritten area including a plurality of lines of handwriting among the specified one or more handwritten areas, a line boundary of handwritten characters is determined from a frequency of pixels indicating a handwritten area in a line direction of the handwritten area image, and a corresponding handwritten area is separated into each line.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for implementing content-aware filters to autonomously remove scan marks from digital documents. In particular implementations, the disclosed systems utilize a set of targeted scan mark models in a scan mark removal pipeline. For example, each scan mark model includes a corresponding content-aware filter configured to identify document regions that match a designated class of scan marks to filter. Examples of scan mark models include staple scan mark models, punch hole scan mark models, and page turn scan mark models. In certain embodiments, the disclosed systems then use the scan mark models to generate mark-specific masks based on document input features. Additionally, in some embodiments, the disclosed systems combine the mark-specific masks into a final segmentation mask and apply the final segmentation mask to the digital document for correcting the identified regions with scan marks.

To make it possible to extract character information with a high accuracy even from a document image obtained by reading a document in which a logo mark or the like overlaps a character portion. By performing binarization processing for a document image obtained by reading a document, a binary image including first pixels representing a color darker than a reference and second pixels representing a color paler than the reference is generated. Then, by changing the pixel among the first pixels included in the generated binary image, whose corresponding pixel's color in the document image is different from a color of a character object within the document, to the second pixel, a binary image in which a background object that overlaps the character object in the document image is removed is generated.

An information processing apparatus includes a processor configured to acquire, from a read image, a predetermined item, and a value corresponding to the item, the read image being obtained by reading a document and being subjected, prior to acquisition of the item and the value, to preprocessing and character recognition. Further, the processor is configured to, in response to not successfully acquiring at least one of the item and the value, change a setting on the preprocessing or a setting on the character recognition in accordance with the acquisition or non-acquisition state of the item and the value, and then perform the preprocessing or the character recognition. In response to not successfully acquiring at least one of the item and the value, the processor is further configured to identify where the item and the value are located.

Vehicles and other items often have corresponding documentation, such as registration cards, that includes a significant amount of informative textual information that can be used in identifying the item. Traditional OCR may be unsuccessful when dealing with non-cooperative images. Accordingly, features such as dewarping, text alignment, and line identification and removal may aid in OCR of non-cooperative images. Dewarping involves determining curvature of a document depicted in an image and processing the image to dewarp the image of the document to make it more accurately conform to the ideal of a cooperative image. Text alignment involves determining an actual alignment of depicted text, even when the depicted text is not aligned with depicted visual cues. Line identification and removal involves identifying portions of the image that depict lines and removing those lines prior to OCR processing of the image.

An information processing apparatus includes a processor configured to acquire, from a read image, a predetermined item, and a value corresponding to the item, the read image being obtained by reading a document and being subjected, prior to acquisition of the item and the value, to preprocessing and character recognition. Further, the processor is configured to, in response to not successfully acquiring at least one of the item and the value, change a setting on the preprocessing or a setting on the character recognition in accordance with the acquisition or non-acquisition state of the item and the value, and then perform the preprocessing or the character recognition.