A text recognition method and apparatus disclosed. The text recognition method includes: obtaining a to-be-detected image; determining a target text detection area in the to-be-detected image, where the target text detection area includes target text in the to-be-detected image, and the target text detection area is a polygonal area including m vertex pairs, m being a positive integer greater than 2; correcting the polygonal area to m1 rectangular areas to obtain a corrected target text detection area; and performing text recognition on the corrected target text detection area to determine the target text, and outputting the target text.

A method of performing character isolation in an optical character recognition process, the method comprising receiving image data representing one or more character columns, determining a number of black pixels in each column of the image data, defining a vertical separation threshold which is a maximum number of black pixels in a column, dividing the columns into different pixel groups and groups of excluded columns by excluding any columns with a number of black pixels below the vertical separation threshold, identifying the pixel group representing the left most character column in the image data, determining whether there are one or two pixel groups representing character columns in the image data and, if it is determined that there are two pixel groups representing character columns, using a predetermined width value for a right most character column in order to identify a right hand boundary of the right most character column.

An image processing device includes: an obtaining unit that obtains image information of a second region to detect an erecting direction of an image formed on a document, the second region being defined in the image in advance according to a criterion different from a criterion for defining a first region in the image, in which character recognition is performed; and an output unit that outputs character information of the first region, the character information being recognized in accordance with the erecting direction of the image obtained from the image information.

A Table Extractor provides various techniques for automatically delimiting and extracting tables from arbitrary documents. In various implementations, the Table extractor also generates functional relationships on those tables that are suitable for generating query responses via any of a variety of natural language processing techniques. In other words, the Table Extractor provides techniques for detecting and representing table information in a way suitable for information extraction. These techniques output relational functions on the table in the form of tuples constructed from automatically identified headers and labels and the relationships between those headers and labels and the contents of one or more cells of the table. These tuples are suitable for correlating natural language questions about a specific piece of information in the table with the rows, columns, and/or cells that contain that information.

Systems and methods for extracting information from a sheet of material to facilitate organization of information from paper, and other physical writing surfaces are provided. An example system includes a sheet of material and a device for scanning the sheet with an optical sensor. The sheet of material includes an indication region. The indication region allows for indictors to be marked corresponding with at least one a corresponding subregion to be extracted. The sheet of material further includes at least one fiducial mark for identifying a boundary of the sheet. The device includes a processor operably coupled to the optical sensor for causing the optical sensor to scan the sheet and detect a boundary thereof using the fiducial marks and further identify a designated subregion of the sheet. Upon identification of the designated subregion, the processor is configured to extract information contained in the designated subregion for organization of information.

Computerized techniques for improved binarization and extraction of information from digital image data are disclosed in accordance with various embodiments. The inventive concepts include: rendering, using a processor of the mobile device, a digital image using a plurality of binarization thresholds to generate a plurality of range-binarized digital images, wherein each rendering of the digital image is generated using a different combination of the plurality of binarization thresholds; identifying, using the processor of the mobile device, one or more range connected components within the plurality of range-binarized digital images; and identifying, using the processor of the mobile device, a plurality of text regions within the digital image based on some or all of the range connected components. Corresponding systems and computer program products are also disclosed.

Systems and methods for merging adjacent word fragments in outputs of optical character recognition (OCR) systems can include a processor obtaining word fragments associated with OCR data generated from an image. Each word fragment can be associated with a respective text line of a plurality of text lines. The at least one processor can determine, for each pair of adjacent word fragments in a text line, a respective normalized horizontal distance between the pair of adjacent word fragments. The processor can identify one or more pairs of adjacent word fragments that are candidates for merging based on the determined normalized horizontal distances. The processor can determine that a pair of adjacent word fragments, among the one or more pairs of adjacent word fragments that are candidates for merging, matches a predefined expression of a plurality of predefined expressions, and merge that pair of adjacent word fragments into a single word.

Systems and methods for assigning word fragments to lines of text in optical character recognition (OCR) extracted data can include at least one processor obtaining a plurality of word fragments from OCR generated data associated with an image. The at least one processor can determine vertical coordinates of each of the word fragments in the image. The at least one processor can cluster the plurality of word fragments into one or more clusters of word fragments based on the vertical coordinates of the plurality of word fragments. The at least one processor can assign each word fragment of a respective cluster to a corresponding text line based on the clustering.

A binary image of an input image is generated, and a character region within the binary image and a region surrounding each character are acquired as character segmentation rectangle information. A thinning process is executed on a region within the binary image which is identified based on the character segmentation rectangle information to acquire a thinned image. An edge detected image of the region identified based on the character segmentation rectangle information is acquired. Whether each character identified based on the character segmentation rectangle information is a character to be separated from a background by the binarization process or not is determined based on a result of a logical AND of the thinned image and the edge detected image.

In an image analyzing apparatus, a controller in a first analyzing process performs: sequentially identifying line pixel groups from a first side in a first direction; and determining whether a first-type pixel not contiguous to a first subject group constituted by at least one first-type pixel contiguous to each other in a second direction is present in a first region surrounding the first subject group, using first relevant information relating to each line pixel group located on the first side. In a second analyzing process, the controller performs: sequentially identifying the line pixel groups from a second side in the first direction; and determining whether the first-type pixel not contiguous to the first subject group is present in a second region surrounding the first subject group, using second relevant information relating to each line pixel group located on a second side.