A computer-implemented method is disclosed for segmenting a binarized document. The method includes extracting connected components from the binarized document and discriminating (for at least one of the connected components) whether it is a text component based on a homogeneity level value. The homogeneity level value is representative of the level of homogeneity within the local region of the connected component. The local region includes the connected component and at least one adjacent connected component. The homogeneity level value is based on at least one value representative of at least one image characteristic parameter determined for the connected component and on at least one value representative of the image characteristic parameter of the at least one adjacent connected component.

According to the present disclosure, an image-processing apparatus identifies for each gradation value a connected component of pixels of not less than or not more than the gradation value neighboring and connected to each other in an input image, thereby generating hierarchical structure data of a hierarchical structure including the connected component, extracts based on the hierarchical structure data a connected component satisfying character likelihood as a character-like region, acquires a threshold value of binarization used exclusively for the character-like region, acquires a corrected region where the character-like region is binarized, acquires a background where a gradation value of a pixel included in a region of the input image other than the corrected region is changed to a gradation value for a background, and acquires a binary image data of a binary image composed of the corrected region and the background region.

Examples of a computing device for text recognition is provided. The computing device comprises a processor coupled to a storage medium that stores instructions, which upon execution by the processor, cause the processor to receive a data file comprising an image, identify at least one contour in the image, partition the at least one contour into a plurality of segments, and identify a text character in each segment of the plurality of segments.

A method for managing drawing data including raster data includes: vectorizing, by a computer, the drawing data to generate vector data; generating, by the computer, dimension line data associated with first and second nodes included in the vector data; performing, by the computer, character recognition on a corresponding region in the drawing data corresponding to a close region close to a dimension line represented by the dimension line data; storing, by the computer, a character obtained by the character recognition as a dimension value in association with the dimension line data; and calculating, by the computer, a number of pixels per 1 mm on a drawing represented by the drawing data using the dimension value.

Disclosed herein is a method that improves the performance of handwriting recognition by calculating path scores so as to identify the path with the highest score as the basis for interpreting handwritten characters. Specifically, the method comprises the following steps: detecting connected regions in an input image comprising handwritten characters; determining a plurality of segmentation positions of the input image; obtaining a plurality of recognition results for each segment of each path in the input image, wherein each recognition result represents a character candidate for the segment and each path comprises one or more segments; obtaining a plurality of scores corresponding to the recognition results; calculating scores for each path in the input image based on segment lengths and the scores corresponding to the recognition results; and using the path with the highest score to interpret the handwritten characters in the input 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.

According to the present disclosure, an image-processing apparatus identifies for each gradation value a connected component of pixels of not less than or not more than the gradation value neighboring and connected to each other in an input image, thereby generating hierarchical structure data of a hierarchical structure including the connected component, extracts based on the hierarchical structure data a connected component satisfying character likelihood as a character-like region, acquires a threshold value of binarization used exclusively for the character-like region, acquires a corrected region where the character-like region is binarized, acquires a background where a gradation value of a pixel included in a region of the input image other than the corrected region is changed to a gradation value for a background, and acquires a binary image data of a binary image composed of the corrected region and the background region.

Disclosed herein is a method that improves the performance of handwriting recognition by calculating path scores so as to identify the path with the highest score as the basis for interpreting handwritten characters. Specifically, the method comprises the following steps: detecting connected regions in an input image comprising handwritten characters; determining a plurality of segmentation positions of the input image; obtaining a plurality of recognition results for each segment of each path in the input image, wherein each recognition result represents a character candidate for the segment and each path comprises one or more segments; obtaining a plurality of scores corresponding to the recognition results; calculating scores for each path in the input image based on segment lengths and the scores corresponding to the recognition results; and using the path with the highest score to interpret the handwritten characters in the input image.

Methods, systems, articles of manufacture and apparatus are disclosed to label text on images. An example apparatus includes colorizer circuitry to apply color to text boxes corresponding to optical character recognition (OCR) data associated with an image, OCR manager circuitry to render an OCR text prompt associated with the OCR data, the OCR text prompt to be rendered proximate to respective ones of the text boxes, the OCR text prompt to display a text portion of the OCR data, and edit circuitry to (a) render an interface in response to selection of the OCR text prompt, the interface populated with the text portion of the OCR data, and (b) in response to an overwrite input to the interface, update the text portion of the OCR data in a memory corresponding to the image.

An ink data modification or correction method, and an information processing device and a program for implementing the method are provided, which allow automatic correction of ink data including a spelling error in a handwritten character string. An ink data modification method according to the present disclosure includes determining a modification method of ink data by detecting a spelling error included in a handwritten character string represented by the ink data, and modifying the ink data by manipulating the ink data on the basis of the determined modification method. For example, the determined modification method may be to add a missing character, or to delete a superfluous character, or to correct a typo by replacing an erroneous character with a correct character.