A character segmentation method and apparatus, and a computer-readable storage medium. The character segmentation method comprises: converting a character area image into a grayscale image (step 101); converting the grayscale image into an edge binary image by using an edge detection algorithm (step 102); acquiring character box segmentation blocks from the edge binary image by using a projection method (step 103); and determining a target character area from the character box segmentation blocks by using a contour detection algorithm, and performing character segmentation on the character area image according to the target character area (step 104). Another character segmentation method comprises: converting a character area image into a grayscale image (step 701); performing clustering analysis on the grayscale image by using a fuzzy C-means clustering algorithm, and executing binarization processing on the grayscale image according to a clustering analysis result (step 702); acquiring character positioning blocks from a binary image by using a projection method (step 703); and performing character segmentation on the character area image according to position information of the character positioning blocks (step 704). By using the methods and apparatuses, character segmentation can be performed on a relatively low quality image.

A method and system is provided for determining the denomination and related data for a currency item using a personal computing device, such as a mobile phone. The device includes or is connected to an image capture device that is preferably a digital video camera. At least one image of a target currency item is captured then processed for image quality. A further processing of the image includes a coordinate mapping. A comparison is made between individual pixels of the processed image based on the assigned coordinate mapping with a database of reference currency images to determine the currency denomination. Additional processing of the currency image provides the date and other data regarding the target currency item. A market value for the target currency item is identified by reference to a valuation database using the data determined for the currency item.

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 apparatus includes a control system that defines a test part having multiple features of multiple feature types. The control system controls an additive manufacturing (AM) machine to print multiple copies of the test part, with each copy being printed according to a respective set of values used as printing parameters. A measurement system obtains a computed tomography (CT) image of each of the copies of the test part. An analysis system, for each of the plurality of feature types, analyzes the CT images to identify a selected set of values for the printing parameters. The analysis system identifies a portion of the CT image related to a first feature and assesses its density based on an average grayscale value. The AM machine is then controlled to print production parts according to, for each feature type of the production parts, the selected set of values for the printing parameters.

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.

Provided is an information processing apparatus that extracts one or more candidate character strings to be a candidate of an item value corresponding to a predetermined item, from among multiple character strings included in a document image to be processed. The information processing apparatus first obtains information indicating an attribute group of a preset extraction target, then identifies an attribute group to which each of the multiple character strings belongs from among predetermined multiple attribute groups based on a feature vector corresponding to each of the multiple character strings included in the document image to be processed, and subsequently extracts the character string whose identified attribute group is the same as the attribute group of the extraction target from among the multiple character strings included in the document image to be processed, as the candidate character string.

A system for file image processing and extraction of content from images is provided. The system comprises a computer and an application. When executed on the computer, the application receives a source document containing areas of interest and normalizes the document to align with a stored template image. The application also applies metadata associated with the template image to the areas of interest to identify data fields in the normalized document and extracts data from the identified data fields. The application also processes the extracted data using at least character recognition systems and produces a static structure using at least the identified data fields, the fields containing the processed data. The areas of interest comprise portions of the source document containing text needed to create and populate fields suggested by the stored template image. Normalizing the source document comprises at least one of flipping, rotating, expanding, and shrinking the document.

An apparatus includes a control system that defines a test part having multiple features of multiple feature types. The control system controls an additive manufacturing (AM) machine to print multiple copies of the test part, with each copy being printed according to a respective set of values used as printing parameters. A measurement system obtains a computed tomography (CT) image of each of the copies of the test part. An analysis system, for each of the plurality of feature types, analyzes the CT images to identify a selected set of values for the printing parameters. The analysis system identifies a portion of the CT image related to a first feature and assesses its density based on an average grayscale value. The AM machine is then controlled to print production parts according to, for each feature type of the production parts, the selected set of values for the printing parameters.

A method and system is provided for determining the denomination and related data for a currency item using a personal computing device, such as a mobile phone. The device includes or is connected to an image capture device that is preferably a digital video camera. At least one image of a target currency item is captured then processed for image quality. A further processing of the image includes a coordinate mapping. A comparison is made between individual pixels of the processed image based on the assigned coordinate mapping with a database of reference currency images to determine the currency denomination. Additional processing of the currency image provides the date and other data regarding the target currency item. A market value for the target currency item is identified by reference to a valuation database using the data determined for the currency item.

An image object labeling method and system are disclosed. The method is executed by a processor coupled to a memory and includes providing an image file; detecting at least one first object on the image file and generating at least one graphic block and attribute thereof; performing a binarization process to present a first graphic feature on a region containing the graphic block in the image file and a second graphic feature on the rest region; combining the results of detecting and the binarization process, and filtering the image file through several gradually reduced masks to show several separated graphic components until number of the separated graphic components and the at least one graphic block are the same; and assigning a label to the separated graphic components according to the attribute, alternatively, outputting a message, receiving a command for adjusting the graphic block and attribute thereof, as the labels.