Disclosed herein is a software technology for facilitating an interactive conversational session between a user (e.g., a client, a patient, etc.) and a digital conversational character. For instance, in one aspect, the disclosed process may involve two primary phases: (1) an authoring phase that involves a first user accessing a content authoring tool to create a given type of visual conversation application that facilitates interactions between a second user and a digital conversational character in an interactive conversational session, and (2) a rendering phase that involves the second user accessing the created visual conversation application to interact with the digital conversational character in an interactive conversational session.

The present subject matter is related in general to the field of image processing, disclosing method and system for evaluating an image quality for Optical Character Recognition (OCR) Image evaluation system receives image comprising optical character data. The image evaluation system determines image parameter value for each of one or more image parameters of the image. The image parameter value for each of the one or more image parameters is determined for plurality of binary image segments identified in the image. The image evaluation system determines suitability value and impact value of the image, based on the image parameter value for each of the image parameters determined for the image. The image evaluation system determines quality score for the image, based on the suitability value and the impact value. The image is transmitted for processing before the OCR, upon determining the quality score to be above overall pre-defined threshold value.

A computer device segments a first sample region to obtain a candidate image region set that includes a plurality of candidate image regions, For each of the candidate image regions, the device obtains a first relationship degree corresponding to each candidate image region and obtains a second relationship degree corresponding to the candidate image region. The device obtains a relationship degree change value based on the first relationship degree and the second relationship degree. The device selects, from the plurality of candidate image regions, a first candidate image region as a target image region in accordance with a determination that the first candidate image region satisfies a condition in the relationship degree change value. The device performs model training based on the target image region to obtain a target detection model.

Systems and methods for performing OCR of an image depicting text symbols and imaging a document having a plurality of planar regions are disclosed. An example method comprises: receiving a first image of a document having a plurality of planar regions and one or more second images of the document; identifying a plurality of coordinate transformations corresponding to each of the planar regions of the first image of the document; identifying, using the plurality of coordinate transformations, a cluster of symbol sequences of the text in the first image and in the one or more second images; and producing a resulting OCR text comprising a median symbol sequence for the cluster of symbol sequences.

Systems and methods herein describe receiving an image via an image capture device, using a machine learning model, generating an image augmentation decision, accessing an augmentation reality content item, associating the generated image augmentation decision with the augmentation reality content item, modifying the received image using the augmentation reality content item and the associated image augmentation decision, and causing presentation of the modified image on a graphical user interface of a computing device.

Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images.

An electronic device and a method for document segmentation are provided. The method includes: obtaining a first feature map and a second feature map corresponding to an original document; performing a first upsampling on the second feature map to generate a third feature map; concatenating the first feature map and the third feature map to generate a fourth feature map; inputting the fourth feature map to a first inverted residual block (IRB) and performing a first atrous convolution operation based on a first dilation rate to generate a fifth feature map; inputting the fourth feature map to a second IRB and performing a second atrous convolution operation based on a second dilation rate to generate a sixth feature map; concatenating the fifth feature map and the sixth feature map to generate a seventh feature map; performing a convolution operation on the seventh feature map to generate a segmented document.

An information processing apparatus includes a receiving unit and a controller. The receiving unit receives an extraction-area image indicating an extraction area. The extraction area includes a fill-in area in which a writer handwrites information. When an instruction to correct a recognition result for the information written in the fill-in area indicated by the extraction-area image is given, the controller causes a display unit to display a different extraction-area image similar to the extraction-area image.

Techniques for binarization and extraction of information from image data are disclosed. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; and extracting data from some or all of the plurality of binarized images. The extracted data includes connected components that overlap and/or are obscured by unique background. Corresponding systems and computer program products are disclosed.

The present disclosure relates to methods of analyzing works of art for purposes of authentication or attribution. Such methods may be implemented by receiving digital image data associated with a work of art, identifying a plurality of artist's strokes formed along a surface of the work of art, segmenting the plurality of strokes into a plurality of individual strokes, analyzing the plurality of individual strokes to determine stroke characteristics, and comparing the stroke characteristics to stroke characteristics derived from one or more computational models based on known works of art.