G06V30/162

Systems and methods for mobile automated clearing house enrollment

Systems and methods for mobile enrollment in automated clearing house (ACH) transactions using mobile-captured images of financial documents are provided. Applications running on a mobile device provide for the capture and processing of images of documents needed for enrollment in an ACH transaction, such as a blank check, remittance statement and driver's license. Data from the mobile-captured images that is needed for enrolling in ACH transactions is extracted from the processed images, such as a user's name, address, bank account number and bank routing number. The user can edit the extracted data, select the type of document that is being captured, authorize the creation of an ACH transaction and select an originator of the ACH transaction. The extracted data and originator information is transmitted to a remote server along with the user's authorization so the ACH transaction can be setup between the originator's and receiver's bank accounts.

Systems and methods for mobile image capture and processing of documents

Techniques for processing images of documents captured using a mobile device are provided. The images can include different sides of a document from a mobile device for an authenticated transaction. In an example implementation, a method incudes inspecting the images to detect a feature associated with a first side of the document. In response to determining an image is the first side of the document, a type of content is selected to be analyze on the image of the first side and one or more of regions of interests (ROIs) are identified on the image of the first side that are known to include the selected type of content. A process can include receiving a sub-image of the image of the first side from the preprocessing unit, and performing content detection test on the sub-image.

Systems and methods for mobile image capture and processing of documents

Techniques for processing images of documents captured using a mobile device are provided. The images can include different sides of a document from a mobile device for an authenticated transaction. In an example implementation, a method incudes inspecting the images to detect a feature associated with a first side of the document. In response to determining an image is the first side of the document, a type of content is selected to be analyze on the image of the first side and one or more of regions of interests (ROIs) are identified on the image of the first side that are known to include the selected type of content. A process can include receiving a sub-image of the image of the first side from the preprocessing unit, and performing content detection test on the sub-image.

Optical character recognition quality evaluation and optimization
12014559 · 2024-06-18 · ·

A processor may receive an image and determine a number of foreground pixels in the image. The processor may obtain a result of optical character recognition (OCR) processing performed on the image. The processor may identify at least one bounding box surrounding at least one portion of text in the result and overlay the at least one bounding box on the image to form a masked image. The processor may determine a number of foreground pixels in the masked image and a decrease in the number of foreground pixels in the masked image relative to the number of foreground pixels in the image. Based on the decrease, the processor may modify an aspect of the OCR processing for subsequent image processing.

Optical character recognition quality evaluation and optimization
12014559 · 2024-06-18 · ·

A processor may receive an image and determine a number of foreground pixels in the image. The processor may obtain a result of optical character recognition (OCR) processing performed on the image. The processor may identify at least one bounding box surrounding at least one portion of text in the result and overlay the at least one bounding box on the image to form a masked image. The processor may determine a number of foreground pixels in the masked image and a decrease in the number of foreground pixels in the masked image relative to the number of foreground pixels in the image. Based on the decrease, the processor may modify an aspect of the OCR processing for subsequent image processing.

User terminal device and method for controlling the same

A user terminal device and a method for controlling the same are provided. The user terminal device includes a sensor configured to sense a user touch operation for a binarized text image, a controller configured to generate an indicator pointing out a point where the user touch operation is sensed, when the user touch operation is sensed by the sensor, and a display unit configured to display the binarized text image and the generated indicator.

IMAGE PROCESSING APPARATUS THAT IDENTIFIES CHARACTER PIXEL IN TARGET IMAGE USING FIRST AND SECOND CANDIDATE CHARACTER PIXELS
20190087679 · 2019-03-21 ·

In an image processing apparatus, a controller is configured to perform: acquiring target image data representing a target image including a plurality of pixels; determining a plurality of first candidate character pixels from among the plurality of pixels, determination of the plurality of first candidate character pixels being made for each of the plurality of pixels; setting a plurality of object regions in the target image; determining a plurality of second candidate character pixels from among the plurality of pixels, determination of the plurality of second candidate character pixels being made for each of the plurality of object regions according to a first determination condition; and identifying a character pixel from among the plurality of pixels, the character pixel being included in both the plurality of first candidate character pixels and the plurality of second candidate character pixels.

Method and system for training neural network for entity detection

A system and method for training a neural network is implemented for detecting at least one entity in a document to derive relevant inferences therefrom. The method describes obtaining at least one document. The at least one document is processed, via a detection module, to detect a widget entity. The detected widget entity is classified as active or inactive based on a detected state of the widget entity. The classified widget entity is modified into a corresponding machine-readable widget-entity based on the detected state. The at least one document is processed, via an extraction module, to detect a text entity in near vicinity of the classified widget entity. A training pair comprising the machine-readable widget entity and the corresponding text entity is generated. The neural network is trained using the generated training pair.

INFORMATION PROCESSING SYSTEM, METHOD, AND NON-TRANSITORY COMPUTER-EXECUTABLE MEDIUM
20240257547 · 2024-08-01 ·

An information processing system includes circuitry. The circuitry acquires a captured image by capturing a document. The circuitry performs an analysis process using the captured image. The circuitry selects, for each of at least one setting item of a plurality of setting items relating to image processing to be performed on the captured image, at least one setting value from among configurable setting values as a candidate for a recommended setting. The circuitry performs image processing repeatedly on the captured image while changing setting values of the plurality of setting items with a setting value of the at least one setting item restricted to the at least one setting value selected as the candidate for the recommended setting. The circuitry determines recommended settings for the plurality of setting items relating to image processing to obtain an image suitable for character recognition.

INFORMATION PROCESSING SYSTEM, METHOD, AND NON-TRANSITORY COMPUTER-EXECUTABLE MEDIUM
20240257547 · 2024-08-01 ·

An information processing system includes circuitry. The circuitry acquires a captured image by capturing a document. The circuitry performs an analysis process using the captured image. The circuitry selects, for each of at least one setting item of a plurality of setting items relating to image processing to be performed on the captured image, at least one setting value from among configurable setting values as a candidate for a recommended setting. The circuitry performs image processing repeatedly on the captured image while changing setting values of the plurality of setting items with a setting value of the at least one setting item restricted to the at least one setting value selected as the candidate for the recommended setting. The circuitry determines recommended settings for the plurality of setting items relating to image processing to obtain an image suitable for character recognition.