A detection-based segmentation-free method and system for license plate recognition. An image of a vehicle is initially captured utilizing an image-capturing unit. A license plate region is located in the image of the vehicle. A set of characters can then be detected in the license plate region and a geometry correction performed based on a location of the set of characters detected in the license plate region. An operation for sweeping an OCR across the license plate region can be performed to infer characters with respect to the set of characters and locations of the characters utilizing a hidden Markov model and leveraging anchored digit/character locations.

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.

An intelligent parking management system for residential communities is disclosed that includes a license plate reader; and a server communicatively coupled to the license plate reader over a network. The server includes a memory storing a parking policy and registered license places for one or more residential communities registered with the at least one server; and at least one processor. The processor is operably configured to receive a license plate number, over the network, from the license plate reader; compare the license plate number to a plurality of registered license plate numbers stored in the memory; and communicate, over the network, a parking violation message as a result of determining that the license plate number does not match any one of the plurality of registered license plate numbers to a user such as a resident, a towing company, or administrator.

An example non-transitory computer-readable medium includes instructions executable by a processor to detect boundaries of a representation of a document page in a captured image, model the boundaries of the representation of the document page as nonlinear curves, use the nonlinear curves to transform pixels of the representation of the document page into pixels of a dewarped representation of the document page, and output a dewarped image based on the dewarped representation of the document page.

An image processing apparatus includes a display device configured to display information, a reading device configured to read a document, and one or more controllers configured to function as a unit configured to input an image read by the reading device to a trained model trained based on an image that does not contain text and orientation information about the image that does not contain text, and a unit configured to display information about the image read by the reading device on the display device based on at least an output result from the trained model.

An image outputting device includes a scanning module, a storage module, an identification module, a calibration module and a printing module. The scanning module generates an image by scanning an object. The storage module stores the image. The identification module identifies a layout orientation and a text orientation of the image. The calibration module calibrates the layout orientation and the text orientation of the image according to a relation of an identification result of the identification module and a layout orientation of the printing medium. When the printing module prints the calibrated image on a printing surface of the printing medium and outputs the printing medium with the printing surface facing downwardly, the layout orientation of the printed image matches with the layout orientation of the printing medium, and the text orientation of the printed image is opposite to an medium outputting direction or arranged from proximal to distal.

An example apparatus including memory to store a first image of a document and a second image of the document, and a processor coupled to the memory, wherein the processor is to: perform optical character recognition on the first image to generate a first output dataset; perform optical character recognition on the second image to generate a second output dataset; and compute a transformation matrix based on the first output dataset and the second output dataset, the transformation matrix to align the first image with the second image.

Detection of textual phrases in a non-horizontal orientation at a scene is a target problem. This disclosure relates to a processor implemented method to detect a text from multimedia content captured at a scene. An input original image is processed by a trained model to obtain individual character with bounding box on the original image. The original image is positioned by a gradient to obtain a rotated image if number of detected characters is not equal to number of expected characters on the original image. At least one missing character bounding box on the original image and on the rotated image are estimated to construct a horizontal text image if number of detected characters is not equal to number of expected characters on the rotated image. At least one missing character in the estimated bounding box is detected by at least one text returned from an optical character reader.

Described herein are computerized methods and systems for authentication of a physical document. An image capture device coupled to a mobile device captures a sequence of images of a physical document as at least one of the physical document or the image capture device is rotated, during which the mobile device tracks the physical document throughout the sequence of images, and adjusts operational parameters of the image capture device based upon imaging conditions associated with the physical document. The mobile device selects images from the sequence of images and classifies the physical document using the selected images. The mobile device identifies a region of interest in the physical document using the selected images and the classification. The mobile device reconstructs the region of interest, generates an authentication score for the document using the reconstructed region of interest, and determines whether the physical document is authentic based upon the authentication score.

Systems and methods provide a deployable cloud-agnostic redaction container for performing optical character recognition and redacting information from a document using a cloud-based, guided redaction framework. An example method for document redaction includes receiving a plurality of documents and extracting pages from the plurality of documents. The method then determines, based on a load balancing criterion, a processing order for the pages extracted from the plurality of documents, and performs, based on the processing order, an optical character recognition process and a redaction process on the pages to generate redacted pages. The redacted pages are provided for transmission or storage to a cloud data management platform.