In several embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The techniques include detecting medical documents and/or documents relevant to an insurance claim by defining candidate edge points based on the captured image data and defining four sides of a tetragon based on at least some of the candidate edge points. In the case of an insurance claim process, the techniques also include determining whether the document is relevant to an insurance claim; and in response to determining the document is relevant to the insurance claim, submitting the image data, information extracted from the image data, or both to a remote server for claims processing. The image capture and processing techniques further facilitate processing of medical documents and/or insurance claims with a plurality of additional features that may be used individually or in combination in various embodiments.

An information processing apparatus according to an embodiment includes a memory and one or more processors configured to function as a map acquisition unit, a filtering unit and a converting unit. The map acquisition unit acquires a polar coordinate map specifying first occupancy of a target in a polar coordinate space. The filtering unit performs filtering on the polar coordinate map using filtering windows of sizes corresponding to a distance from a reference position. The converting unit converts the filtered polar coordinate map into a rectangular coordinate space.

System that facilitates rapid onboarding of an autonomous (cashier-less) store by capturing images of items in the store's catalog from different angles, with varying backgrounds and lighting conditions, and that automatically builds a classifier training dataset from these images. The system may have cameras in different positions, lights supporting variable illumination, and monitor screens that generate different background colors. It may have an input device such as a barcode reader, and an operator terminal that prompts operators to place items into the imaging system in the necessary orientations. Once an item is placed in the imaging system, a fully automated process may generate a sequence of background colors, a sequence of lighting conditions, and may capture and process images from all of the cameras to create training images. Training images for an item may be generated in seconds, compared to many minutes per item using manual image capture and processing.

A method of generating a patient-specific prosthetic includes receiving anatomic imaging data representative of a portion of a patient's anatomy. A first digital representation of the anatomic imaging data is defined. The first digital representation of the anatomic imaging data is modified. A second digital representation of the portion of the patient's anatomy is defined based on the modifying of the first digital representation of the anatomic imaging data. A patient-specific prosthetic template of the portion of the patient's anatomy is generated based at least in part on the second digital representation of the anatomic imaging data.

One example method involves operations for receiving a request to transform an input image into a target image. Operations further include providing the input image to a machine learning model trained to adapt images. Training the machine learning model includes accessing training data having a source domain of images and a target domain of images with a target style. Training further includes using a pre-trained generative model to generate an adapted source domain of adapted images having the target style. The adapted source domain is generated by determining a rate of change for parameters of the target style, generating weighted parameters by applying a weight to each of the parameters based on their respective rate of change, and applying the weighted parameters to the source domain. Additionally, operations include using the machine learning model to generate the target image by modifying parameters of the input image using the target style.

An information processing apparatus, connectable with an image output apparatus, includes circuitry to receive image data of an image from a memory, acquire information of an image placement region of the image output apparatus, the image placement region being variable depending on a type of the image output apparatus, and the image is to be output on the image placement region of the image output apparatus, generate an output image by placing the image within the image placement region based on the image data of the image to be output, and the image placement region of the image output apparatus, and transmit the generated output image to the image output apparatus.

Signal processing devices and methods estimate transforms between signals using a least squares technique. From a seed set of transform candidates, a direct least squares method applies a seed transform candidate to a reference signal and then measures correlation between the transformed reference signal and a suspect signal. For each candidate, update coordinates of reference signal features are identified in the suspect signal and provided as input to a least squares method to compute an update to the transform candidate. The method iterates so long as the update of the transform provides a better correlation. At the end of the process, the method identifies a transform or set of top transforms based on a further analysis of correlation, as well as other results.

Aspects described herein provide a computer-implemented method and system for generating topographic map data at different scales. More specifically, the topographic map data is reduced from large scale to small scale, wherein the scale of the vector features is reduced according to their geometry, feature type and attributes. In order to quickly and easily output digital maps at different scales so that a user may quickly zoom in and out of a map, different zoom levels are produced for different scales, each zoom level containing a variable amount of detail according to its scale, with larger scale zoom levels generally containing more detail than small scale zoom levels. Each zoom level is made up of one or more vector tiles representative of a geographic area, wherein the vector tiles may contain one or more vector features that are representative of objects within that geographic area, and other information related to that geographical area.

Systems and methods for cropping media for a particular orientation using a computing device are described. A method may first comprise receiving by a video preprocessor of the device, a first frame of media in a first orientation. A first region comprising a first feature within the first frame may be identified, by an image analyzer. A cropping calculator of the device may generate a score for the first region based on a characteristic of the first feature and determine that the score for the first region exceeds a threshold. An image processor of the device may then crop the first frame of the video, responsive to the determination that the score for the first region exceeds the threshold, to include the first region within a predetermined display area comprising a subset of the first frame in a second orientation.

A display device includes a display unit which includes a plurality of pixels and a display area having a corner of a non-right angular shape and a signal controller which controls the display unit to display an image through the plurality of pixels based on an input image signal, detects a specific pattern in a partial region, of the image, corresponding to a partial area, of the display unit, including the corner of the non-right angular shape, and controls the display unit to display a partial image corresponding to the partial region of the image in the display area without crossing the corner, according to a position of the specific pattern in the partial region.