The present invention provides an orientation adjustment device and an orientation adjustment method of a displayed image. The orientation adjustment method includes the following steps. Step 1 is to capture a first image frame and a second image frame sequentially by an image capturing unit. Step 2 is to obtain a plurality of a first pixel eigenvalues near a first side in the first image frame. Step 3 is to obtain a plurality of a second pixel eigenvalues near the first side in the second image frame. Step 4 is to obtain a difference eigenvalue according to the first pixel eigenvalue and the second pixel eigenvalue. Step 5 is to rotate the image frames output by the image capture unit so that the first side is corresponding to the predetermined display side if the difference eigenvalue is greater than a threshold.

A license plate number recognition method includes: extracting license plate number features of an image to be recognized including a license plate number, through a pre-trained convolutional neural network; extracting an intermediate convolution result during extracting the license plate number features, and extracting a first verification feature and/or a second verification feature according to the intermediate convolution result; verifying whether the license plate number features are correct according to the first and/or second verification features; if correct, outputting a predicted license plate number result according to the license plate number features. During the feature extraction process of the license plate number features, an intermediate feature is extracted as a verification feature to verify whether the extracted license plate number features are correct, and only when the verification is passed, outputting the license plate number result, which reduces the output error rate of the license plate number recognition result.

A license plate number recognition method includes: extracting license plate number features of an image to be recognized including a license plate number, through a pre-trained convolutional neural network; extracting an intermediate convolution result during extracting the license plate number features, and extracting a first verification feature and/or a second verification feature according to the intermediate convolution result; verifying whether the license plate number features are correct according to the first and/or second verification features; if correct, outputting a predicted license plate number result according to the license plate number features. During the feature extraction process of the license plate number features, an intermediate feature is extracted as a verification feature to verify whether the extracted license plate number features are correct, and only when the verification is passed, outputting the license plate number result, which reduces the output error rate of the license plate number recognition result.

Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

Provided is an image reading system that divides, with respect to image data obtained by performing a double sided reading in a state where a booklet is opened, cover sheet image data into two parts corresponding to a pair of cover sheets to arrange the two parts at a front and an end, respectively, and arranges main text image data between the front and the end, and then generates an image file from each of the arranged image data.

An apparatus, method, and computer readable medium for generating and displaying a dynamic language translation overlay that include accessing a frame buffer of the GPU, analyzing, in the frame buffer of the GPU, a frame representing a section of a stream of displayed data that is being displayed by a display device, based on the analyzed frame, identifying a reference patch that includes an instruction to identify an object comprising original text, based on the instruction included in the reference patch, recognizing the original text, generating translated text, generating an overlay comprising an augmentation layer, the augmentation layer including the translated text, and overlaying the overlay, onto the displayed data such that the translated text is viewable while the original text is obscured from view.

Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least improve region of interest detection efficiency by converting pixels of an input receipt image from a first format to a second format, generate a binary representation of the input receipt image based on the converted pixels, the binary representation of the input receipt image corresponding to saturation values for respective ones of the converted pixels, calculate mirror data from the binary representation of the input receipt image, and cluster the binary representation of the input receipt image to identify a first set of candidate regions of interest, the candidate regions of interest characterized by portions of the binary representation of the input receipt image having saturation values that satisfy a threshold value.

Systems and methods for obscuring images and/or text during a screen sharing operation in a video conferencing session are described herein. In some embodiments, a client device detects a screen sharing operation. As part of the screen sharing operation, the client device captures an image of a display. The client device recognizes images and/or text in the image of the display and determines whether any of the images and/or text are restricted. If the images and/or text are determined to be restricted, the client device obscures the images and/or text prior to encoding of the image of the display for transmission.

Methods and systems for providing notifications in an extended reality (XR) environment are described herein. A computing device may provide, to a user and via an XR device, an XR environment. The computing device may detect one or more first locations of one or more display devices. At least one first display device of the one or more display devices may be in a physical environment around the XR device. The computing device may retrieve one or more notifications for display in the XR environment and determine, based on the one or more first locations of the one or more display devices, one or more second locations for the one or more notifications. The computing device may then provide, in the XR environment and at the one or more second locations, the one or more notifications.

A cascade auto-review system for automated classification and annotation of input is provided. An example system is structure adaptive and task oriented and includes a communication module configured to receive the input including images, videos, and metadata. The system further includes a plurality of subsystems. Each subsystem has a series of successive classifier stages configured to detect tags in the input and approve or reject the tags based on the images, the videos, and the metadata. The system further includes a database to store results of the classification and annotation. The results are used to train computer vision and machine learning algorithms.