Methods, systems, and techniques for processing textual depictions in a computer game screenshot. At least one processor is used to obtain a screenshot of a computer-implemented game, wherein the screenshot includes a game data region. The game data region includes a textual depiction indicative of how a user performed in the game. The at least one processor segments the textual depiction from the screenshot by performing image segmentation on the screenshot and determines alphanumeric characters corresponding to the textual depiction. After determining the alphanumeric characters, the at least one processor outputs the characters to, for example, storage or a display. Image processing in the form of any one or more of aspect ratio transformation, cropping, scaling, binarizing, and blurring may be done prior to segmentation.

A method for assisting manufacturing outsourcing from a manufacturer to a processor of a component is disclosed. The method includes receiving, from a manufacturer terminal of the manufacturer, two-dimensional data expressing the component in a two-dimensional manner. The method includes extracting designation information from the two-dimensional data. The method includes determining outsourcing requirements corresponding to the designation information. The method includes adding, to the two-dimensional data, additional data corresponding to at least part of the outsourcing requirements. The method includes transmitting, to a processor terminal of the processor, the two-dimensional data to which the additional data is added.

A method and an apparatus for retrieving a target are provided. The method may include: obtaining at least one image and a description text of a designated object; extracting image features of the image and text features of the description text by using a pre-trained cross-media feature extraction network; and matching the image features with the text features to determine an image that contains the designated object.

A method for extracting and providing a text color and background color in an image, includes detecting a first area that includes a text in a given image; extracting, from the first area, a representative text color that represents the text and a representative background color that represents a background of the first area; and overlaying a second area that includes a translation result of the text on the given image and applying the representative text color and the representative background color to a text color and a background color of the second area.

Embodiments disclosed herein provide for systems and methods of separating characters associated with ligatures in digitized documents. The systems and methods provide for a ligature detection engine configured to identify the ligatures, and a ligature processing engine configured to identify and remove the glyphs attaching the separate characters forming the ligature.

A process mining system performs process mining using visual logs generated from video streams of worker devices. Specifically, for a given worker device, the process mining system obtains a series of images capturing a screen of a worker device while the worker device processes one or more tasks related to an operation process. The process mining system determines activity labels for a plurality of images. An activity label for an image may indicate an activity performed on the worker device when the image was captured. The activity label is determined by extracting information from pixels of the image and inferring the activity of the worker device from the extracted information. The process mining system generates event logs from the visual logs of worker devices and uses the event logs for process mining.

An approach for enhancing a video stream. The approach processes a video stream and identifies frames comprising text. The approach marks text extraction locations and extracts the text from the frames. The approach determines if a mirroring effect should be applied to the text and applies if applicable, creating enhanced text. The approach inserts the enhanced text and smooths the edges of the inserted enhanced text. The approach merges the frames with the enhanced text into the video stream, creating an enhanced video stream and sends the enhanced video stream to requesting users.

An image processing apparatus includes circuitry to set first upper limit values for vertical and horizontal sizes of a character included in image data for erecting direction determination, segment the image data in units of character into a plurality of rectangular areas, determine, in the image data, a plurality of first rectangular areas each of which satisfies the first upper limit values, perform character recognition on characters in the plurality of first rectangular areas in four directions of a +X direction, a −X direction, a +Y direction, and a −Y direction, calculate degrees of certainty of the four directions, determine whether a direction having a highest degree of certainty among the calculated degrees of certainty of the four directions is an erecting direction of the image data to output a determination result, and perform, along the erecting direction, character recognition on characters in a plurality of second rectangular areas of the image data, the plurality of second rectangular areas satisfying second upper limit values for the vertical and horizontal sizes smaller than the first upper limit values for erecting direction determination.

A method of identifying characters in images extracts features of a detection image including characters. Enhancement processing is performed on the detection image according to the features to obtain an enhanced image. Closed edges of the characters are detected in the enhanced image. First rectangular outlines of the characters are determined according to the closed edges. The first rectangular outlines are corrected to obtain second rectangular outlines. The characters are cropped from the detection image according to the second rectangular outlines. The method identifies characters in images accurately and rapidly.

A method for recognizing handwritten text is disclosed. The method comprises receiving data comprising a sequence of ink points; applying the received data to a neural network-based sequence classifier trained with a Connectionist Temporal Classification (CTC) output layer using forced alignment to generate an output; generating a character hypothesis as a portion of the sequence of ink points; applying the character hypothesis to a character classifier to obtain a first probability corresponding to the probability that the character hypothesis includes the given character; processing the output of the CTC output layer to determine a second probability corresponding to the probability that the given character is observed within the character hypothesis; and combining the first probability and the second probability to obtain a combined probability corresponding to the probability that the character hypothesis includes the given character.