Examples of present disclosure relate to method and system to extract text from engineering drawing for performing accurate OCR. Initially, for the extraction, image of engineering drawing is received with a plurality of components. Each of the plurality of components in the image is classified to be one of a textual component and a non-textual component. At least one word element for textual components from the plurality of components is identified based on segmentation of the plurality of components. The segmentation is performed by drawing a plurality of horizontal edge projections of a predefined length for each of the textual components. Further, the textual components is identified to be associated with the at least one word element when horizontal edge projection of each of the textual components overlaps with adjacent textual component. The at least one word element is provided as extracted text for performing OCR on the engineering drawing.

A method for processing camera images in real-time is disclosed. The user starts a process that generates a feed from a mobile device of camera images of a document. An image from the feed is obtained and set as the current image. One or more of a plurality of aspects regarding the image are computed and tested against a threshold. If the aspect fails to satisfy the threshold, then the user is prompted to change the move the mobile device. Once the aspects satisfy their respective thresholds, the camera feed is stopped, the last image is saved, and character recognition of the last image is performed and displayed to the user.

An apparatus for character recognition executes a first process for acquiring first image data which is an image in which string data containing one or more characters is drawn at a first magnification through a drawing process that outputs image data acquired by drawing characters at a display magnification, executes a second process for acquiring second image data which is an image in which the string data is drawn at a second magnification larger than the first magnification through the drawing process, executes a third process for acquiring a recognition result including a character code of each of the characters in the string data drawn in the second image data through a character recognition process, and executes a fourth process for adjusting a newline position of the recognition result acquired from the second image data by using a newline position of the string data drawn in the first image data.

Examples of present disclosure relate to method and system to extract text from engineering drawing for performing accurate OCR. Initially, for the extraction, image of engineering drawing is received with a plurality of components. Each of the plurality of components in the image is classified to be one of a textual component and a non-textual component. At least one word element for textual components from the plurality of components is identified based on segmentation of the plurality of components. The segmentation is performed by drawing a plurality of horizontal edge projections of a predefined length for each of the textual components. Further, the textual components is identified to be associated with the at least one word element when horizontal edge projection of each of the textual components overlaps with adjacent textual component. The at least one word element is provided as extracted text for performing OCR on the engineering drawing.

An image processing apparatus including: a processor; and memory storing computer-readable instructions therein, the computer-readable instructions, when executed by the processor, causing the image processing apparatus to perform: acquiring target image data configured by a plurality of pixels and representing a target image including a character; acquiring a character code corresponding to the character in the target image; acquiring an index value relating to a number of a plurality of character pixels configuring the character in the target image by using the character code corresponding to the character in the target image; determining a first extraction condition by using the index value; and extracting the plurality of character pixels satisfying the first extraction condition from the plurality of pixels in the target image.

A computer implemented method for generating a region of interest on a digital image of a sidewall of a tyre, the sidewall having one or more embossed and/or engraved markings, is provided. The method comprises generating a histogram of oriented gradients feature map of the digital image, inputting the histogram of oriented gradients feature map into a trained convolutional neural network, wherein said trained convolutional neural network is configured to output a first probability based on the input histogram of oriented gradients feature map that a region of pixels of the digital image contains the embossed and/or engraved markings, and if the first probability is at or above a first predetermined threshold, accepting said region of pixels as said region of interest.

The present disclosure involves systems, software, and computer implemented methods for identifying document generators by color footprints. An example method includes receiving a request to classify a first document. A document footprint is generated for the first document that includes a set of most frequently occurring color values in the first document. A classification for the first document is determined as either generated-by-the-document-generator or not-generated-by-the-document-generator based on comparing the document footprint for the first document to a document generator footprint. The document generator footprint includes a set of common color values that occur in a set of training documents for the document generator. The classification for the first document is provided in response to the request.

Various examples are directed to methods and systems for object recognition in an image. A computer vision system may receive a patch comprising a plurality of pixels arranged in a grid. The computer vision system may determine a plurality of columns and a plurality of rows in the patch. The plurality of columns may be based at least in part on a column target sum and the plurality of rows may be based at least in part on a row target sum.

A system and method for robust estimation of state parameters from internal readings in a sequence of images are provided. Various techniques can be implemented to address observation noise and/or underlying process noise to stabilize the readings.

A supplemental device for attachment to an injection device, the supplemental device comprising: an imaging arrangement configured to capture an image of one or more numbers present on a moveable component of the injection device; and a processor arrangement configured to run a first algorithm to: receive data representing an image; determine the position of at least one number in the image by determining the boundaries of each visible number; select one of the visible numbers to be identified; perform a pattern matching process to identify the value of the selected number; and determine a dose dialled into the injection device using the determined position of the selected one of the at least one visible number in the image.