The present invention discloses a system for automated vehicles license plates characters segmentation and recognition comprising an imaging processor connected to at least one image grabber module or camera. The image grabber module captures images of the vehicles and forwards it to said connected imaging processor and the imaging processor segments and recognizes the vehicles license plates character region including the region with deformed license plates characters in the captured vehicle images by involving binarization of maximally stable external regions corresponding to probable license plate region in the captured vehicle images.

A system for optimizing images may include a camera sensor configured to capture a first image, and an image pipeline configured to receive the first image from the camera sensor. The image pipeline may identify a plurality of regions in the first image, and generate a second image from the plurality of regions in the first image. The second image may be smaller than the first image such that the second image can be more efficiently processed by a neural network. The system may also include a neural network configured to receive the second image from the image pipeline and train the neural network using the second image or process the second image using the neural network.

A device may receive document image data that includes an image of a document to be digitized. The device may detect, from the document image data, a table of information that is depicted in the image. The device may determine a data extraction score associated with a table image, wherein the data extraction score is associated with using a data conversion technique to convert the table image to digitized table data. The device may perform, based on the data extraction score not satisfying a threshold, a morphological operation on the table image to generate an enhanced table image that corresponds to an enhanced table of information associated with the table of information. The device may process, using the data conversion technique, the enhanced table image to extract the information from the enhanced table. The device may perform an action associated with the extracted information.

A material data collection system allows capturing of material data. For example, the material data collection system may include digital image data for materials. The material data collection system may ensure that captured digital image data is properly aligned, so that material data may be easily recalled for later use, while maintaining the proper alignment for the captured digital image. The material data collection system may include using a capture guide, to provide cues on how to orient a mobile device used with the material data collection system.

A material data collection system allows capturing of material data. For example, the material data collection system may include digital image data for materials. The material data collection system may ensure that captured digital image data is properly aligned, so that material data may be easily recalled for later use, while maintaining the proper alignment for the captured digital image. The material data collection system may include using a capture guide, to provide cues on how to orient a mobile device used with the material data collection system.

A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.

Generating a table with at least one skewed row, skewed column, shifted row, or shifted column is described. A table generation system generates a table that includes cells arranged in a grid comprising rows and columns, and defines each cell using a grid address, a grid span, a grid angle, a string skew value, a string shift value, and a shift indicator for the cell. The table generation system may receive input modifying a grid angle for at least one row or column and generate a modified table by skewing cells included in the at least one row or column by the grid angle. The table generation system may additionally or alternatively receive input shifting at least one row or column by a string shift value and modify the display of the table by shifting the at least one row or column according to the string shift value.

Generating a table with at least one skewed row, skewed column, shifted row, or shifted column is described. A table generation system generates a table that includes cells arranged in a grid comprising rows and columns, and defines each cell using a grid address, a grid span, a grid angle, a string skew value, a string shift value, and a shift indicator for the cell. The table generation system may receive input modifying a grid angle for at least one row or column and generate a modified table by skewing cells included in the at least one row or column by the grid angle. The table generation system may additionally or alternatively receive input shifting at least one row or column by a string shift value and modify the display of the table by shifting the at least one row or column according to the string shift value.

Techniques for desirably translating a document image to an editable electronic textual document are presented. Utilizing respective applications, a document processing management component (DPMC) can convert the document image to a grayscale document image, remove noise from such image, rotate such image to reduce or eliminate any skewing of such image, and perform character recognition on the rotated grayscale document image to extract the textual information from such document to generate an electronic textual document. DPMC can associate a document identifier with the electronic textual document, and such document and document identifier can be stored in a data store. When such document is related to a device or other item, a code or textual string can be associated with the device or item, wherein a communication device can scan the code or textual string. In response, DPMC can retrieve such document, or information relating thereto, from the data store.

A method and system for generating synthetic images for use in a database is described. The database is used for delineation of features in real images, the method comprising the steps of: providing a delineated image acquired using a first scanner, defining a model related to the generation of synthetic images using a second scanner, processing the delineated image using the model to generate a synthetic image, mapping contours to the synthetic image to form a synthetic image-contour pair; repeating providing, defining and processing steps to generate a plurality of synthetic images and contour pairs for the database; using said database of synthetic images and contour pairs to optimise a contouring algorithm, where the optimised algorithm generates contours for the real images of the same type as the synthetic images; processing one or more further real images to contour and delineate features on the further real image using the algorithm.