Techniques and systems for recognizing characters on a circuit board are discussed herein. For example, a digital image of a character on a circuit board can be obtained. The digital image can be processed with a gradient, structural, and concavity algorithm. The processing can include identifying a gradient feature based on a stroke shape, identifying a structural feature based on a stroke trajectory, identifying a concavity feature based on a stroke relationship, and so on. The character can be classified based on the gradient feature, the structural feature, and/or the concavity feature. The classifying can be performed using a k-nearest neighbor classifier algorithm and/or a distance metric.

The present method includes: transforming a gray matrix of a natural scene image into a local contrast matrix, and performing a binary division to the obtained local contrast matrix using an Otsu method, thereby obtaining a binary matrix; performing a connected domain analysis to the binary matrix, eliminating non-character connected domains to obtain character connected domains; performing a detection of elements of a special structure of a formula to the character connected domains using a correlation coefficient method, and separately annotating all the detected elements of the special structure: dividing rows of the binary matrix by means of horizontal projection; recognizing each character connected domain by means of a convolutional neural network; defining an output sequence, and outputting the results of recognition in a corresponding sequence according to a typesetting format of LaTeX.

An image processing system adapted to binarize images is provided. The system includes a component detector configured to receive an image and detect a plurality of components in the image. The components are detected based on a content of the image. Further, the system includes a logical splitter configured to split the image into a plurality of windows based on the plurality of components. The plurality of windows is of varying window sizes. In addition, the system includes a threshold detector configured to determine a binarization threshold value for each window. The system also includes a binarization module configured to binarize a plurality of component images based on the corresponding binarization threshold values of the component. Furthermore, the system includes a logical integrator configured to generate a binarized image. The binarized image is a logically integrated image comprising the plurality of component images.

In one aspect, a method of optical character recognition of digital character objects in digital images includes the step of obtaining a digital image. The digital images include rendering of a first object in the digital image. The first object comprises a set of sub-objects and a set of relationships between the sub-object. The method includes the step of generating a definition of a first object by defining an object outline for the first object as a set of sub-objects; defining a sub-object outline for each sub-object as a set of lines and curves; and defining each relationship between each set of connected sub-objects in terms of one or more intersections or one or more corners.

Systems and methods for recognition of unreadable characters on printed circuit boards. In some embodiments, a method for recognizing characters can be utilized for recognition of damaged characters on a printed circuit board. The method can include obtaining a digital image for each of a plurality of characters on the printed circuit board. The method can further include dividing each digital image into an array of regions. The method can further include generating a data structure from the arrays of the digital images. The data structure can include gradient features based on stroke shapes on small distances, structural features based on stroke trajectories on extended distances, and concavity features based on stroke relationships.

This disclosure relates generally to image processing, and more particularly to system and method for detecting and annotating bold text in an image document. In one embodiment, a method is provided for annotating bold text in an image document. The method comprises receiving the image document, processing the image document to derive a digitized textual image, detecting one or more regions of bold text within the digitized textual image using an adaptive edge rounding filter, and annotating the one or more regions of bold text within the image document.

Complete removal of an underline which intersects a character may cause problems in a subsequent character recognition or conversion process, when parts of the character which coincided with the underline are also removed. To help reduce the problems, parts of underline may be removed from an image while parts of the character that coincide with the underline are maintained in the image. Areas where the character coincides with the underline are defined from a reduced version of the underline. When the underline is removed, the areas where the character coincide with the underline are maintained in a second image. The second image may then be subjected to a character recognition or conversion process with potentially fewer problems.

In an image processing apparatus, a controller is configured to perform: acquiring target image data representing a target image including a plurality of pixels; determining a plurality of first candidate character pixels from among the plurality of pixels, determination of the plurality of first candidate character pixels being made for each of the plurality of pixels; setting a plurality of object regions in the target image; determining a plurality of second candidate character pixels from among the plurality of pixels, determination of the plurality of second candidate character pixels being made for each of the plurality of object regions according to a first determination condition; and identifying a character pixel from among the plurality of pixels, the character pixel being included in both the plurality of first candidate character pixels and the plurality of second candidate character pixels.

A work assistance system includes a drawing, a work record table, a handwriting display determination unit, a display control unit, and input means. The drawing includes parts and handwritings. The work record table stores the handwriting for the part as the work record. The handwriting display determination unit determines, as the writing candidates, the handwritings not associated with the parts based on the work record table. The display control unit displays the writing candidates and the parts via the input means in a selectable manner on a data display unit of a terminal of a user.

This disclosure relates generally to image processing, and more particularly to system and method for detecting and annotating bold text in an image document. In one embodiment, a method is provided for annotating bold text in an image document. The method comprises receiving the image document, processing the image document to derive a digitized textual image, detecting one or more regions of bold text within the digitized textual image using an adaptive edge rounding filter, and annotating the one or more regions of bold text within the image document.