In some embodiments, apparatuses and methods are provided herein useful to train a machine learning algorithm to detect text of interest. In some embodiments, there is provided a system to detect vertically oriented text of interest including a first data set comprising a plurality of captured digital images each depicting an object of interest and a second data set comprising a plurality of augmented digital images each depicting a captured digital image augmented with a synthetic text image; a first control circuit configured to cause the machine learning algorithm to output a machine learning model trained to automatically detect occurrences of vertically oriented text of interest based on the first data set and the second data set; at least one camera; and a second control circuit configured to execute the machine learning model to automatically detect vertically oriented text of interest on the object of interest.

A system and method for correcting image data is disclosed. The method includes receiving one or more documents from one or more electronic mediums. The method further includes determining a primary character and one or more alternate characters corresponding to the mis-captured character image, extracting one or more confident instances of the primary character and the one or more alternate characters from the one or more documents and generating one or more scores corresponding to the primary character and the one or more alternate characters. Further, the method includes predicting a correct character corresponding to the mis-captured character image by using a trained image prediction-based ML model and automatically replacing the mis-captured character image with the predicted correct character.

An interactive voice response system is provided that includes an interactive voice recognition module, an image collection module, and a data extraction module. The image collection module communicates with the voice recognition module and the user device. The extraction module communicates with the image collection module. The voice recognition module collects speech data from a user of the user device and provides an indication to the image collection module when the speech data includes complex data. The image collection module, in response to the indication, communicates with the user device in a text message. The text message includes a link that, when activated, opens a camera on the user device. The image collection module, in response to receiving an image having the complex data from the camera, communicates the image to the extraction module, which extracts the complex data from the image as textual data.

An image reading apparatus includes a character recognition processing unit, an incorrect recognition index calculator, a certainty calculator, a direction determining unit, and an image processing unit. The incorrect recognition index calculator calculates incorrect recognition indexes. The incorrect recognition index is set based on a count of incorrect recognition characters. The count of incorrect recognition characters is a count of candidates for characters possibly incorrectly recognized when the documents are read. The incorrect recognition index is set such that recognition certainty indicative of accuracy of the recognition becomes smaller as the count of incorrect recognition characters increases. The certainty calculator adjusts the recognition certainty using the incorrect recognition index. The direction determining unit that determines a direction of the documents based on the adjusted recognition certainty. The image processing unit corrects the image data based on the determined document direction to align image directions of the plurality of documents.

An image processing device includes: an obtaining unit that obtains image information of a second region to detect an erecting direction of an image formed on a document, the second region being defined in the image in advance according to a criterion different from a criterion for defining a first region in the image, in which character recognition is performed; and an output unit that outputs character information of the first region, the character information being recognized in accordance with the erecting direction of the image obtained from the image information.

An image processing system and an image processing method for localising recognised characters in an image. An estimation unit is configured to estimate a first location of a recognised character that has been obtained by performing character recognition of the image. A determination unit is configured to determine second locations of a plurality of connected components in the image. A comparison unit is configured to compare the first location and the second locations, to identify a connected component associated with the recognised character. An association unit is configured to associate the recognised character, the identified connected component, and the second location of the identified connected component.

Disclosed is a system for performing User Interface (UI) verification of a Device Under Test (DUT). Before performing the UI verification, a set of corner markers is positioned at corners of a display frame associated to the DUT. Once the set of corner markers are positioned, an image receiving module receives a DUT image, captured by an image capturing unit, of the UI pertaining to a DUT. A skew correction module for correcting orientation of the DUT image by determining an orientation correction factor. A file configuration module for storing the orientation correction factor in a pre-configuration file when the DUT image is occupying the content greater than the predefined threshold percentage. In one aspect, the orientation correction factor may be referred while testing a UI of the DUT.

An object is to easily and appropriately identify the orientation of imaging means at the time of image capturing. A control section of an imaging device or an image processing device acquires an image captured by an imaging section and performs image recognition processing of recognizing a photographic subject corresponding to a first orientation such as a horizontal imaging orientation or a vertical imaging orientation in the image so as to judge whether a predetermined photographic subject is present in the image. Then, based on the judgment result, the control section identifies whether the orientation of the imaging device or the imaging section at the time of image capturing is the first orientation or a second orientation.

Speed and accuracy of character recognition can be improved by isolating text orientation during an early stage of processing an image containing a mixture of horizontal and vertical text. Vertical and horizontal line bounding boxes are defined from characters in the image. In a section of the image containing horizontal text, vertical line bounding boxes may tend to be larger and/or spaced close together due to misalignment of characters. For the same reason, horizontal line bounding boxes may tend to be larger and/or spaced closed together in a section of the image containing vertical text. Such variations in size and/or spacing may be used to identify a division between the horizontal and vertical text. A subsequent character recognition process may take advantage of a known division to conserve computing resources.

Speed and accuracy of character recognition can be improved by isolating text orientation during an early stage of processing an image containing a mixture of horizontal and vertical text. Vertical and horizontal line bounding boxes are defined from characters in the image. In a section of the image containing horizontal text, vertical line bounding boxes may tend to be larger and/or spaced close together due to misalignment of characters. For the same reason, horizontal line bounding boxes may tend to be larger and/or spaced closed together in a section of the image containing vertical text. Such variations in size and/or spacing may be used to identify a division between the horizontal and vertical text. A subsequent character recognition process may take advantage of a known division to conserve computing resources.