License plate recognition (“LPR”) systems may encounter degradation in quality and obstructions that negatively impact performance of the LPR systems. A LPR system is configured to apply image processing algorithms to output information describing performance of the system and to monitor the performance of the system over time. Based on the performance of the system over time, the LPR system determines when one or more entities of the system require action to maintain or improve performance and transmits information describing the required action.

An image generation method obtains an original image. A character area, a background area, and a position of each flawless character in the original image are determined. The character area is segmented to obtain a first image of each flawless character. A background is removed from the first image to obtain a second image. First image processing is performed on the second image to obtain a third image. Second image processing is performed on the second image to obtain fourth images. Third image processing is performed on the fourth images respectively to obtain fifth images. A similarity between each fifth image and the third image is calculated. When the similarity is greater than a defect threshold, a background image is segmented. Brightness of the background image is adjusted. The target fourth image and adjusted background image are synthesized. The method can generate images with defective characters quickly.

An information processing apparatus according to one embodiment includes a memory and one or more hardware processors. The memory stores order information in which an order of pieces of meta-information for a character to be recognized is defined. The one or more hardware processors are connected to the memory and function as a recognition unit and an update unit. The recognition unit serves to perform character recognition on an image including a character string by using first meta-information specified from the pieces of the meta-information. The update unit serves to update the first meta-information to second meta-information. in accordance with the order information in a case when a confidence score of the character recognition satisfies a predetermined condition. The character recognition is performed by using the second meta-information.

An information processing apparatus according to one embodiment includes a memory and one or more hardware processors. The memory stores order information in which an order of pieces of meta-information for a character to be recognized is defined. The one or more hardware processors are connected to the memory and function as a recognition unit and an update unit. The recognition unit serves to perform character recognition on an image including a character string by using first meta-information specified from the pieces of the meta-information. The update unit serves to update the first meta-information to second meta-information. in accordance with the order information in a case when a confidence score of the character recognition satisfies a predetermined condition. The character recognition is performed by using the second meta-information.

Various methods, apparatuses/systems, and media for data processing are disclosed. A processor receives a digital document; applies an optical character recognition (OCR) algorithm on said received digital document by utilizing an OCR tool; identifies defective data extracted by the OCR tool resulted from relatively inferior image quality of the received digital document; implements an auto rectification algorithm on the identified defective data; automatically generates, in response to implementing the auto rectification algorithm, corresponding auto-rectified data for each identified defective data; records the defective data and corresponding auto-rectified data at a field level; receives user input data on said recorded auto-rectified data; determines whether the auto-rectified data is correct or not; and populates, based on determining that the auto-rectified data is correct, a machine learning model with said received user input data to be utilized for subsequently received digital document.

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 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 and system is provided for determining the denomination and related data for a currency item using a personal computing device, such as a mobile phone. The device includes or is connected to an image capture device that is preferably a digital video camera. At least one image of a target currency item is captured then processed for image quality. A further processing of the image includes a coordinate mapping. A comparison is made between individual pixels of the processed image based on the assigned coordinate mapping with a database of reference currency images to determine the currency denomination. Additional processing of the currency image provides the date and other data regarding the target currency item. A market value for the target currency item is identified by reference to a valuation database using the data determined for the currency item.

According to an embodiment, an information processing apparatus includes an image interface, an input interface, a display interface, a manipulation interface, a storage unit, and a processor. The processor is configured to cause a display terminal through a display interface to display a screen so as to receive an input of a key through the manipulation interface; transmit an operation signal indicating the key to the one of external devices through the input interface; and when the key is a repeat key, transmit an operation signal for inputting a character string indicated by repeat information to the one of the external devices through the input interface.

According to an embodiment, an information processing apparatus includes an image interface, an input interface, a display interface, a manipulation interface, a storage unit, and a processor. The processor is configured to cause a display terminal through a display interface to display a screen so as to receive an input of a key through the manipulation interface; transmit an operation signal indicating the key to the one of external devices through the input interface; and when the key is a repeat key, transmit an operation signal for inputting a character string indicated by repeat information to the one of the external devices through the input interface.