A method of structural masking for progressive health monitoring of a structural component includes receiving a current image of the structural component. A processor aligns the current image and a reference image of the structural component. The processor performs a structure estimation on the current image and the reference image to produce a current structure estimate image and a reference structure estimate image. The processor generates a structural mask from the reference structure estimate image. The processor masks the current structure estimate image with the structural mask to identify one or more health monitoring analysis regions including a potential defect or damaged area appearing in the masked current structure estimate image that does not appear in the reference structure estimate image.

A system and method of validating electronic encoded information from magnetic stripe card data transmitted as electronic stripe data includes a lump transmission stream. The lump transmission stream is read by at least two track channel readers each of which recognizes and reads only data corresponding to data to be read from a respective magnetic stripe represented in the lump transmission stream, which has data read from two tracks of magnetic card stripes. One track channel reader reads the first portion of the lump stream and discards the second portion of the stream, the second track channel reader reads the second portion of the stream and discards the first portion of the stream.

Apparatus, methods, and articles of manufacture for implementing crowdsourcing pipelines that generate training examples for machine learning expression classifiers. Crowdsourcing providers actively generate images with expressions, according to cues or goals. The cues or goals may be to mimic an expression or appear in a certain way, or to “break” an existing expression recognizer. The images are collected and rated by same or different crowdsourcing providers, and the images that meet a first quality criterion are then vetted by expert(s). The vetted images are then used as positive or negative examples in training machine learning expression classifiers.

Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

For image quality scoring of an image from a medical scanner, a generative model of an expected good quality image may be created using deep machine-learning. The deviation of an input image from the generative model is used as an input feature vector for a discriminative model. The discriminative model may also operate on another input feature vector derived from the input image. Based on these input feature vectors, the discriminative model outputs an image quality score.

An electronic device, according to various embodiments of the present disclosure, may include: an image sensor that obtains the first image; an image processing unit that processes the obtained first image to thereby create the second image; an image quality inspecting unit that performs image quality inspection on the basis of the created second image; and an iris recognition unit that, if the image quality of the second image satisfies a predetermined condition, performs iris recognition on the basis of the obtained first image.

An image transfer method and an image recognition method that are useful in performing an image recognition process on photographs (photographed images) of participants taken at events. In the image transfer method, moving image data is generated by converting image data received from an outside to moving image frames, and is transmitted to an image recognition device. In the image recognition method, at least one virtual computer is activated. The moving image data from an image transfer device is stored in a cloud data storage section. The virtual computer receives the stored moving image data, and performs the image recognition process on image data converted from the moving image data. The virtual computer transmits processing results to the cloud data storage section. The virtual computer is terminated after termination of the image recognition process.

A method for identifying print control elements for quality data acquisition includes encoding position information in a human-readable identification code, encoding specific print job information and the human-readable identification code in a machine-readable data code, positioning the codes alongside their associated print control element on a printing substrate, photographing the printed print control element and adjacent machine-readable data code using information from adjacent identification code, and processing data with a mobile communication device having a camera function and communications interface. Image data produced are exporting to a support computer via the communications interface. Machine-readable data code are decoded, image data on the computer are analyzed using information obtained from decoded machine-readable data code, the results of analysis are transmitted from the computer to the mobile communication device, and erroneous settings, found by image analysis, in a printing press producing printed products, are corrected.

This application teaches a method for indicating voxel quality comprising graphically and/or mathematically. Such a method may include measuring a distance from the three-dimensional scanning device to an area of a subject corresponding to an image voxel. It may also include measuring an angle between a line of sight from the three-dimensional imaging device and an orthogonal ray of the same area of the subject corresponding to the same voxel. The process may further include comparing the measured distance and angle to known acceptable operating ranges of the scanner, and plotting a quality point corresponding to the foregoing metrics on a set of axes.