A method for processing a plurality of radiation protective garments includes receiving a plurality of radiation protective garments from a customer, scanning an identification tag of each received radiation protective garment to identify electronic identification data of each radiation protective garment, and automatically identifying a subset of the radiation protective garments that require performance testing by using the identification data to access a file history of each scanned radiation protective garment, the file history including a performance testing schedule. The method further includes using an x-ray scanning system to scan the subset of the radiation protective garments and to generate x-ray image data, automatically updating the file histories of the subset of the radiation protective garments to include the corresponding x-ray image data, and identifying defects in the corresponding radiation protective garment based on the x-ray image data.

A method for determining a size of a garment, comprising: receiving an image comprising a representation of the garment and a representation of a reference element, the reference element having a predefined shape and predefined dimensions; identifying the representation of the garment within the received image; identifying the representation of the reference element within the received image; determining first dimensions of the representation of the reference element within the received image and second dimensions of the representation of the garment within the received image; determining real dimensions of the garment using the first dimensions of the representation of the reference element within the received image, the second dimensions of the representation of the garment within the received image and the predefined dimensions of the reference element; and outputting the real dimensions of the garment.

A motor controlling system is disclosed. The motor controlling system is integrated in an apparatus having roll-to-roll mechanism, and comprises a linear light source, N number of cameras and a modular electronic device. When a roll of continuous web material is discharged by an unwinding unit of the roll-to-roll mechanism so as to be further transferred to an inspection unit, the cameras are controlled by the modular electronic device to capture a plurality of time-consecutive material image frames. Subsequently, the modular electronic device conducts a defection inspection for a segment of the continuous web material by applying an image process to the material image frames. As a result, in case of there being at least one defect found, the modular electronic device stops a plurality of motors of the apparatus from running, thereby making the segment of the continuous web material be positioned on an inspection platform.

Methods and systems are disclosed for performing operations comprising: receiving a monocular image that includes a depiction of a user wearing a garment; generating a segmentation of the garment worn by the user in the monocular image; accessing a video feed comprising a plurality of monocular images received prior to the monocular image; smoothing, using the video feed, the segmentation of the garment worn by the user to provide a smoothed segmentation of the garment worn by the user; and applying one or more visual effects to the monocular image based on the smoothed segmentation of the garment worn by the user.

A method of evaluating camouflage for a specified area of responsibility, the method includes calculating an apparent spectrum of the camouflage at far field with respect to an observer; calculating an apparent spectrum of the specified area of responsibility at far field with respect to the observer; calculating a difference between the apparent spectrum of the camouflage with the apparent spectrum of the area of responsibility; and comparing the difference to a predetermined threshold, thereby determining suitability of the camouflage for the specified area of responsibility.

Systems and methods are described for determining quality attributes of raw material of textile. According to an embodiment the for determining quality attributes of raw material of textile can include a processor coupled with a memory, the memory storing instructions executable by the processor to: receive one or more images of said raw material captured by an imaging device; enhance one or more features of said received one or more images by varying dynamic range of said one or more features of said received one or more images to obtain dynamically enhanced one or more images; extract values of one or more attributes of said enhanced one or more images, wherein said one or more attributes includes any or combination of staple length, fibre fineness, short fibre content, yarn hairiness, yarn count, yarn elongation, maturity and moisture content; and compare the extracted values with reference attribute values stored in a first database, wherein quality of said raw material is determined based on comparison of the extracted values with the reference attribute values.

A system and method of obtaining a quantitative evaluation of paper. By looking at the topographic data and comparing it to machine parameters, an operator can optimize the paper forming machine settings to create consistently high quality paper with minimal surface defects.

According to various embodiments, a framework for transferring micro-scale properties of any kind (geometry, optical properties, material parameters resolution, etc.) of a material, to larger images of the same material is provided. The framework includes a machine learning model capable of learning to perform this transfer from a set of micro-scale images of one or more patches of the material and micro-scale properties of the material. The machine learning framework transfers the micro-scale properties to images of the same material, regardless of its size, resolution, illumination or geometry.

Method and system for facilitating personalized garment fit evaluations over computer network, irrespective of non-uniform garment sizing options. 2D image of a selected garment offered for purchase is received. 2D image of a reference garment having preferred fit for customer and of same garment type as selected garment is received. Selected garment image and reference garment image includes a view of the selected/reference garment flattened against a surface and a measurement reference scale enabling measurement along any two image points. Selected garment and/or reference garment is transformed into a proportional image in which distances between points are presented along a common scale. Selected garment image is compared with reference garment image, and an indication of at least one fit deviation measurement of selected garment relative to reference garment is provided. A fit compatibility of selected garment may be determined and provided based on fit deviation measurement and garment fitting property.

Provided are a substrate inspecting unit capable of reducing image data labeling work time through training image data set verification and semi-automatic image labeling, and at the same time, improving prediction performance by improving classification accuracy for data sets, and a substrate treating apparatus including the same. The substrate inspecting unit comprises a feature extracting module for extracting a feature from training data included in each class in response to a plurality of training data related to image data of a substrate being classified according to a predefined class, a validity evaluating module for evaluating validity of the feature, a class verifying module for verifying the predefined class, and a data reconstructing module for reconstructing the plurality of training data based on a feature determined as valid and a verified class, wherein reconstructed training data is utilized when inspecting the substrate.