A non-transitory computer readable storage medium storing computer readable instructions executable by a computer is provided. The computer readable instructions cause the computer to obtain first image data composing a first image and second image data composing a second image, specify first edge pixels in the first image using the first image and second edge pixels in the second image using the second image data, determine positional relation between the first image and the second image in a first degree of accuracy, based on positional relation between the first edge pixels and the second edge pixels, determine first usable pixels among the first edge pixels and the second usable pixels among the second edge pixels, and using the first usable pixels and the second usable pixels, determine positional relation between the first image and the second image in a second degree of accuracy being higher than the first degree.

Provided are a method and an apparatus for detecting a thickness of paper, and a storage medium. The method includes: acquiring a first thickness image of a target paper; extracting at least one first thickness feature and at least one second thickness feature from the first thickness image in the first thickness image; performing average processing on gray values of multiple pixel points in the at least one first thickness feature to acquire a first gray value, and the average processing is performed on gray values of the multiple pixel points in the at least one second thickness feature to acquire a second gray value; when the first gray value is smaller than the second gray value of multiple pixel points in at least one second thickness feature, determining that a thickness of a region, corresponding to the at least one second thickness feature, on the target paper has changed.

Provided are a detection method, a detection apparatus and a detection process. The detection method includes: using a sensor for idle scanning to obtain a first output electrical signal, and performing feedback correction on the first output electrical signal to eliminate a noise to obtain first correction data; using the sensor to scan a correction specimen page to obtain a second output electrical signal, and performing the feedback correction on the second output electrical signal to eliminate a noise to obtain second correction data; calculating according to the first correction data, the second correction data and an electrical signal predetermined value to obtain third correction data; using the sensor to scan a to-be-detected object to obtain a third output electrical signal; and correcting the third output electrical signal according to the first correction data and the third correction data. In the detection method obtains an accurate detection result.

A drug screening system and methods of using the same are disclosed. The drug screening system identifies and highlights drugs or other contraband substances enclosed within mailpieces based on score imagery computed from selected wavelengths based on chemical signatures. A wide-field, multispectral short-wave infrared imaging system allows for dissolved, concealed drug screening of mailpieces that improve inspection efficiency and accuracy.

Methods and systems are disclosed for analyzing one or more images of a textile to determine a presence or absence of defects. In one example, an image of at least a portion of a textile may be obtained and compared to a reference image of a reference textile. Based on the comparison, one or more areas indicative of a height variation between the textile and the reference textile may be determined. An action may be performed based on the one or more areas indicative of the height variation.

An inspection system of a filament yarn, including: an irradiation means configured to irradiate the filament yarn with inspection light; a measurement means configured to measure with an area sensor a luminance level of a shade and a background of the filament yarn; an image processing means configured to obtain image information on the basis of information obtained from the area sensor; and a determination means configured to decide a type and a frequency of an error from the image information and determine an inspection result of the filament yarn on the basis of a threshold value according to the error is provided.

Various examples are provided related to face identification of material. An image can be captured by a vision system and feature parameters determined and compared to a material feature database to determine which face of the material is being presented. The vision system can employ a set of parameters for configuration to acquire the image. The system can communicate the identification to downstream processes in real time. A near-universal, color agnostic, angular orientation independent identification of material faces can be determined without the need for physical manipulation of the material.

An information processing device includes an acquisition unit acquiring image data and ink data, the image data being obtained by digitizing, as an image, the fabric before the printing process is performed, the ink data indicating a type of the ink, a storage unit storing derivation data for deriving a recommended parameter for at least one of the pre-processing device and the post-processing device, and a control unit deriving, based on the derivation data, the recommended parameter from the image data and the ink data, wherein the derivation data includes first data and second data, the first data being configured to define a learned model learned by machine learning, the learned model being configured to, when the image data is input, output fabric data indicating a feature value of the fabric, the second data indicating a correspondence relationship between the fabric data and the ink data, and the recommended parameter.

A computer system and process for scanning apparel items for generation of three-dimensional (3D) reproduced representations of scanned apparel items having folding line indications. An electronic scan is created of at least one apparel item by an imaging device. Point clouds are determined from the at least one scanned apparel item and at least one high polygon 3D model is determined from the point clouds. 3D translation and rotational camera reference images are generated which are associated with the at least one scanned apparel item. Next, a mannequin pose estimation and correction is determined utilizing the generated 3D translation and rotational camera reference images and mannequin detection and removal is then determined relative to the at least one scanned apparel item. Information (data) for indication of fold lines for folding the at least one scanned apparel item is the determined.

Methods and systems are disclosed for analyzing one or more images of a textile to determine a presence or absence of defects. In one example, an image of at least a portion of a textile may be obtained and compared to a reference image of a reference textile. Based on the comparison, one or more areas indicative of a height variation between the textile and the reference textile may be determined. An action may be performed based on the one or more areas indicative of the height variation.