A mark irradiation unit (130) irradiates an object with a mark. An image capture unit (140) captures an image of the object, and generates image data. Then, an image capture area data generation unit recognizes a position of the mark in the object, and cuts out image capture area data which is a part of the image data on the basis of the mark. For this reason, the mark irradiation unit (130) irradiates the object with the mark, and thus even when a positioning symbol is not printed on the object to be stored as the image data, only a necessary portion in the image data is cut out.

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.

An identification module is disclosed for use in a key making machine. The identification module may have a key receiving assembly configured to receive only a shank of an existing key. The identification module may also have a tip guide, configured to receive a tip of the shank of the existing key. The tip guide may have a slot that exposes a tip end of the shank. The identification module may also have an imaging assembly configured to capture an image of the tip end through the slot.

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.

To issue an appropriate warning based on detection of an object even under the circumstances where it is difficult to determine the outside environment of a movable body, a warning device according to the present invention includes an image acquisition unit configured to acquire a plurality of images respectively based on a plurality of filter characteristics, a detection unit configured to perform detection of a specified object on each of the plurality of acquired images, and a warning unit configured to issue a specific warning when the object is detected from at least any one of the plurality of acquired images, wherein the warning unit issues a higher level of warning when the object is detected from all of the plurality of images than when the object is detected from some of the plurality of images.

A method and system for monitoring a driver's state include obtaining a baseline biometric parameter value of a driver from a first set of images, obtaining a current biometric parameter value of the driver from a second set of images, comparing the current value with the baseline value and determining the driver's state based on the comparison.

Aspects of the present disclosure include methods, systems, and non-transitory computer readable media for receiving an initial image of the area, receiving an updated image of the area, detecting at least one of a person in the area or a movement in the area based on the updated image, comparing the updated image and the initial image to identify a change in the area, and determining a presence or an absence of the occlusion based on the change in the area and the at least one of the person or the movement in the area.

In a feature, a road condition detection system includes: a combination module configured to generate a combined image based on at least two images, each of the two images including a road and generated based on one of: (a) an image captured using a camera, (b) light detection and ranging (LIDAR) data, (c) radar data, and (d) ultrasonic data; a feature extraction module configured to generate a first feature map based on the combined image; an information map module configured to generate a second feature map based on at least one operating parameter; a joining module configured to generate a joint feature map based on the first and second feature maps; and a condition module configured to set a road condition of the road in front of a vehicle based on the joint feature map.

Embodiments include systems and methods for remotely measuring distances in an environment captured by a device. A device captures a video stream of a device along with AR data that may include camera pose information and/or depth information, and transmits the video stream and AR data to a remote device. The environment may be analyzed to identify objects such as lines, edges, curves, shapes, anchors/corners, products, e.g., appliances, and other things of interest. Some or all of objects may be identified to the remote device to facilitate selecting an object or region of interest. Selected points for an object may be more precisely located by snapping them to corresponding anchor points for an object. Using anchor points facilitates more precise identification and/or measurement of an aspect of an object, such as one of its dimensions, the volume of a space, or performing other actions such as replacement of an object.

Scanners, methods, and computer storage media having computer-executable instructions embodied thereon that process variable sized objects with high package pitch on a moving conveyor belt are provided. The scanners include a substrate and a plurality of sensors attached to the substrate. The plurality of sensors forms an array of sensors having at least two or more rows of off-axis sensors. The sensors may include a one or more area array sensors. The arrays of sensors captures moving objects row by row and are optimized reduce object spacing on the conveyor belt. Additionally, the scanner having the array of sensor may process different objects having different heights at the same time. Accordingly, object throughput on the conveyor belt is increased by reducing minimum object gap (e.g., processing of “no gap” or non-singulated objects).