Systems and methods for mobile enrollment in automated clearing house (ACH) transactions using mobile-captured images of financial documents are provided. Applications running on a mobile device provide for the capture and processing of images of documents needed for enrollment in an ACH transaction, such as a blank check, remittance statement and driver's license. Data from the mobile-captured images that is needed for enrolling in ACH transactions is extracted from the processed images, such as a user's name, address, bank account number and bank routing number. The user can edit the extracted data, select the type of document that is being captured, authorize the creation of an ACH transaction and select an originator of the ACH transaction. The extracted data and originator information is transmitted to a remote server along with the user's authorization so the ACH transaction can be setup between the originator's and receiver's bank accounts.

Information about a drug-containing vessel is determined by capturing image data of the curved surface of a cylindrical portion of a drug-containing vessel. The image data is unfurled from around the curved surface, binarised, and a template matching algorithm employed to determine that the label information comprises candidate information about the vessel and/or the drug.

Embodiments herein describe tracking the location and orientation of a target in a digital image. In an embodiment, this tracking can be used to control navigation for a vehicle. In an embodiment, a digital image can be captured by a visual sensor is received. A first array including a plurality of binary values related to the pixel velocity of a first plurality of pixels in the digital image as compared to corresponding pixels in a first one or more prior digital images can be generated. A second array including a plurality of values related to the standard deviation of pixel intensity of the first plurality of pixels in the digital image as compared to corresponding pixels in a second one or more prior digital images can be further generated. A plurality of thresholds relating to the values in the second array can be determined. A plurality of target pixels and a plurality of background pixels can be identified in the digital image, based on the first array, the second array, and the plurality of thresholds. A binary image related to the digital image, based on the identified plurality of target pixels and the identified plurality of background pixels, and identifying at least one of a location and an orientation of the target in the digital image based on the binary image, can be generated. In an embodiment, a command can be transmitted to a navigation system for a vehicle, to assist in navigating the vehicle toward the target, based on the identified at least one of a location and an orientation of the target.

Systems and methods are disclosed for segmenting a digital image to identify an object portrayed in the digital image from background pixels in the digital image. In particular, in one or more embodiments, the disclosed systems and methods use a first neural network and a second neural network to generate image information used to generate a segmentation mask that corresponds to the object portrayed in the digital image. Specifically, in one or more embodiments, the disclosed systems and methods optimize a fit between a mask boundary of the segmentation mask to edges of the object portrayed in the digital image to accurately segment the object within the digital image.

A method of label detection includes: obtaining, by an imaging controller, an image depicting a shelf; increasing an intensity of a foreground subset of image pixels exceeding an upper intensity threshold, and decreasing an intensity of a background subset of pixels below a lower intensity threshold; responsive to the increasing and the decreasing, (i) determining gradients for each of the pixels and (ii) selecting a candidate set of the pixels based on the gradients; overlaying a plurality of shelf candidate lines on the image derived from the candidate set of pixels; identifying a pair of the shelf candidate lines satisfying a predetermined sequence of intensity transitions; and generating and storing a shelf edge bounding box corresponding to the pair of shelf candidate lines.

Methods and systems for image binarization using mean restrain are disclosed. A method includes: obtaining, by a computing device, a grayscale image; generating, by the computing device, a histogram from the grayscale image; determining, by the computing device, a foreground mean value and a background mean value for each pixel value in the histogram; determining, by the computing device, a binarization threshold using the foreground mean values and the background mean values; and generating, by the computing device, a binarized image using the grayscale image and the binarization threshold.

The present disclosure provides an inspection device, a control method and a control apparatus for the same, and relates to the technical field of inspection patrol. The inspection device can patrol in a lane which has at least one lane line. The control method includes collecting an environment image around the inspection device. The control method includes identifying the lane line from the environment image. The control method includes determining a distance between the inspection device and the lane line. The control method includes determining a deviation between the inspection device and a preset route in the lane according to the distance between the inspection device and the lane line. The control method includes controlling the inspection device to move toward the preset route according to the deviation.

A mark detection system and method is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes an image processor configured to execute the computer-readable instructions to access an image of a document and process the image to generate a binarized image. The image processor is further configured to extract components of the binarized image using a connected-component labelling algorithm. Furthermore, the image processor is configured to analyze features of the extracted components to detect one or more marks in the document.

The present disclosure provides, inter alia, methods and compositions (e.g., conjugates) for imaging, at high spatial resolution, targets of interest.

An image processing device which is capable of accurately detects and corrects areas affected by clouds even if multiple types or layers of clouds present in images, is disclosed. The device includes: a cloud spectrum selection unit for selecting at least one spectrum for each of pixels from spectra of one or more clouds present in an input image; an endmember extraction unit for extracting spectra of one or more endmembers other than the one or more clouds from those of the input image; and an unmixing unit for deriving fractional abundances of the respective spectra of one or more endmembers and a selected spectrum of one of the one or more clouds for the each of pixels in the input image