System and method for detecting the authenticity of products by detecting a unique chaotic signature. Photos of the products are taken at the plant and stored in a database/server. The server processes the images to detect for each authentic product a unique authentic signature which is the result of a manufacturing process, a process of nature etc. To detect whether the product is genuine or not at the store, the user/buyer may take a picture of the product and send it to the server (e.g. using an app installed on a portable device or the like). Upon receipt of the photo, the server may process the receive image in search for a pre-detected and/or pre-stored chaotic signature associated with an authentic product. The server may return a response to the user indicating the result of the search. A feedback mechanism may be included to guide the user to take a picture at a specific location of the product where the chaotic signature may exist.

Systems and methods for detecting cracks in an electronic device are disclosed. In one embodiment, the method includes receiving an image of a front side of a mobile device and automatically identifying edges in the image. For given edges among the identified edges, the method includes determining whether another edge among the identified edges is present within a predetermined distance of the given edge. Next, straight line segments corresponding to the edges for which another edge is within the predetermined distance are identified, and then a crack evaluation assessment is assigned to the mobile device based at least in part on the identified straight line segments.

A method for positioning an intelligent terminal apparatus comprises: acquiring data points scanned by a position detection device in the intelligent terminal apparatus at the current position of the intelligent terminal apparatus; converting valid data points into segment features to obtain a first set of segment features; and converting point features in an established map of the intelligent terminal apparatus into segment features to obtain a second set of segment features; selecting, from the first and second set of segment features, segments having the same position relationship respectively to form a first and a second candidate subset of the first and the second set of segment features respectively; and determining a transformation matrix that matches the first candidate subset to the second candidate subset, and identifying the current position and the orientation angle of the intelligent terminal apparatus in the established map based on the transformation matrix.

Disclosed is a method and system for processing images from an aerial imaging device. An image of an object of interest is received from the aerial imaging device. A parameter vector is extracted from the image. Image analysis is performed on the image to determine a height and a width of the object of interest. Idealized images of the object of interest are generated using the extracted parameter vector, the determined height, and the determined width of the object of interest. Each idealized image corresponds to a distinct filled volume of the object of interest. The received image of the object of interest is matched to each idealized image to determine a filled volume of the object of interest. Information corresponding to the determined filled volume of the object of interest is transmitted to a user device.

An iterative multi-image camera orientation estimation comprising: capturing an image of a scene before the camera; detecting line segments in the scene; computing a maximum likelihood (ML) camera orientation by maximizing a likelihood objective by rotating the camera's X-Y-Z coordinate system such that it is being optimally aligned with the line segments in at least two of the frontal, the lateral, and the vertical orthogonal directions; estimating a maximum a-posteriori (MAP) camera orientation that maximizes an a-posteriori objective such that the MAP camera orientation is an optimal value in between the priori camera orientation and the ML camera orientation, and is closer to the one with smaller uncertainty; iterating the multi-image camera orientation estimation with the priori camera orientation and its corresponding priori camera orientation uncertainty set to the computed MAP camera orientation and its corresponding uncertainty respectively until the uncertainty is lower than a threshold.

Systems and methods for detecting and tracking a marker in real time is disclosed. Shape based segmentation of at least one object detected in a first frame from a sequence of frames is performed to define a region of interest (ROI) surrounding an object of interest corresponding to the marker. A marker detection model is dynamically trained based on sampling points from a plurality of pixels in and around the ROI. The marker is then tracked in real-time based on projected ROI in subsequent frames and the trained marker detection model. To optimize computation time required in classifying the pixels as marker pixels or non-marker pixels, the ROI is reduced to half its size, classification is performed on the reduced ROI and to improve accuracy, blob detection and classifying pixels along the boundary of the reduced ROI is performed by processing the ROI in original resolution.

A method to determine the volume of a box object from the captured image of the box object. The method includes identifying a geometric mark on the box object in the captured image to find the positions of two reference points of the geometric mark. The two reference points are separated by a predetermined distance. The method also includes processing a group of parameters and a predetermined mapping obtained from a calibration process. The group of parameters includes the positions of the two reference points and the predetermined distance separating the two reference points.

The present disclosure provides geological linear body extraction method based on tensor voting coupled with Hough transformation, including pre-processing a remote sensing image to obtain a pre-processed remote sensing image; selecting three optimal wavebands from N multi-spectral wavebands of the pre-processed remote sensing image, so as to obtain a remote sensing image combined by the optimal wavebands, N being a natural number greater than or equal to 3; using Gaussian high-pass filtering to perform sharpening processing on the remote sensing image combined by the optimal wavebands, so as to enhance linearized edge information; performing edge detection on the remote sensing image having enhanced linearized edge information, so as to obtain all edge points in the remote sensing image; and converting all the edge points in the remote sensing image from an image coordinate system to a parameter coordinate system, and extracting a geological linear body from the parameter coordinate system.

The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes receiving a request to authenticate a document image. The image is preprocessed to prepare the image for line orientation analysis. The preprocessed image is analyzed to determine lines in the preprocessed image. The determined lines are automatically analyzed by performing line orientation test(s) on the determined lines to generate line orientation test result(s) for the preprocessed image. The line orientation test result(s) are evaluated to determine whether the image is authentic. In response to determining that at least one line orientation test result matches a predefined condition corresponding to an unauthentic document, a determination is made that the image is not authentic. In response to determining that none of the line orientation test results match any predefined condition corresponding to an unauthentic document, a determination is made that the image is authentic.

Systems and methods disclosed herein provide for some embodiments infrared camera systems for maritime applications. For example in one embodiment, a watercraft includes a plurality of image capture components coupled to the watercraft to capture infrared images around at least a substantial portion of a perimeter of the watercraft; a memory component adapted to store the captured infrared images; a processing component adapted to process the captured infrared images according to a man overboard mode of operation to provide processed infrared images and determine if a person falls from the watercraft; and a display component adapted to display the processed infrared images.