An optical identification method for sensing a physiological feature, includes: projecting light to a physiological portion for generating reflection light from the physiological portion; receiving the reflection light, to generate an image; generating slant pattern information according to the image; transforming the slant pattern information into a pattern identification matrix; and determining the physiological feature according to the pattern identification matrix.

A method, computer system, and computer program product for consolidating and recording elements on a physical display board is provided. The embodiment may include capturing an initial image of a visual display mechanism, whereby the initial image contains elements. The embodiment may also include determining an initial state of the visual display mechanism based on the captured image. The embodiment may further include recognizing characters of the elements in the initial state. The embodiment may also include capturing a subsequent image of the visual display mechanism. The embodiment may further include comparing the initial image and the subsequent image of the visual display mechanism. The embodiment may include identifying updates to the visual display mechanism based on the comparison of the initial image and the subsequent image. The embodiment may further include performing a clean-up function of the elements and the recognized characters, based on the identified updates.

An image-based transaction system includes a mobile device with an image sensor that is programmed to capture, via the image sensor, a video stream of a scene. The mobile device identifies a document using image characteristics from the video stream and acquires an image of at least a part of the document, and then identifies symbols in the image based on locations within the image of the document. The symbols can include alphanumeric symbols. The mobile device processes the symbols according to their type to obtain an address related to the document and the symbols and initiates a transaction associated with the identified document.

Methods, systems, and devices for object recognition are described. A device may generate a subspace based at least in part on a set of representative feature vectors for an object. The device may obtain an array of pixels representing an image. The device may determine a probe feature vector for the image by applying a convolutional operation to the array of pixels. The device may create a reconstructed feature vector in the subspace based at least in part on the set of representative feature vectors and the probe feature vector. The device may compare the reconstructed feature vector and the probe feature vector and recognize the object in the image based at least in part on the comparison. For example, the described techniques may support pose invariant facial recognition or other such object recognition applications.

The proposed method allows to obtain long range data for the objects that are registered with image disparities of just a few pixels, supplementing conventional multi-view stereo (MVS) methods optimized for larger disparity values. This method uses at least four identical image sensing devices with parallel optical axes and located in the corners of a square providing orthogonal baselines for the imager pairs of the equal length. Image enhancement and processing is based on 2-d complex lapped transform (CLT), this method achieves subpixel disparity resolution with frequency-domain differential rectification avoiding resampling of the rectified images. CLT has efficient FPGA implementations with discrete cosine (DCT) and sine (DST) transforms. FPGA-based tile processor (TP) outputs data for the disparity space image (DSI), textures, data for field calibration and velocity measurements with electronic rolling shutter image sensors.

A system, method, and mobile device application are configured to capture, with a mobile device, a document such as a next generation sequencing (NGS) report that includes NGS medical information about a genetically sequenced patient. At least some of the information is extracted from the document using an entity linking engine, and the extracted information is provided into a structured data repository where it is accessible to provide information regarding the patient specifically as well as collectively as part of a cohort of patients with similar genetic variants, medical histories, or other commonalities. In one aspect, the document is matched to a template model, and the document is processed using one or more masks segregating the template model, and therefore the document, into a series of distinct subregions.

Technology for matching images (for example, video images, still images) of an identical infrastructure object (for example, a tower component of a tower supporting power lines) for purposes of comparing the infrastructure object to itself at different points in time to detect a potential anomaly and the potential need for maintenance of the infrastructure object. In some embodiments, this matching of images is done using creation of a three dimensional (#D) computer model of the infrastructure object and by tagging captured images with location on the 3D model across multiple videos taken at different points in time.

A digital image depicting a digital representation of a scene is captured by an image sensor of a vehicle. An identification system recognizes a real-world object from the digital image as a target object based on derived image characteristics and identifies object information about the target object based on the recognition. The identification provides the object information to the vehicle data system of the vehicle so that the vehicle data system can execute a control function of the vehicle based on the received object information.

A method is provided for Optical Character Recognition (OCR). A plurality of OCR decoding results each having a plurality of positions is obtained from capturing and decoding a plurality of images of the same one or more OCR characters. A recognized character in each OCR decoding result is compared with the recognized character that occupies an identical position in each of the other OCR decoding results. A number of occurrences that each particular recognized character occupies the identical position in the plurality of OCR decoding results is calculated. An individual confidence score is assigned to each particular recognized character based on the number of occurrences, with a highest individual confidence score assigned to a particular recognized character having the greatest number of occurrences. Determining which particular recognized character has been assigned the highest individual confidence score determines which particular recognized character comprises a presumptively valid character for the identical position.

A method and system for determining at least a size dimension of objects shown in multimedia content items are presented. The method includes receiving an input multimedia content item; identifying objects shown in the multimedia content item; generating at least a first signature for at least a first object of the plurality of objects and at least a second signature for at least a second object; identifying at least one concept that matches the at least a first object; determining an actual size of the first object respective of the match to the at least one concept; determining a size scale between the first object and the second object using the at least a first signature and the at least a second signature; and determining the at least size dimension of the second object respective of the size scale and the actual size of the first object.