Abstract: A diagnostic support for a skin includes a radio-transparent structure that defines a folding surface of the skin and on which the skin may be stretched and consequently folded, thereby defining folded, mutually superimposed portions spaced apart from each other. The support may be used for radiographic inspection of a folded animal skin.

Abstract: Embodiments of the present systems and methods may provide techniques that are applicable to a variety of imaging modalities and that utilize prior knowledge of the dynamics of a physiological system to analytically generate augmented samples for machine learning. For example, in an embodiment, a method implemented in a computer comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method may comprise generating a transform for an image of tissue based on deformation of the tissue under compression, obtaining an image of tissue using an imaging modality, and generating an output image by transforming the image of the tissue using the transform.

Abstract: A method of vehicle detection is provided. The method comprises receiving an image from a traffic camera, wherein the image contains vehicle traffic flow. A number of regions in the image that exceed a predetermined number of candelas are identified and masked. Contrast edges are added around the masked regions in the image. One or more vehicles are detected in the image based on the contrast edges.

Abstract: Provided is a computer-recordable recording medium having stored thereon a video file including artificial intelligence (AI) encoding data, wherein the AI encoding data includes: image data including encoding information of a low resolution image generated by AI down-scaling a high resolution image; and AI data about AI up-scaling of the low resolution image reconstructed according to the image data, wherein the AI data includes: AI target data indicating whether AI up-scaling is to be applied to at least one frame; and AI supplementary data about up-scaling deep neural network (DNN) information used for AI up-scaling of the at least one frame from among a plurality of pieces of pre-set default DNN configuration information, when AI up-scaling is applied to the at least one frame.

Abstract: Methods and systems are provided for medical imaging systems. In one embodiment, a method for a medical imaging system comprises acquiring emission data during a positron emission tomography (PET) scan of a patient, reconstructing a series of live PET images while acquiring the emission data, and tracking motion of the patient during the acquiring based on the series of live PET images. In this way, patient motion during the scan may be identified and compensated for via scan acquisition and/or data processing adjustments, thereby producing a diagnostic PET image with reduced motion artifacts and increased diagnostic quality.

Abstract: Embodiments of the present disclosure provide a method, apparatus for determining a rotation angle of an engineering mechanical device, an electronic device and a computer readable medium. The method may include: acquiring a depth image sequence acquired by a binocular camera disposed at a rotating portion of the engineering mechanical device during rotation of the rotating portion of the engineering mechanical device; converting the depth image sequence into a three-dimensional point cloud sequence; and determining a matching point between three-dimensional point cloud frames in the three-dimensional point cloud sequence, determining a rotation angle of the binocular camera during the rotation of the rotating portion of the engineering mechanical device based on the matching point between the three-dimensional point cloud frames as the rotation angle of the engineering mechanical device.

Abstract: Disclosed are methods for handwriting recognition. In some aspects, an image representing a page of a sample document is analyzed to identify a region having indications of handwriting. The region is analyzed to determine frequencies of a plurality of geometric features within the region. The frequencies may be compared to profiles or histograms of known language types, to determine if there are similarities between the frequencies in the sample document relative to those of the known language types. In some aspects, machine learning may be used to characterize the document as a particular language type based on the frequencies of the geometric features.

Abstract: A method for checking an alignment of a 2D or 3D camera, wherein a reference image is detected and stored in a first preferred alignment of the camera, wherein a current image is detected to check the alignment of the camera, wherein the reference image is provided monochrome with a first color and the current image is provided monochrome with a second color that differs from the first color, and wherein the current image and the reference image are displayed as an image mixing.

Abstract: Method of defining at least one treatment area including receiving a first set of data from a digital geometric representation of a target area; receiving a second set of data representing at least a portion of an applicator designed to contact the target area; digitally overlying the second set of data over the first set of data to generate a first digital overlay; digitally defining a treatment area on the first digital overlay surrounding the condition; generating a third set of data representing a portion of the applicator and the treatment area; digitally overlying the third set of data over the first set of data to generate a second digital overlay representing coverage of a condition by the treatment area; and generating a first electronic image that includes a visual depiction of the second digital overlay.

Abstract: A method is for the automated evaluation of at least one image data record of a patient recorded with a medical image recording device for the preparation of diagnostic findings. In the method, at least one item of input data describing the patient and/or the recording process and/or the examination target is determined after completion of the recording of the image data record. A selection algorithm which evaluates the image data record and the input data is used for determining at least one automated evaluation process to be applied and applicable and at least one image quality measure with regard to the evaluation process is determined by evaluating the image data record. The selected automated evaluation process is only performed for an image quality measure meeting a threshold quality requirement.

Abstract: A medical image processing apparatus, having a processor configured to divide brains included in a brain image and a standard brain image into a plurality of regions corresponding to each other, calculate a first correction amount between the pixel value of a first reference pixel included in each of the plurality of region in the brain image and the pixel value of a second reference pixel and a second correction amount for matching first other pixel values other than the first reference pixel included in each of the plurality of regions in the brain image with pixel values of second other pixels, and correct the brain image based on the first correction amount and the second correction amount.

Abstract: A range differentiator useful for auto-focusing, the range differentiator including an image generator providing an image of a scene at various physical depths, a depth differentiator distinguishing portions of the image at depths below a predetermined threshold, irrespective of a shape of the portions, and providing a depth differentiated image and a focus distance ascertainer ascertaining a focus distance based on the depth differentiated image.

Abstract: Provided is a computer-recordable recording medium having stored thereon a video file including artificial intelligence (AI) encoding data, wherein the AI encoding data includes: image data including encoding information of a low resolution image generated by AI down-scaling a high resolution image; and AI data about AI up-scaling of the low resolution image reconstructed according to the image data, wherein the AI data includes: AI target data indicating whether AI up-scaling is to be applied to at least one frame; and AI supplementary data about up-scaling deep neural network (DNN) information used for AI up-scaling of the at least one frame from among a plurality of pieces of pre-set default DNN configuration information, when AI up-scaling is applied to the at least one frame.

Abstract: A method for anti-counterfeiting processing and related products are disclosed. The method may include: acquiring a face image and an iris image, wherein both the face image and the iris image are from a target object; determining a positional relationship between the iris image and the face image, and performing living body detection according to the iris image; and in response to the positional relationship satisfying a pre-set condition and the iris image being from a living body, determining that the target object is a true and effective face.

Abstract: Methods and systems for imaging a lumen, wherein imaging is manipulated to provide centered magnified version of the image, yielding precise and centered images for better efficacy in real-time treatment by practitioners and experts.

Abstract: Briefly, a method for verifying the visual perceptibility of a display is provided. An intended message is written to a bistable display. Pixels that comprise portions of the message are measured and evaluated to determine if the message actually displayed on the bistable display was perceptible by a human or a machine. In some cases, information regarding the message actually perceivable from the display may be stored for later use. Responsive to determining that a message is perceivable or not perceivable, alarms may be set, one or more third parties notified, or additional display features may be set.

Abstract: A method for visible cephalometric measurement is provided. The method comprises: acquiring a data item to be measured according to a preset analysis method, and acquiring preset reference information; determining a measurement reference point according to the acquired preset reference information; and generating a measurement result based on the measurement reference point and the data item to be measured, and displaying it. A computer processing device and a visible cephalometric system are also provided. The computer may automatically generate measurement results according to user's selection and perform cephalometric measurement more easily, accurately, and more efficiently.

Abstract: A video editing application generates video-filled text based on context-sensitive video segments. For example, the video editing application receives a text selection including multiple characters. A text selection context that identifies a characteristic of the text selection is determined, the context including a category of the text selection and a tag identifying an entity associated with the text selection. Scores are computed for multiple video segments, each score indicating a match between an attribute of the respective video segment and the text selection context. Video segments with attributes that match the context are selected, based on a comparison of each score to a threshold. The video editing application generates a composite video that includes a combination of a selected video segment and a character from the text selection, the combination including an outline of the character and the selected video segment.

Abstract: The present disclosure provides a posture estimation method, a posture estimation apparatus, and a computer readable storage medium. Here, the posture estimation method includes: calculating an angular velocity control amount at a current moment based on a measured acceleration value and an estimated acceleration value at the current moment; correcting the measured angular velocity value at the current moment according to the calculated angular velocity control amount to obtain the corrected angular velocity value at the current moment; and obtaining an estimated posture quaternion value at a next moment according to the corrected angular velocity value obtained by calculation and an estimated posture quaternion value at the current moment.

Abstract: A method for identifying distracted pedestrians. The method includes determining operating conditions of a vehicle using a plurality of vehicle controllers. Pedestrian parameters for a pedestrian in a vicinity of the vehicle are acquired using a plurality of vehicle sensors. The pedestrian parameters include at least one of face positions, body positions, gait and hand gestures. Information related to an environment surrounding the vehicle is acquired. Pedestrian awareness level is determined based on the acquired pedestrian parameters and based on the information related to the environment surrounding the vehicle. A determination is made whether the pedestrian awareness level is below a predefined threshold. The pedestrian is classified as distracted, in response to determining that the pedestrian awareness level is below the predefined threshold.