Abstract: The present invention provides a system for detecting whether a subject having a target suffers from an Alzheimer's disease. The system includes a multi-harmonic generation microscope and a processor. The multi-harmonic generation microscope images the target by a second harmonic generation (SHG) and a third harmonic generation (THG) to respectively obtain an SHG image and a THG image. The processor couples to the multi-harmonic generation microscope and configures to add a first color to the SHG image and a second color to the THG image to respectively obtain a color-added SHG image and a color-added THG image, and combine the color-added SHG image and the color-added THG image to obtain a combined image, wherein the combined image is used to determine whether the subject suffers from the Alzheimer's disease.

Abstract: A method and system for image processing are provided in the present disclosure. The method may include obtaining a plurality of source images generated by a plurality of imaging sensors. The method may also include processing each of the plurality of source images by: retrieving a plurality of source image blocks from the source image according to block position information associated with the corresponding imaging sensor; generating, for each of the plurality of source image blocks, a target image block based on the source image block; and forming a target image based on the generated target image blocks. The method may further include generating a combined image based on the target images.

Abstract: A method and an apparatus for detecting a usage status of a parking space, an electronic device, and a storage medium are disclosed. The method comprises: obtaining a monitored image of a to-be-detected parking space; identifying lane line position information of the to-be-detected parking space from the monitored image; identifying vehicle information from the monitored image, wherein the vehicle information comprises vehicle position information; and determining a usage status of the to-be-detected parking space based on a positional relationship between the lane line position information and the vehicle position information. Determining the usage status of the to-be-detected parking space based on the positional relationship between the lane line position information and the vehicle information is less affected by external environmental factors, which thus may improve the accuracy of a detection result of the usage status of the parking space.

Abstract: A method includes receiving a directive from a user to find an object in a geographical area, wherein the object is identified with an input label selected from a set of labels, obtaining sensor data in response to the directive for a real world physical object in the geographical area using one or more sensors, processing the sensor data with a plurality of automatic target recognition (ATR) algorithms to assign a respective ATR label from the set of labels and a respective confidence level to the real world physical object, and receiving modeled relationships within the set of labels using a probabilistic model based on a priori knowledge encoded in a set of model parameters. The method includes inferring an updated confidence level that the real world physical object actually corresponds to the input label based on the ATR labels and confidences and based on the probabilistic model.

Abstract: A method and a system for determining a center of resistance point of a tooth for orthodontic treatment planning are provided. The method comprises: obtaining a tooth mesh from image data associated with a tooth crown of a patient; identifying a mesiodistal center of the tooth crown; determining a reference plane in the image data to extend through the mesiodistal center; determining an intersection curve based on an intersection of the reference plane and the tooth mesh, the intersection curve following a shape of the surface of the crown at the reference plane; determining a tooth axis of the tooth crown based on the intersection curve; determining a crown height of the tooth crown based on the tooth axis; and determining the center of resistance of the tooth based on the determined crown height and the determined tooth axis.

Abstract: An image processing apparatus includes detecting means for detecting a first detected region and a second detected region from an input image, on the basis of a first detection criterion and a second detection criterion, respectively; image setting means for setting, as a target image subjected to correction, an image including the first detected region, and setting, as a reference image that is referred to in the correction, an image including the second detected region; accepting means for accepting, from a user, designation of a region in the target image and a correction instruction for the designated region; correction region setting means for identifying, in the reference image, a region corresponding to the designated region, and for setting a to-be-corrected region on the basis of the identified region and the second detected region; and correcting means for correcting the first detected region in the target image on the basis of the to-be-corrected region set in the reference image.

Abstract: A system and a method measure volumetric changes of brain structures. The method includes initializing an intensity value of all voxels of a 3D voxel dataset representing the brain of a subject to an initial value preferentially equal to 0. For all voxels that belong to a segmented brain structure for which reference data of a longitudinal reference model exists, automatically executing the following steps: calculating a deviation of a volume change for the segmented brain structure from the longitudinal reference model, normalizing the deviation to obtain a quantitative value of the volume change on a same scale for voxel's belonging to different brain structures; and setting the intensity value of the voxels to the previously obtained quantitative value Q. The voxels of the 3D voxel dataset are displayed in a form of a longitudinal deviation map.

Abstract: An object dataset creation or modification mechanism is provided for object dataset creation or modification using a labeled action-object video. For a plurality of frames of the labeled action-object video, an identification is made of a subset of frames where a bounding box object (BBO) exists. BBOs in the subset of frames where a BBO exists are pruned to identify sufficiently distinct BBOs thereby forming a set of pruned BBOs. For each pruned BBO in the set of pruned BBOs: an information addition score is determined; the information addition score is assessed; responsive to the information addition score being positively assessed, the pruned BBO is added to an object dataset; and, responsive to the information addition score being negatively assessed, the pruned BBO is discarded.

Abstract: A computing system generates a training data set for training the prediction model to detect defects present in a target surface of a target specimen and training the prediction model to detect defects present in the target surface of the target specimen based on the training data set. The computing system generates the training data set by identifying a set of images for training the prediction model, the set of images comprising a first subset of images. A deep learning network generates a second subset of images for subsequent labelling based on the set of images comprising the first subset of images. The deep learning network generates a third subset of images for labelling based on the set of images comprising the first subset of images and the labeled second subset of images. The computing system continues the process until a threshold number of labeled images is generated.

Abstract: The present invention discloses a system for automated vehicles license plates characters segmentation and recognition comprising an imaging processor connected to at least one image grabber module or camera. The image grabber module captures images of the vehicles and forwards it to said connected imaging processor and the imaging processor segments and recognizes the vehicles license plates character region including the region with deformed license plates characters in the captured vehicle images by involving binarization of maximally stable external regions corresponding to probable license plate region in the captured vehicle images.

Abstract: A method for increasing spatial resolution of a MS image using a PAN image. For a portion of the scene, values of parameters of a scene model are obtained according to a resemblance between a simulated MS reflectance and the MS reflectance. A relative variation in the simulated MS reflectance is determined with respect to a simulated PAN reflectance near the values of parameters obtained. A difference between the PAN reflectance and a reflectance of a PAN image with reduced spatial resolution is estimated. An MS image with increased spatial resolution is determined, by adding to the MS reflectance a correction corresponding to a product of this difference and this relative variation. A corresponding image-processing system is also provided.

Abstract: Disclosed is a ship identity recognition method based on the fusion of AIS data and video data, comprising: collecting a ship sample to train a ship target classifier; performing, using the ship target classifier, ship target detection on a video frame collected by a gimbal camera; performing a comparison with a recognized ship library to filter a recognized ship; acquiring AIS data and filtering same across time and spatial scales; predicting the current position of an AIS target using a linear extrapolation method and converting the current position to an image coordinate system; performing position matching between a target to be matched and the converted AIS target; and performing feature extraction on the successfully matched target and storing the extracted feature, together with ship identity information, into the recognized ship library.

Abstract: An information processing apparatus determines, for an image to be processed including a first region having a first image quality and a second region other than the first region having a second image quality lower than the first image quality, whether or not a difference in image quality between the first image quality and the second image quality is equal to or larger than a predetermined value, converts, in a case where the determination unit determines that the difference between the first image quality and the second image quality is equal to or larger than the predetermined value, the image of the second region into an image having a third image quality higher than the second image quality, and generates a combined image by using the post-conversion image having the third image quality and the image of the first region.

Abstract: Methods, systems, and non-transitory computer-readable media for generating augmented data to train a deep neural network to detect traffic lights in image data. The method includes receiving a plurality of real roadway scene images and selecting a subset of the plurality of real roadway scene images. The method also includes selecting an image from the subset and determining a distribution indicting how likely each location in the selected image can contain a traffic light. The method further includes selecting a location in the selected image by sampling the distribution and superimposing a traffic light image onto the selected image at the selected location to generate an augmented roadway scene image. The method also includes processing each image in the subset to generate a plurality of augmented roadway scene images. The method further includes training a deep neural network model using the pluralities of real and augmented roadway scene images.

Abstract: To provide a camera calibration device and a camera calibration method which can easily calibrate a relationship between a machine coordinate system of a machine tool and a camera coordinate system of a camera. A camera calibration device calibrates an imaging means of a machine tool, the machine tool includes: a touch probe which acquires one point whose machine coordinates are known; a camera which images the one point and a pattern including a feature used for calibration; and a drive mechanism which moves a table or a spindle in two orthogonal directions and an image obtained by imaging the one point and the pattern and images obtained by imaging the pattern or/and the one point when the table or a machining machine is moved in the two directions are used to calculate an external parameter by calculating a positional posture relationship between the machine coordinate system and the pattern.

Abstract: A system and method of multi-sensor object detection using point cloud projection is provided. The system uses a LiDAR system and a monocular camera to obtain point cloud data and image data of an object, respectively. A 3D bounding box is determined for the point cloud data and a 2D bounding box is determined for the image data. The LiDAR and camera are jointly calibrated, and the 3D object bounding box of the point cloud data is mapped to the corresponding 2D object bounding box of the image data. The system performs decision-level fusion on the point cloud data and the image data followed by a pixel-level fusion of the 3D object bounding box and the 2D object bounding box.

Abstract: A method for training a locally interpretable model includes obtaining a set of training samples and training a black-box model using the set of training samples. The method also includes generating, using the trained black-box model and the set of training samples, a set of auxiliary training samples and training a baseline interpretable model using the set of auxiliary training samples. The method also includes training, using the set of auxiliary training samples and baseline interpretable model, an instance-wise weight estimator model. For each auxiliary training sample in the set of auxiliary training samples, the method also includes determining, using the trained instance-wise weight estimator model, a selection probability for the auxiliary training sample. The method also includes selecting, based on the selection probabilities, a subset of auxiliary training samples and training the locally interpretable model using the subset of auxiliary training samples.

Abstract: A system according to the present disclosure may include a display unit, a processor communicatively coupled to the display unit and to an ultrasound imaging apparatus for generating an image from ultrasound data representative of a bodily structure and fluid flowing within the bodily structure. The processor may be configured to generate vector field data including axial and lateral (or transverse) velocity components of the fluid flowing within the bodily structure, calculate velocity profiles for a plurality of locations along a wall of the bodily structure based on the axial and lateral velocity components, generate wall shear stress (WSS) visualization data based, at least in part, on the velocity profiles, and cause the display unit to concurrently display the image including the bodily structure overlaid with the WSS visualization data.

Abstract: A Convolution Multiply and Accumulate-Xtended (CMAC-X) system (102) for performing a convolution operation with functional safety mechanism is disclosed. The CMAC-X system (102) receives image data pertaining to an image. The image data comprises a set of feature matrix, a kernel size and depth information. Further, the CMAC-X system (102) generates a convoluted data based on convolution operation for each feature matrix, The CMAC-X system (102) performs an accumulation of the convoluted data to generate accumulated data, when the convolution operation for each feature matrix is performed. The CMAC-X system (102) further performs an addition of a predefined value to the accumulated data to generate added data. Further, the CMAC-X system (102) filters the added data. Further, the CMAC-X system (102) comprises a functional safety unit to verify a functionality of the CMAC-X system (102), thereby performing the convolution operation of the image with functional safety mechanism.

Abstract: An adhered substance detection apparatus of an embodiment includes a calculator and a determiner. The calculator calculates an edge feature for each cell based on edge vectors of pixels within the cell in a captured image, and further calculates a region feature for each unit region based on the calculated edge features of the cells within the unit region. The determiner determines an adherence state of an adhered substance on a lens of a camera based on the region feature. The calculator calculates, as the region feature, number of the cells having an edge strength of zero. When the number of the cells having the zero edge strength is equal to or greater than a predetermined number in a predetermined attention area in the captured image, the determiner determines not to perform a determination for detecting whether the lens of the camera is entirely covered by the adhered substance.