Techniques are described for passive three-dimensional (3D) object authentication based on image sizing, such as for biometric facial recognition. For example, during a registration routine, an imaging system captures images of a registering user's face at multiple distances. The images can be processed to extract registration dimensions, including individual deterministic structural dimensions, dimensional relationships that are static over changes in imaging distance, and dimensional relationships that changes predictably over changes in imaging distance. During an authentication routine, the imaging system again captures authentication images of an authenticating user's face (purportedly the previously registered user) at some authentication imaging distance and processes the images to extract authentication dimensions. Expected and actual dimensional quantities are computed from the authentication and registration dimensions and are compared to determine whether the authenticating user's face appears to be authorized as previously registered and/or is a spoof.

A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations to accept ecosystem data and detect, analyze, and notify a user about a species in an environment. The system analysis and notification may include impact determination of the species on the environment and shall learn from the received and analyzed data, bringing intelligence to the system.

Real-time evaluation and enhancement of image quality prior to capturing an image of a document on a mobile device is provided. An image capture process is initiated on a mobile device during which a user of the mobile device prepares to capture the image of the document, utilizing hardware and software on the mobile device to measure and achieve optimal parameters for image capture. Feedback may be provided to a user of the mobile device to instruct the user on how to manually optimize certain parameters relating to image quality, such as the angle, motion and distance of the mobile device from the document. When the optimal parameters for image capture of the document are achieved, at least one image of the document is automatically captured by the mobile device.

Real-time evaluation and enhancement of image quality prior to capturing an image of a document on a mobile device is provided. An image capture process is initiated on a mobile device during which a user of the mobile device prepares to capture the image of the document, utilizing hardware and software on the mobile device to measure and achieve optimal parameters for image capture. Feedback may be provided to a user of the mobile device to instruct the user on how to manually optimize certain parameters relating to image quality, such as the angle, motion and distance of the mobile device from the document. When the optimal parameters for image capture of the document are achieved, at least one image of the document is automatically captured by the mobile device.

A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization method may be used to provide input to an HILN (H, I, and/or L, or N) detection method. The characterization method includes capturing one or more images of a labeled specimen container including a serum or plasma portion from multiple viewpoints, processing the one or more images to provide segmentation data including identification of a label-containing region, determining a closest label match of the label-containing region to a reference label configuration selected from a reference label configuration database, and generating a combined representation based on the segmentation information and the closest label match. Using the combined representation allows for compensation of the light blocking effects of the label-containing region. Quality check modules and testing apparatus and adapted to carry out the method are described, as are other aspects.

Provided are a leukocyte detection method, a system, an electronic device and a computer readable medium. The method comprises: acquiring a microcirculation image (S1); determining a location of an intra-tubular space of a capillary vessel from the microcirculation image (S2); and determining a leukocyte index based on image information of the intra-tubular space of the capillary vessel (S3).

Provided are a leukocyte detection method, a system, an electronic device and a computer readable medium. The method comprises: acquiring a microcirculation image (S1); determining a location of an intra-tubular space of a capillary vessel from the microcirculation image (S2); and determining a leukocyte index based on image information of the intra-tubular space of the capillary vessel (S3).

An inpainting method includes retrieving image information at an electronic device, where the image information identifies an area within an image. The method also includes retrieving, using the electronic device, semantic information including a plurality of semantic classes and a semantic class distribution for each semantic class of the plurality of semantic classes. The method further includes generating semantic codes associated with different portions of the image based on the image information and the semantic information. In addition, the method includes constructing the area within the image by generating image content based on the semantic information.

Systems, methods, and computer program products are provided for segmenting a brain tumor from various MRI sequencing techniques. A plurality of MRI sequences of a head of a patient are received. Each MRI sequence includes a T1-weighted with contrast image, a Fluid Attenuated Inversion Recovery (FLAIR) image, a T1-weighted image, and a T2-weighted image. Each image of the plurality of MRI sequences is registered to an anatomical atlas. A plurality of modified MRI sequences are generated by removing a skull from each image in the plurality of MRI sequences. A tumor segmentation map is determined by segmenting a tumor within a brain in each image in the plurality of modified MRI sequences. The tumor segmentation map is applied to each of the plurality of MRI sequences to thereby generate a plurality of labelled MRI sequences.

Systems, methods, and computer program products are provided for segmenting a brain tumor from various MRI sequencing techniques. A plurality of MRI sequences of a head of a patient are received. Each MRI sequence includes a T1-weighted with contrast image, a Fluid Attenuated Inversion Recovery (FLAIR) image, a T1-weighted image, and a T2-weighted image. Each image of the plurality of MRI sequences is registered to an anatomical atlas. A plurality of modified MRI sequences are generated by removing a skull from each image in the plurality of MRI sequences. A tumor segmentation map is determined by segmenting a tumor within a brain in each image in the plurality of modified MRI sequences. The tumor segmentation map is applied to each of the plurality of MRI sequences to thereby generate a plurality of labelled MRI sequences.