Abstract: A light emission apparatus includes a laser diode configured to emit a light; a laser driver electrically coupled to the laser diode, the laser driver being configured to drive the laser diode to generate the light; and an optical module arranged to receive the light emitted by the laser diode, the optical module comprising at least one optical element and being configured to adjust the light and emits a transmitting light; wherein the transmitting light emits from the optical module with an illumination angle and the optical module adjusts the light to vary the illumination angle.

Abstract: An image processing system includes an ophthalmoscope device and a processor. The ophthalmoscope device is configured to obtain a color fundus image. The processor is configured to receive the color fundus image; generate a blood vessel segmentation image that corresponds to the color fundus image using a computer vision algorithm or a deep learning model; preprocess the color fundus image and the blood vessel segmentation image to obtain an initial input image; and input the initial input image into a convolutional neural network. The convolutional neural network outputs a value. In addition, the processor generates fundus image analysis information from the cup-to-disc ratio and the value.

Abstract: An image processing system includes an ophthalmoscope device and a processor. The ophthalmoscope device is configured to obtain a color fundus image. The processor is configured to receive the color fundus image; generate a blood vessel segmentation image that corresponds to the color fundus image using a computer vision algorithm or a deep learning model; preprocess the color fundus image and the blood vessel segmentation image to obtain an initial input image; and input the initial input image into a convolutional neural network. The convolutional neural network outputs a value. In addition, the processor generates fundus image analysis information from the cup-to-disc ratio and the value.

Abstract: Embodiments of the present disclosure provide a method for evaluating (e.g., estimating) an efficiency of a machine vision, which includes: obtaining an image, wherein the image presents a plurality of objects which include a first object and a second object; performing an image recognition on the images by the machine vision to obtain a prediction block corresponding to at least one of the first object and the second object; merging a first standard block corresponding to the first object and a second standard block corresponding to the second object to obtain a third standard block; and obtaining evaluation information according to the third standard block and the prediction block, wherein the evaluation information reflects a prediction efficiency of the machine vision for the objects in the image.

Abstract: A method and a system for evaluating a cardiac status, an electronic device and an ultrasonic scanning device are provided. The method includes: obtaining at least first image, wherein each of the first images is a two-dimensional image and includes a first cardiac image; training a depth learning model by the first image; and analyzing at least one second image by using the trained depth learning model to automatically evaluate a cardiac status of a user, wherein each of the second image is the two-dimensional image and includes a second cardiac image.

Abstract: Embodiments of the present disclosure provide a method for evaluating (e.g., estimating) an efficiency of a machine vision, which includes: obtaining an image, wherein the image presents a plurality of objects which include a first object and a second object; performing an image recognition on the images by the machine vision to obtain a prediction block corresponding to at least one of the first object and the second object; merging a first standard block corresponding to the first object and a second standard block corresponding to the second object to obtain a third standard block; and obtaining evaluation information according to the third standard block and the prediction block, wherein the evaluation information reflects a prediction efficiency of the machine vision for the objects in the image.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: A system and method of detecting tampering at an automatic teller machine includes detecting start and end indicators of a transaction. A representation of a scene at the teller machine, prior to the start of the transaction can be compared to a representation of the scene after the end of the transaction. Variations therebetween can indicate tampering at the machine.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: Blocking zones of a surveillance system are configured to prevent false alarms caused by motion within the zones, while allowing tracking of objects through the zones. An object that first appears within a blocking zone is not considered to be a reportable object until the object leaves the zone. All reportable objects are tracked, without regard to the blocking zones. Objects that remain within their initial blocking zone are not deemed to be reportable objects, and therefore do not generate alarms. If an object initially appears within overlapping zones, the object is not deemed to be reportable until it leaves each of the zones at least once. The blocking zones do not mask the video images, and thus a complete record of activity is available for forensic purposes.

Abstract: An open digital watermark system and methodology having various features for unifying watermark production and processing among diverse user multimedia terminals (112), such as set top box, that may be OPIMA compliant. In accordance with specific aspects, intentional image warping is employed to combat pirating, the analog video channel used to download programming, packet signature implemented for watermark insertion by pixel replacement and use of the data stream made to reduce local data processing and storage.

Abstract: A video interface kernel with a defined application program interface includes each of a plurality of core functions for interfacing with video equipment and video processing subsystems. The core functions include such functions as video capture and video output, video recording and playback, and event notification. Functions of the video interface kernel also include video analysis functions and/or interfaces to analysis subsystems, as well as interfaces to point-of-sale terminals, access control systems, and location tracking systems. An intelligent video management module facilitates managing the interactions among the other modules of the kernel, further simplifying the application level interface.

Abstract: To calibrate images from an overhead camera, two equal-length reference lines at different heights relative to the floor plane are imaged. By comparing the resultant image-width of each of these lines in the view provided by the camera, the effective focal point of the camera is determined. In a preferred embodiment, a doorframe is used to provide equal-length lines at different heights parallel to the floor. The threshold of the doorway at the floor plane is used as a reference plane, and a parallel calibration line at a known/measured height in the doorway is defined. The image produced by a vertically oriented camera of these two equal length lines will show a longer line at the elevated position, the different widths of the images of these lines being dependent upon the camera's effective focal point. From these two projections of the equal-length lines at different heights, the camera's focal point distance from the reference floor plane is determined.

Abstract: A system and method of detecting tampering at an automatic teller machine includes detecting start and end indicators of a transaction. A representation of a scene at the teller machine, prior to the start of the transaction can be compared to a representation of the scene after the end of the transaction. Variations therebetween can indicate tampering at the machine.

Abstract: An image processing system (250) and method (300) are disclosed for correcting a head pose in a video phone image, so that a frontal view is presented on a display. A disclosed head pose corrector (250) estimates the orientation of a head pose and adjusts the orientation of the head pose, if necessary, to present a frontal view. The orientation of the head pose is adjusted by generating a three dimensional model of the face surface and adjusting the orientation of the three dimensional face model to provide the desired frontal view. The head pose corrector (250) may be included in a video phone (100) to correct the head pose of transmitted or received images (or both) or may be included in a server on a network to automatically adjust the head shots of one or more participants to a video phone communication.

Abstract: A method and system is configured to characterize regions of an environment by the likelihoods of transition of a target from each region to another. The likelihoods of transition between regions is preferably used in combination with conventional object-tracking algorithms to determine the likelihood that a newly-appearing object in a scene corresponds to a recently-disappeared target. The likelihoods of transition may be predefined based on the particular environment, or may be determined based on prior appearances and disappearances in the environment, or a combination of both. The likelihoods of transition may also vary as a function of the time of day, day of the week, and other factors that may affect the likelihoods of transitions between regions in the particular surveillance environment.

Abstract: A video processing and analysis system is coupled to a building management and control system. The video processing system provides traffic, occupancy, and other information derived from video images of sections of the building and its environs to the building management and control systems. The building systems use this information in a variety of business management applications, including maintenance scheduling, asset replacement, elevator dispatching, HVAC and lighting control, and so on, to reduce operational or maintenance costs, expedite emergency procedures, improve service levels of building facilities, and regulate the building's environmental conditions.

Abstract: A method and system is configured to characterize regions of an environment by the likelihoods of transition of a target from each region to another. The likelihoods of transition between regions is preferably used in combination with conventional object-tracking algorithms to determine the likelihood that a newly-appearing object in a scene corresponds to a recently-disappeared target. The likelihoods of transition may be predefined based on the particular environment, or may be determined based on prior appearances and disappearances in the environment, or a combination of both. The likelihoods of transition may also vary as a function of the time of day, day of the week, and other factors that may affect the likelihoods of transitions between regions in the particular surveillance environment.

Abstract: A method and system is configured to characterize regions of an environment by the likelihoods of transition of a target from each region to another. The likelihoods of transition between regions is preferably used in combination with conventional object-tracking algorithms to determine the likelihood that a newly-appearing object in a scene corresponds to a recently-disappeared target. The likelihoods of transition may be predefined based on the particular environment, or may be determined based on prior appearances and disappearances in the environment, or a combination of both. The likelihoods of transition may also vary as a function of the time of day, day of the week, and other factors that may affect the likelihoods of transitions between regions in the particular surveillance environment.