Abstract:
A method for dynamically adjusting fluorescent imaging is provided. The method is used in a device and includes the following steps: emitting, by a light emitting diode, light to illuminate teeth in an oral cavity, wherein the light is used to generate fluorescence from the teeth; filtering, by an optical filter, the fluorescence; receiving, by an image sensor, a signal and adjusting a gain value of an analog-to-digital converter according to the signal; converting, by the analog-to-digital converter, the filtered fluorescence into a digital signal and adjusting the digital signal according to the gain value; and generating, by a processor, an output image signal that corresponds to the gain value from the digital signal.
Abstract:
A communication system and method are provided. In the communication system, a first electrical device has an end point which is configured to connect to a plurality of 3G dongles, wherein the 3G dongles have different IP addresses; a cloud server integrates the IP addresses to generate an integrated IP address when the cloud server detects that the first electrical device is connected to the 3G dongles; and a second electrical device transmits data packets with the first electrical device via the integrated IP address through the cloud server.
Abstract:
A communication system and method are provided. In the communication system, a first electrical device has an end point which is configured to connect to a plurality of 3G dongles, wherein the 3G dongles have different IP addresses; a cloud server integrates the IP addresses to generate an integrated IP address when the cloud server detects that the first electrical device is connected to the 3G dongles; and a second electrical device transmits data packets with the first electrical device via the integrated IP address through the cloud server.
Abstract:
A tooth-position recognition system includes an electronic device and a calculation device. The electronic device includes a first camera. The first camera is configured to capture a plurality of tooth images. The calculation device includes a second camera and a processor. The second camera is configured to capture a user image. The processor is configured to receive the tooth images, compare the corresponding position of each pixel in each tooth image to generate a depth map, and input the tooth images, the depth map, and a plurality of first tooth-region identifiers into a tooth deep-learning model. The tooth deep-learning model outputs a plurality of deep-learning probability values that are the same in number as the first tooth-region identifiers. The processor inputs the user image and the plurality of second tooth-region identifiers into a user-image deep-learning model.
Abstract:
An image-processing method for marking plaque fluorescent reaction areas is provided, including: obtaining a first RGB image of a mouth region; obtaining a second RGB image of the mouth region; respectively converting the first RGB image and the second RGB image into a first HSV image and a second HSV image; obtaining a first average brightness value of the first HSV image and a second average brightness value of the second HSV image; normalizing the first average brightness value or the second average brightness value according the first average brightness value and the second average brightness value to obtain a normalized image; converting the normalized image into a third RGB image, and obtaining a plurality of pixel points of the dental plaque according to the third RGB image and the first RGB image or the second RGB image; and marking the pixel points in the third RGB image.
Abstract:
A method for improving the efficiency of reconstructing a three-dimensional model is provided. The method includes: dividing a series of different Gray code binary illumination patterns into a plurality of groups; converting binary values of Gray code binary illumination patterns in each group to a plurality of sets of two specific values to generate decimal illumination patterns corresponding to the specific values; overlapping the decimal illumination patterns in each group to a grayscale illumination pattern; using a projector to project each grayscale illumination pattern onto an object from a projection direction; using a camera to capture one or more object images of the object; reverting the object images to non-overlapping Gray code binary images corresponding to the object images; and reconstructing the depth of the object according to the non-overlapping Gray code binary images.
Abstract:
A video conferencing system is provided. The video conferencing system includes: a first video conferencing terminal; a second video conferencing terminal, for establishing a video conference with the first video conferencing terminal via a peer-to-peer connection; and a management server. When a user needs to add a third video conferencing terminal to the video conference to establish a multi-way video conference, the first video conferencing terminal and the second video conferencing terminal automatically terminate the peer-to-peer connection, and connect to the third video conferencing terminal through the management server to perform the multi-way video conference.
Abstract:
An acoustic echo cancellation (AEC) system includes a remote device, for capturing a remote captured sound, a server coupled to the remote device, and a local device coupled to the server. The server transmits the remote captured sound from the remote device to the local device. The local device receives, stores and plays the remote captured sound as a local playback sound. An echo is generated from reflection of the local playback sound. The local device captures the echo and a local sound into a local captured sound, and transmits both the remote captured sound and the local captured sound to the server. The server performs AEC on the local captured sound by using the remote captured sound from the local device and transmits the AEC processed local captured sound to the remote device.