Abstract: The present application is concerned with an oral scanner system having an oral scanner being structured and/or arranged for performing a scanning procedure of at least a portion of an oral cavity, a processor being coupled with a memory in which oral health sensor data and/or oral health data relating to at least one previous scanning procedure performed with the oral scanner and/or in which oral care activity data relating to at least one previous oral care activity procedure performed with an oral care device is stored, wherein the processor is structured and/or arranged to determine at least one scanning procedure parameter for influencing a next scanning procedure in dependance on the stored data and/or to determine at least one scanning procedure guidance in dependance on the stored data, where the scanning procedure guidance comprises at least one automatic feedback provided to the user by a feedback unit immediately before and/or during the next scanning procedure.

Abstract: The present application is concerned with an oral scanner system an oral scanner being structured and/or arranged for performing a scanning procedure of at least a portion of an oral cavity of a subject, a position detector structured and/or arranged for outputting position sensor data relating to a discrete position or location at which the oral scanner currently performs the scanning procedure, a processor structured and/or arranged to receive at least the position sensor data, to process the position sensor data to determine a scanning discrete position or location within the at least portion of the oral cavity at which the oral scanner is currently performing the scanning procedure, and to compute a scanning procedure progress value being in a range between a start progress value and an end progress value for each of at least two discrete positions or locations based at least on the determined scanning discrete position or location at which the oral scanner is currently performing the scanning procedure,

Abstract: A method for training a segmentation model is provided. The method includes using first training images to train a segmentation model. The method includes using second training images to train an image generator. The method includes inputting real images into the segmentation model to generate predicted annotation images. The method includes inputting the predicted annotation images into the image generator to generate fake images. The method includes updating the segmentation model and the image generator according to a loss caused by differences between the real images and the fake images.

Abstract: A brightness control device for controlling light-emitting diodes (LEDs) during a video recording performed by an image sensor. The brightness control device includes a pulse width modulation (PWM) signal output unit and a brightness control signal generation unit. The signal output unit is configured to provide at least one PWM signal. The brightness control signal generation unit is configured to generate a brightness control signal according to an exposure signal of the image sensor and the at least one PWM signal.

Abstract: An oral-area positioning device is provided in the invention. The oral-area positioning device includes a storage circuit, a positioning circuit and a calculation circuit. The storage circuit stores information corresponding to a plurality of oral areas. The positioning circuit obtains a target image from an oral-image extracting device, and obtains a first position estimation result according to the information corresponding to the plurality of oral areas and a first algorithm. The positioning device obtains a second position estimation result at least according to the information corresponding to the plurality of oral areas, a second algorithm and a reference image position of a reference image, wherein the reference image position is one of the oral areas. The calculation circuit generates a third position estimation result according to the first position estimation result and the second position estimation result.

Abstract: An image positioning device is provided in the invention. The image positioning device includes a calculation circuit and a positioning circuit. The calculation circuit obtains a plurality of images from an image capturing device and classifies the images into a plurality of main groups based on a first algorithm, wherein each main group corresponds to a different area and the calculation circuit classifies the images of each main group into a plurality of sub-groups based on a feature of each image of each main group and a clustering algorithm. The positioning circuit is coupled to the calculation circuit. The positioning circuit positions each sub-group in the area corresponding to each main group based on the relative position relationship between each sub-group of each main group.

Abstract: A distinguishing device for dental plaque and dental calculus includes a light-emitting diode, an image sensing unit, and a processor. The light-emitting diode movies in a first direction and is separated from teeth in an oral cavity by a predetermined distance in a second direction. The second direction is perpendicular to the first direction. The light-emitting diode generates a blue light to illuminate the teeth, so that dental plaque on the teeth generates a first autofluorescence and dental calculus on the teeth generates a second autofluorescence. The image sensing unit is configured to sense the first autofluorescence and the second autofluorescence. The processor is coupled to the image sensing unit to distinguish a dental plaque area from a dental calculus area on the teeth according to the first autofluorescence and the second autofluorescence.

Abstract: Digital image stitching systems and methods are disclosed herein for generating one or more panoramic image views. A plurality of digital images depicting a target feature within an application area are captured by a camera of a scanner device. Motion data is captured, by a sensor coupled to the scanner device, as the scanner device moves relative to the target feature, where relative position data, corresponding to the plurality of digital images, is determined based on the motion data. An angle or position is generated for a first image relative to a second image of the plurality of images, and, based on image matching of the angle or the position of the second image with respect to the first image, a panoramic image view is generated depicting the target feature in a wider field of view of the application area than either the first image or the second image.

Abstract: An image classifying device is provided in the invention. The image classifying device includes a storage device, a calculation circuit and a classifying circuit. The storage device stores information corresponding to a plurality of image classes. The calculation circuit obtains a target image from an image extracting device and obtains the feature vector of the target image. The calculation circuit obtains a first estimation result corresponding to the target image based on the information corresponding to the plurality of image classes and the feature vector and obtains a second estimation result corresponding to the target image based on a reference image, wherein the reference image corresponds to one of the image classes. The classifying circuit adds the target image into one of the image classes based on the first estimation result and the second estimation result.

Abstract: An image positioning device is provided in the invention. The image positioning device includes a calculation circuit and a positioning circuit. The calculation circuit obtains a plurality of images from an image capturing device and classifies the images into a plurality of main groups based on a first algorithm, wherein each main group corresponds to a different area and the calculation circuit classifies the images of each main group into a plurality of sub-groups based on a feature of each image of each main group and a clustering algorithm. The positioning circuit is coupled to the calculation circuit. The positioning circuit positions each sub-group in the area corresponding to each main group based on the relative position relationship between each sub-group of each main group.

Abstract: A method for distinguishing plaque and calculus is provided. The method is used in a device and includes the following steps: emitting, by a blue light-emitting diode, blue light to illuminate teeth in an oral cavity, wherein the blue light is used to generate autofluorescence of plaque and calculus on the teeth; sensing, by an image sensor, the autofluorescence of plaque and calculus; and distinguishing, by a processor, a plaque area and a calculus area on the teeth based on the autofluorescence.

Abstract: An oral-area positioning device is provided in the invention. The oral-area positioning device includes a storage device, a positioning circuit and a calculation circuit. The storage device stores information corresponding to a plurality of oral areas. The positioning circuit obtains a target image from an oral-image extracting device, and obtains a first position estimation result according to the information corresponding to the plurality of oral areas and a first algorithm. The positioning device obtains a second position estimation result at least according to the information corresponding to the plurality of oral areas, a second algorithm and a reference image position of a reference image, wherein the reference image position is one of the oral areas. The calculation circuit generates a third position estimation result according to the first position estimation result and the second position estimation result.

Abstract: An insulin-dosage detection device is arranged on a rotation member of an insulin injection pen having an injection button. The rotation variation of the rotation member corresponds to the injection dosage of the insulin injection pen. The insulin-dosage detection device has a circuit, a detection button, and a processor. The circuit, arranged on the rotation member of the insulin injection pen, outputs electronic signals in response to rotation of the rotation member. The detection button is connected to the injection button. The rotation member of the insulin injection pen rotates in response to the detection button and the injection button being pressed. The circuit rotates along with the rotation member. The processor, coupled to the circuit, calculates the rotation variation of the rotation member according to a first electronic signal and a second electronic signal respectively output from the circuit before and after the rotation of the circuit.

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 information collection method for an injection pen includes several steps as follows. The action of the pressing knob is sensed to determine whether the rotation information of the pressing knob is obtained. The traveling movement of the injection pen is sensed to determine whether the movement information of the injection pen is obtained. A determination is made that the traveling movement of the injection pen is conformed as an intending injection action according to the rotation information of the pressing knob and the movement information of the injection pen. When the traveling movement of the injection pen is conformed as the intending injection action, an actual injection dose that the injection content is pushed outwards from the injection pen is calculated according to the rotation information of the pressing knob. The actual injection dose is recorded.

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: A method for distinguishing plaque and calculus is provided. The method is used in a device and includes the following steps: emitting, by a blue light-emitting diode, blue light to illuminate teeth in an oral cavity, wherein the blue light is used to generate autofluorescence of plaque and calculus on the teeth; sensing, by an image sensor, the autofluorescence of plaque and calculus; and distinguishing, by a processor, a plaque area and a calculus area on the teeth based on the autofluorescence.

Abstract: An image processing method for a fluorescence reaction region of teeth. The image processing method includes emitting blue light from a light source to illuminate the teeth in a mouth, so that the teeth generate fluorescence; capturing a first teeth image of the teeth by an image capturing unit; separating the first teeth image into a first red-value image, a first green-value image, and a first blue-value image by a processing unit; transforming the first red-value image into a second red-value image by the processing unit using a pixel value transforming function; and combining the second red-value image, the first green-value image, and the first blue-value image into a second teeth image by the processing unit.

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: 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.