Abstract: A character recognition method includes the following operations: determining that the image of character to be identified corresponds to a matching character of several registered characters according to several vector distances to be identified between a vector of an image of character to be identified and several vectors of several registered character images of several registered characters, and storing a matching vector distance between the vector of the image of character to be identified and a vector of the matching character by a processor; and storing a data of the matching character according to the image of character to be identified when the matching vector distance is less than a vector distance threshold by the processor.

Abstract: The present disclosure provides a method of mesh generation for an RTM process, including operations of: obtaining a geometry of a target object; generating a solid mesh of the target object according to the geometry; obtaining material characteristics of the target object; assembling a runner mesh with the solid mesh, wherein the runner mesh has grid dimensions different from those of the solid mesh; determining process parameters of the RTM process; and generating a forecasted result of the RTM process according to the solid mesh, the runner mesh, the process parameters, and the material characteristics. Generating the solid mesh includes operations of: dividing the geometry into modules; generating a first and second modular meshes corresponding to a first and second modules, wherein the second modular mesh abuts the first modular mesh, and the second modular mesh has grid dimensions different from those of the first modular mesh.

Abstract: The present disclosure provides a method of mesh generation for an RTM process, including operations of: obtaining a geometry of a target object; generating a solid mesh of the target object according to the geometry; obtaining material characteristics of the target object; assembling a runner mesh with the solid mesh, wherein the runner mesh has grid dimensions different from those of the solid mesh; determining process parameters of the RTM process; and generating a forecasted result of the RTM process according to the solid mesh, the runner mesh, the process parameters, and the material characteristics. Generating the solid mesh includes operations of: dividing the geometry into modules; generating a first and second modular meshes corresponding to a first and second modules, wherein the second modular mesh abuts the first modular mesh, and the second modular mesh has grid dimensions different from those of the first modular mesh.

Abstract: A method of data augmentation is provided. The method includes the following operations: selecting an original image from an original dataset including label data configured to indicate a labeled area of the original image; selecting at least part of content, located in the labeled area, of the original image as a first target image; generating a first sample image according to the first target image, in which the first sample image includes the first target image and a first border pattern different from the first target image, and the content, located in the labeled area, of the original image is free from including at least part of the first border pattern; and incorporating the first sample image into a sample dataset, in which the sample dataset is configured to be inputted to a machine learning model.

Abstract: An object detection method and an associated electronic device are provided, wherein the object detection method includes: utilizing an image processing circuit to determine whether motion occurs in an image to generate a determination result; selectively utilizing a specific bounding box to identify a target object to generate an identification result according to the determination result, wherein the specific bounding box represents a location of the target object in a previous image; and selectively updating information of the specific bounding box according to the identification result.

Abstract: The present invention provides a processing circuit applied to a face recognition system, which includes a characteristic value calculation module, a determination circuit and a threshold value calculation module.

Abstract: A method of handling signal transmission applicable to a display system includes a plurality of steps. The steps include transmitting a reset signal embedded in a first data signal to each of at least one source driver via a first data channel, generating a first control signal for setting the at least one source driver, and transmitting the first control signal embedded in a second data signal to each of the at least one source driver via a second data channel when the reset signal is transmitted via the first data channel.

Abstract: A method of handling signal transmission applicable to a display system includes a plurality of steps. The steps include transmitting a reset signal embedded in a first data signal to each of at least one source driver via a first data channel, generating a first control signal for setting the at least one source driver, and transmitting the first control signal embedded in a second data signal to each of the at least one source driver via a second data channel when the reset signal is transmitted via the first data channel.

Abstract: The disclosure provides a light source module including a substrate, multiple light-emitting elements, multiple reflecting elements, and an encapsulation layer. The reflecting elements and light-emitting elements are disposed in stack arrangement in the direction perpendicular to the substrate surface, respectively. The encapsulation layer disposed between the reflecting elements and light-emitting elements includes multiple first grooves and main portions. The first grooves located between the light-emitting elements are connected to each other. The main portions cover the light-emitting elements, and the reflecting elements and the light-emitting elements are disposed in the central position of the main portions having multiple first inclined ridges disposed around the central position to define the first grooves in the first direction parallel to the extending direction of the substrate surface.

Abstract: A motion image integration method includes acquiring a raw image, detecting a first motion region image and a second motion region image by using a motion detector according to the raw image, merging the first motion region image with the second motion region image for generating a motion object image according to a relative position between the first motion region image and the second motion region image, and cropping the raw image to generate a sub-image corresponding to the motion object image according to the motion object image. A range of the motion object image is greater than or equal to a total range of the first motion region image and the second motion region image. Shapes of the first motion region image, the second motion region image, and the motion object image are polygonal shapes.

Abstract: An image scanning, displaying and lighting system for eliminating color differences is revealed. The system includes an image scanner, a display screen with a second emission spectrum and a lighting device with a third emission spectrum. The image scanner consists of an optoelectronic image capturing and forming system, a plurality of first light sources disposed around the optoelectronic image capturing and forming system and a control module. The first light sources have a first emission spectrum which is a white light composed of a plurality of wavebands with different peak wavelengths. The control module controls the optoelectronic image capturing and forming system to take monochrome images in different colors in time sequence. The second emission spectrum has the same characteristics as the first emission spectrum while the third emission spectrum has the same characteristics as the second emission spectrum.

Abstract: A motion detection method includes acquiring a raw image, detecting a motion object image according to the raw image by using a motion detector, cropping the raw image to generate a sub-image according to the motion object image, and inputting the sub-image to a processor for determining if a motion object of the sub-image matches with a detection category. The processor includes a neural network. The shape of the sub-image is a polygonal shape.

Abstract: An object detection method and an associated electronic device are provided, wherein the object detection method includes: utilizing an image processing circuit to determine whether motion occurs in an image to generate a determination result; selectively utilizing a specific bounding box to identify a target object to generate an identification result according to the determination result, wherein the specific bounding box represents a location of the target object in a previous image; and selectively updating information of the specific bounding box according to the identification result.

Abstract: A light source module including a substrate and a plurality of light emitting units is provided. The light emitting units are disposed on a surface of the substrate and each light emitting unit includes a first light emitting device, a second light emitting device, a first reflective element, a second reflective element and a package structure. The first reflective element and the second reflective element are respectively overlapped with the first light emitting device and the second light emitting device along a direction being perpendicular to the surface of the substrate. The package structure is disposed between the first reflective element, the second reflective element, the first light emitting device and the second light emitting device. The package structure includes a main body portion and a first recess. The main body portion covers the first light emitting device and the second light emitting device.

Abstract: A display device and a driving method thereof are provided. The display device includes a first light-emitting diode, a first controller, a second light-emitting diode, and a second controller. The first controller has a first current source. The second controller has a second current source, wherein the first current source is coupled to a coupling point of the second light-emitting diode and the second current source. When the first light-emitting diode is normal, the first current source provides a first driving current to drive the first light-emitting diode. When the first light-emitting diode is open, the first current source stops providing the first driving current, and the second current source provides a second driving current to drive the second light-emitting diode.

Abstract: An image scanning and displaying system for eliminating color differences is revealed. The system includes an image scanner and a display screen with a second emission spectrum. The image scanner consists of an optoelectronic image capturing and forming system, a plurality of first light sources disposed around the optoelectronic image capturing and forming system and a control module. The first light sources have a first emission spectrum which is a white light composed of a plurality of wavebands with different peak wavelengths. The control module controls the optoelectronic image capturing and forming system to take monochrome images in different colors in time sequence. The second emission spectrum has the same characteristics as the first emission spectrum.

Abstract: An image scanning, displaying and lighting system for eliminating color differences is revealed. The system includes an image scanner, a display screen with a second emission spectrum and a lighting device with a third emission spectrum. The image scanner consists of an optoelectronic image capturing and forming system, a plurality of first light sources disposed around the optoelectronic image capturing and forming system and a control module. The first light sources have a first emission spectrum which is a white light composed of a plurality of wavebands with different peak wavelengths. The control module controls the optoelectronic image capturing and forming system to take monochrome images in different colors in time sequence. The second emission spectrum has the same characteristics as the first emission spectrum while the third emission spectrum has the same characteristics as the second emission spectrum.

Abstract: A method of updating background model for an image processing device is disclosed. The method includes receiving at least a background image, counting a number of occurrences of a color of each pixel of the background image according to a color information of each pixel of the at least a background image, to establish a background model including a statistical color information about the color and the number of occurrences of the color, receiving a current image, and determining whether to update the number of occurrences of the color in the background model corresponding to a color of each pixel of the current image according to a color information of each pixel of the current image and a result of comparing a random number with a threshold.

Abstract: The present disclosure provides a measurement method for a molding system comprising an upper mold and a lower mold forming a mold cavity. The method includes applying a pressure difference to a molding resin for driving the molding resin to flow into a preform in the mold cavity; detecting a flow front of the molding resin at a first position and a second position in the mold cavity; and calculating a flowing property of the molding resin based on the first position, the second position, a travelling time of the flow front from the first position to the second position, and the pressure difference.

Abstract: A motion detection method includes acquiring a raw image, detecting a motion object image according to the raw image by using a motion detector, cropping the raw image to generate a sub-image according to the motion object image, and inputting the sub-image to a processor for determining if a motion object of the sub-image matches with a detection category. The processor includes a neural network. The shape of the sub-image is a polygonal shape.