14 results about "Image converter" patented technology

A machine learning method according to this embodiment trains a recognizer using a composite image, acquires a labeled real image based on an image captured by a sensor, stores, when at least one of the results of the recognition when the labeled real image is input to the recognizer match the label, results of the recognition performed by the recognizer, performs machine learning using a data set group including a plurality of the data sets, a real image and a composite image forming a pair in each of the data sets, thereby generating an image transformer, generating a labeled real image as a result of the image transformer transforming the composite image into the real image, and trains the recognizer based on the labeled real image.

An image processing apparatus comprises a receiver (401) receiving an image comprising first pixel brightnesses encoded in accordance with a perceptually uniform Electrical to Optical Transfer Function, EOTF. A converter converts this to second pixel brightnesses encoded in accordance with an EOTF representing a logarithmic mapping from optical light values to the second pixel brightnesses and an image processor circuit (411) applies a brightness adjustment processing to the second pixel brightnesses. The converter (410) comprises a first converter (601, 605) generating intermediate pixel brightnesses applying a logarithm function to the first pixel brightnesses A second converter (603) generates intermediate pixel brightnesses by applying a second logarithm function to an output value of the perceptually uniform EOTF for the first pixel brightness divided by a divisor equal to the first pixel brightnesses raised to a power of an exponent having a value exceeding 1. A combiner generates the second pixel brightnesses by combining the intermediate pixel brightnesses.

1. The name of the design product: image instrument. 2. The use of the design product: the design product is used for image measuring instrument, mainly for measuring parts. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: perspective view 1.

Complementary metal-oxide-semiconductor (CMOS) image sensor, comprising: i) a bias junction consisting of a first semiconductor material type and electrically coupled to a voltage source to apply a reverse bias of opposite polarity to a polarity of the first semiconductor material type to the bias junction; ii) a pixel in a pixel array, comprising: a photosensitive element, a first well consisting of a second semiconductor material type, and a second well consisting of the first semiconductor material type, and active CMOS elements used for at least one of 1) reading and 2) resetting the image data acquired by the photosensitive element; and iii) an implanted, buried layer consisting of the second semiconductor material type, extending over a region representing the pixel array below the second well consisting of the first semiconductor material type;wherein the implanted, buried layer, which consists of the second semiconductor material type, is arranged to interact with the blocking bias applied by the voltage source to the bias junction to reduce a parasitic current path between the second well, which consists of the first semiconductor material type and is used by the active CMOS elements, and a substrate, resulting in more uniform pixel-to-pixel performance in an image sensor with two or more pixels.

The present invention relates to a display apparatus and a method of driving the same. The display apparatus includes a pixel, an image converter that generates a second image by correcting a gray scale of a first logo in a first image of the pixel, and a data driver that provides a data signal corresponding to the second image to the pixel. The image converter detects the first logo based on a value and a saturation of the first image, generates first map data corresponding to the first logo, and specifies the pixel corresponding to the first logo based on the first map data.

An image analysis device includes: an image converter configured to generate target image frames based on video image frames captured by a terminal device; a plurality of image analyzers respectively comprising a plurality of image analysis models, the plurality of image analyzers being configured to: generate a plurality of analysis results by analyzing the target image frames respectively using the plurality of image analysis models different from each other, and perform a respective independent analysis scheduling regardless of analysis execution states of other image analyzers; and a security state determiner configured to determine a security mode of the terminal device based on the plurality of analysis results.

Text-to-image transformers configured in one aspect to associate an input text token with the specific object, apply latent blending with attention to a combination of keys and values for the input text token and a background image upon which to add the object; and which in another aspect perform latent blending with attention to keys and values for the object to add, keys and values for the background, and keys and values for a text prompt.

Described herein is a skin detection and prevention system comprising an image converter module for receiving a first photograph and converting the first photograph to one or more new photographs, an image analyzer module for analyzing the one or more new photographs to identify one or more damaged skin areas of the new photographs, and a scoring module for receiving the analyzed second photograph and generating a skin score based on the one or more types of skin damage and the severity present in the one or more new photographs.

The present disclosure relates to a machine learning method, a machine learning system, and a computer-readable medium. The machine learning method according to the present embodiment includes training an identifier using a synthetic image, obtaining a labeled actual image based on a captured image captured by a sensor, saving an identification result of the identifier in a case where at least a part of the identification result in a case where the labeled actual image is input to the identifier coincides with a label, generating an image converter by performing machine learning using a dataset group including a plurality of datasets in which an actual image and a synthetic image are paired, converting the synthetic image into the actual image by the image converter, generating a labeled actual image, and training the identifier based on the labeled actual image.

The utility model discloses a guitar capable of assisting in indicating press positions, which comprises a guitar structure, an indicating structure is fixedly mounted above the guitar structure, the guitar structure comprises a guitar body serving as a body, a placement groove is formed in the surface of the guitar body, a through hole communicated with the placement groove is formed in the lower part of the guitar body, and the through hole is communicated with the placement groove. The indicating structure comprises a single-chip microcomputer, an image converter, an image capturer, a wireless module and a lamp holder module are electrically embedded and installed on the surface of the single-chip microcomputer, the single-chip microcomputer is fixedly installed in a connecting frame, an electronic base is fixedly installed on one side in the connecting frame, and meanwhile the electronic base is electrically connected with the single-chip microcomputer. A button electron for providing a power source is installed in the electronic base in a clamped mode, a frame cover plate is rotatably installed on the upper portion of the surface of the connecting frame, and the guitar capable of assisting in indicating pressing positions can provide a working power source through the arranged button electron.

Augmented reality applications require precise camera calibration to reduce the overall target registration errors. The camera calibration determines the mathematical model of the camera in order to determine how the physical world space is mapped to the camera image space and thus is highly dependent on the optics of the camera. The camera calibration algorithm normally assumes that the optics of the camera is rigidly fixed, which in fact is not at least for tilted laparoscopic cameras as illustrated in FIGS. 6 to 8. Furthermore, any mechanical play between elements of the objective and the image converter will render the optics variable. According to the invention markers to will be placed within the field of view of the laparoscopic camera, which allows for determination of rotation of the optical part and mechanical misalignment without the necessity or providing any additional sensor.

Display driving apparatus and driving method. A display driving apparatus for improving sharpness of an image according to an aspect of the present invention includes a luminance calculator for calculating first luminance data corresponding to a first resolution and second luminance data corresponding to a second resolution smaller than the first resolution using input image data, an offset calculator for calculating an offset based on the first luminance data and the second luminance data, an input image converter for converting the input image data into input image data to which the calculated offset has been applied, a first data output unit for generating output image data for a first panel using the converted input image data and outputting the generated output image data, and a second data output unit for generating output luminance data for a second panel using the second luminance data and outputting the generated output luminance data.

The inventive method involves receiving as input a representation of an ordered set of two-dimensional images. The ordered set of two-dimensional images is analyzed to determine at least one first view of an object in at least two dimensions and at least one motion vector. The next step is analyzing the combination of the first view of the object in at least two dimensions, the motion vector, and the ordered set of two-dimensional images to determine at least a second view of the object; generating a three-dimensional representation of the ordered set of two-dimensional images on the basis of at least the first view of the object and the second view of the object. Finally, the method involves providing indicia of the three-dimensional representation as an output.

An image masking system (100) is disclosed. The system (100) includes a segmentation module (130) configured to extract one or more regions of interest by processing an input query image using a segmentation network. The segmentation module (130) is further configured to select one or more segments from the one or more extracted regions of interest based on a user indicator. The system (100) includes a mask generation module (140) configured to generate a binary mask for the selected segments on the input query image. The system (100) further includes an image transformer module (150) configured to generate a masked image by performing an arithmetic operation on the binary mask and the input query image. The image transformer module (150) is further configured to extract an embedding of the masked image using one of a convolutional neural network architecture or a Transformer architecture.