A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization method may be used to provide input to an HILN (H, I, and/or L, or N) detection method. The characterization method includes capturing one or more images of a labeled specimen container including a serum or plasma portion from multiple viewpoints, processing the one or more images to provide segmentation data including identification of a label-containing region, determining a closest label match of the label-containing region to a reference label configuration selected from a reference label configuration database, and generating a combined representation based on the segmentation information and the closest label match. Using the combined representation allows for compensation of the light blocking effects of the label-containing region. Quality check modules and testing apparatus and adapted to carry out the method are described, as are other aspects.

A high-dynamic-range (HDR) detecting system includes a camera module comprising an image sensor; and a vision module that receives data generated by the camera module and accordingly transmits feedback to the camera module. The camera module comprises a multiple-exposure unit that provides different exposure settings, according to which a plurality of images are captured by the image sensor. The vision module comprises an object detection device that detects objects in the plurality of images, thereby resulting in object detection results as metadata.

The disclosure directed to methods for measuring an analyte alone or in combination with total protein in biological samples. More particularly, the disclosure relates to methods for measuring an analyte and/or total protein using one or more colorimetric reagents alone or in combination with protein precipitation reagents.

An apparatus includes at least one memory configured to store instructions, and at least one processor in communication with the at least one memory and configured to execute the instructions to perform same area dividing on each of a plurality of images, and create a composite image from the plurality of images. A first area of the composite image is composited from corresponding areas in a first number of image among the plurality of images. A second area of the composite image is composited from corresponding areas in a second number of image among the plurality of images.

An image processing device includes a setting unit configured to estimate a disparity between a first image and a second image based on a method different from stereo matching and set, based on the disparity thus estimated, a search range for a corresponding point for the stereo matching, a disparity map generating unit configured to search only the search range thus set for a corresponding point of each pixel between the first image and the second image and generate a disparity map, and a disparity map compositing unit configured to composite a plurality of the disparity maps each generated from a corresponding one of a plurality of image pairs.

An image pickup apparatus includes a lens, an image pickup device, and a processor. The processor acquires a plurality of pieces of first image data and second image data with an exposure time period longer than an exposure time period of the first image data from the image pickup device, detects a motion region by using the first image data and the second image data, and acquires motion detection information by using the plurality of pieces of first image data. The processor changes a synthesis method in accordance with whether the motion region is detected and generates one piece of synthesized image data.

This application provides an image obtaining method and apparatus. The image obtaining method according to this application includes: obtaining first original image data, where the first original image data is captured by an image sensor based on an initial visible light exposure parameter and luminous intensity of an infrared illuminator; obtaining a luminance of a visible light image based on the first original image data; adjusting the visible light exposure parameter based on a first difference, where the first difference is a difference between the luminance of the visible light image and preset target luminance of the visible light image; obtaining a luminance of an infrared image based on the first original image data; adjusting the luminous intensity of the infrared illuminator based on a second difference, where the second difference is a difference between the luminance of the infrared image and preset target luminance of the infrared image.

An optical tracking device is used to track a target object. An outer surface of the target object is divided into a first region and a second region adjacent to each other, and a marker is disposed on the first region. The optical tracking device includes an optical sensor and an operation processor. The optical sensor has auto exposure function and is adapted to acquire a detection image containing at least one of the first region and the second region. The operation processor is electrically connected to the optical sensor and adapted to analyze variation of an exposure parameter of the auto exposure function for determining whether the first region is appeared in the detection image, so as to acquire an operation datum of the target object.

Methods for improving and modifying a High Dynamic Range (HDR) scene, captured as a series of images of the scene with different exposure levels and the scene through classification-based image merging, tuning, correction, and replacement. The approach employs mixing images to improve the selection and display of both shadowed and highlighted details. The increased efficiency resulting from improvements in computational resource utilization of image processing hardware can, from the implementation of the improved computational methods herein, significantly reduce the time required to generate and display a tone-mapped HDR image, a gamma-corrected HDR image, and/or a segmented and replaced HDR image.

The present application relates to an image-fusion method and apparatus, a computing and processing device and a storage medium. The method includes: based on a same one target scene, acquiring a plurality of exposed images of different exposure degrees; acquiring a first exposed-image fusion-weight diagram corresponding to each of the exposed images, wherein the first exposed-image fusion-weight diagram contains fusion weights corresponding to pixel points of the exposed image; acquiring a region area of each of overexposed regions in each of the exposed images; for each of the exposed images, by using the region area of each of the overexposed regions in the exposed image, performing smoothing filtering to the first exposed-image fusion-weight diagram corresponding to the exposed image, to obtain a second exposed-image fusion-weight diagram corresponding to the exposed image; and according to each of the second exposed-image fusion-weight diagrams, performing image-fusion processing to the plurality of exposed images, to obtain a fused image. Accordingly, the present application can balance the characteristics of the different overexposed regions, and prevent the losing of the details of the small overexposed regions, to enable the obtained fused image to be more realistic.