A method for analyzing a biochip image is provided, including: (S1) acquiring and preprocessing the biochip image to obtain a preprocessed image; (S2) performing a correction for angle deflection on the preprocessed image to obtain a deflection-corrected image; and (S3) performing an enhancement processing on the deflection-corrected image, and identifying a positive or negative of an area of interest in the preprocessed image according to an image on which the enhancement processing has been performed. An apparatus (100) for analyzing a biochip image, a method for analyzing an image, a computer device (200) and a storage medium are disclosed.

An information processing apparatus comprises a first acquisition unit that acquires a captured image obtained by capturing an image of a chart for calibration, a second acquisition unit that acquires a reference image which is an image of the chart that serves as a reference, a third acquisition unit that acquires information on distortion aberration of a lens used to capture the captured image, a first generation unit that generates a pseudo image which is an image obtained by reflecting the distortion aberration in the reference image, based on the reference image and the information on distortion aberration, and a second generation unit that generates a composite image obtained by compositing the captured image and the pseudo image.

An image capture apparatus that captures an image of a chart for correcting distortion of a lens, obtains a deviation angle indicating an angle of deviation of the image capture apparatus from a directly facing positional relationship relative to the chart, obtains a deviation distance indicating a distance of deviation from the directly facing positional relationship, obtains an appropriate distance between the chart and the image capture apparatus in the directly facing positional relationship, and presents information based on the deviation angle and the deviation distance so that the directly facing positional relationship is established, and present information regarding the appropriate distance in a case in which the deviation distance and the deviation angle have each fallen below a predetermined determination threshold.

A motion detecting section detects a change in relative position relation between a subject and an image capturing section performing a rolling shutter operation. A thinning-out setting section sets a thinning-out amount of a line thinning-out operation of the image capturing section according to the detection result obtained by the motion detecting section. A recognition processing section performs subject recognition in an image obtained by the image capturing section, by using a recognizer corresponding to the thinning-out amount set by the thinning-out setting section. The change in relative position relation is detected based on motion of a moving body on which the image capturing section is mounted, an image capturing scene, an image obtained by the image capturing section, and the like. Line thinning-out is performed during the rolling shutter operation, and the thinning-out amount is set according to the detection result obtained by the motion detecting section.

A stereo camera apparatus includes a first imaging unit including a first imaging optical system provided with a plurality of lens groups, and a first actuator configured to change a focal length by driving at least one of the plurality of lens groups of the first imaging optical system; a second imaging unit including a second imaging optical system provided with a plurality of lens groups, and a second actuator configured to change a focal length by driving at least one of the plurality of lens groups of the second imaging optical system; a focal length controller configured to output synchronized driving signals to the first and second actuators; and an image processing unit configured to calculate a distance to a subject by using images captured by the first imaging unit and the second imaging unit.

A mapping system receives sensor data from an unmanned aerial vehicle. The mapping system further receives images from a camera of the unmanned aerial vehicle. The mapping system determines an altitude of the camera based on the sensor data. The mapping system calculates a footprint of the camera based on the altitude of the camera and a field of view of the camera. The mapping system constructs a localized map based on the images and the footprint of the camera.

A system, apparatus, and method for predicting a camera lens attribute using a neural network are presented. The predicted camera lens parameter may be used to produce a 3D model of an object from one or more 2D images of the object.

The invention provides an integrated digital microscope system comprising a camera, a lens and a screen to view an object characterised in that an integrated circuit comprises a video buffer write block, a grid generator block, and a video buffer read block configured to correct lens distortion errors in an image appearing on said screen. The invention also provides an integrated digital microscope system configured to remove chromatic distortion errors.

A head-up display device includes: a display unit that produces a display light for the left eye by modulating a first illumination light derived from superimposing first illumination light beams output from a first region of a fly eye lens and produces a display light for the right eye by modulating a second illumination light derived from superimposing second illumination light beams output a second region of the fly eye lens; and an image processing unit that produces an image for the left eye and produces an image for the right eye; and a display control unit that causes a display unit to display the image for the left eye when the first illumination light is produced and causes the display unit to display the image for the right eye when the second illumination light is produced.

Texture extraction is disclosed.