A circuit device 100 includes an error detection circuit 110 and a processing circuit 120. The error detection circuit 110 obtains a glare index value, which is an index value indicating glare of a head-up display, based on image data IMD for head-up display. The error detection circuit 110 determines whether or not a glare index value has exceeded a first threshold value, and when the glare index value exceeds the first threshold value, detects occurrence of a first glare error. When occurrence of a first glare error is detected, the processing circuit 120 performs processing corresponding to the first glare error.

A system, a method and a non-transitory computer readable storage medium for base calling are described. The base calling method includes processing through a neural network first image data comprising images of clusters and their surrounding background captured by a sequencing system for one or more sequencing cycles of a sequencing run. The base calling method further includes producing a base call for one or more of the clusters of the one or more sequencing cycles of the sequencing run.

The invention relates to a method in the preparation of samples for microscopic examination onto which a coverslip is applied. The method is notable for the fact that the coverslipping quality is checked automatically and at least partly optically. The invention further relates to an apparatus for carrying out the method, and to an apparatus for checking the coverslipping quality of samples onto which a coverslip is applied.

The technology disclosed relates to classification of process cycle images to predict success or failure of process cycles. The technology disclosed includes capturing and processing images of sections arranged on an image generating chip in genotyping process. Image description features of production cycle images are created and given as input to classifiers. A trained classifier separates successful production images from unsuccessful or failed production images. The failed production images are further classified by a trained root cause classifier into various categories of failure.

Disclosed are a face image and iris image acquisition method and device, a computer-readable readable storage medium and an apparatus. The method includes rotating the first tripod head to force the face lens and the iris lens to be in acquisition positions; capturing a first face image and a first iris image simultaneously by the face lens and the iris lens; and locating the iris in the first iris image, and if no iris is located, determining whether a condition of light-avoiding rotation is satisfied, and if the condition is satisfied, rotating the second tripod head to adjust an angle or a position of the supplementary light source to enable a light spot region to avoid an iris region.

The image processing unit selects multiple subject areas from strobe-ON image data to be corrected, and, from the selected multiple subject areas, the image processing unit acquires a feature amount such as gloss information corresponding to each subject. Subsequently, from each subject area, the image processing unit selects a part of the subject area, based on the acquired feature amount. Then, regarding the partial area of each subject area, which is selected based on the feature amount, the image processing unit estimates the auxiliary light arrival rate corresponding to each subject, based on a pixel value of the strobe-ON image data and a pixel value of strobe-OFF image data. Thereafter, based on the estimated auxiliary light arrival rate, the image processing unit corrects the brightness of each subject area of the strobe-ON image data, in order to generate corrected image data.

An example electronic system is described in which an imaging device includes a lens and an image sensor. The imaging device is aligned with an optical target. The optical target includes a text character of a defined text size. An image capturer activates the imaging device to capture an electronic image of the optical target. The electronic image includes the text character of the optical target. An optical recognizer generates an optical recognition result for the character based on the captured electronic image. A sharpness detector compares the optical recognition result with a true value of the text character included in the optical target. Based on the comparison, a designated or defined text size is selected as a designated resolution. The designated resolution is then associable with the imaging device, the optical target, the electronic image, or a component thereof.

Arrangement for acquiring images for producing a head related transfer function filter is disclosed. In the arrangement the camera of a mobile phone or similar portable device is adjusted for the imaging. All acquired images are analyzed and only suitable images are sent further for producing the head related transfer filter. The arrangement is further configured to provide instructions to the user so that the whole head and other relevant body parts are sufficiently covered.

An object recognition device is configured to perform object recognition based on information from a unit configured to detect an object image in each frame based on a reflected signal of a transmission signal and configured to calculate one or more patterns of a confidence degree regarding the object image detected according to one or more preset calculation methods. The object recognition device includes: a first evaluation value calculator configured to increase a count of a first evaluation value indicating a probability that the object image is a real image based on the one or more patterns of the confidence degree; and a real image determiner configured to determine that the object image is a real image when a cumulative count of the first evaluation value exceeds a comparative value.

Methods, systems, and apparatus for efficient image analysis. In some aspects, a system includes a camera configured to capture images, one or more environment sensors configured to detect movement of the camera, a data processing apparatus, and a memory storage apparatus in data communication with the data processing apparatus. The data processing apparatus can access, for each of a multitude of images captured by a mobile device camera, data indicative of movement of the camera at a time at which the camera captured the image. The data processing apparatus can also select, from the images, a particular image for analysis based on the data indicative of the movement of the camera for each image, analyze the particular image to recognize one or more objects depicted in the particular image, and present content related to the one or more recognized objects.