Embodiments described herein involve determining an area of interest on a growth media. An overall brightness control value for a plurality of illumination sources configured to illuminate the growth media is calculated. The overall brightness control value generating at least one image that substantially matches a target intensity at the area of interest. An individual brightness value for each illumination source of the plurality of illumination sources is calculated by individually adjusting a brightness of each illumination source to generate at least one image that substantially matches the target intensity in each respective illumination source's area of influence. A calibrated brightness value for each illumination source is determined based on an image intensity with each illumination source turned on at the respective individual brightness value and an intensity that each illumination source generates within each respective area of influence when turned on alone.

Implementing fingerprint authentication during a swipe motion on a display.

Electronic equipment includes a display and an optical fingerprint sensor. The display includes a display surface including light-emitting pixels in an array in a first direction and a direction intersecting the first direction. The optical fingerprint sensor includes as imaging element including light-receiving elements in an array in the first direction and the second direction on a side opposite to the display surface of the display in a third direction intersecting the first direction and the second direction, and each of the light-receiving elements transfers a photoelectrically converted charge at the same timing.

Implementing fingerprint authentication during a swipe motion on a display.

Electronic equipment includes a display and an optical fingerprint sensor. The display includes a display surface including light-emitting pixels in an array in a first direction and a direction intersecting the first direction. The optical fingerprint sensor includes as imaging element including light-receiving elements in an array in the first direction and the second direction on a side opposite to the display surface of the display in a third direction intersecting the first direction and the second direction, and each of the light-receiving elements transfers a photoelectrically converted charge at the same timing.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine a first measure of pixel values in the first image, acquire a second image, estimate ambient light illuminating the first object based on the second image and modify the first measure of pixel values based on a second measure of pixel values corresponding to estimated ambient light based on the second image. The instructions include further instructions to perform a comparison of the modified first measure of pixel values to a third measure of pixel values determined from a third image of a second object, wherein the third image is previously acquired by illuminating the second object with a second light beam and, when the comparison determines that the first measure is equal to the third measure of pixel values within a tolerance, determine whether the first object and the second object are a same object.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine a first measure of pixel values in the first image, acquire a second image, estimate ambient light illuminating the first object based on the second image and modify the first measure of pixel values based on a second measure of pixel values corresponding to estimated ambient light based on the second image. The instructions include further instructions to perform a comparison of the modified first measure of pixel values to a third measure of pixel values determined from a third image of a second object, wherein the third image is previously acquired by illuminating the second object with a second light beam and, when the comparison determines that the first measure is equal to the third measure of pixel values within a tolerance, determine whether the first object and the second object are a same object.

Methods and apparatus for applying data analytics such as deep learning algorithms to sensor data. In one embodiment, an electronic device such as a camera apparatus including a deep learning accelerator (DLA) communicative with an image sensor is disclosed, the camera apparatus configured to evaluate unprocessed sensor data from the image sensor using the DLA. In one variant, the camera apparatus provides sensor data directly to the DLA, bypassing image signal processing in order to improve the effectiveness the DLA, obtain DLA results more quickly than using conventional methods, and further allow the camera apparatus to conserve power.

Methods and apparatus for applying data analytics such as deep learning algorithms to sensor data. In one embodiment, an electronic device such as a camera apparatus including a deep learning accelerator (DLA) communicative with an image sensor is disclosed, the camera apparatus configured to evaluate unprocessed sensor data from the image sensor using the DLA. In one variant, the camera apparatus provides sensor data directly to the DLA, bypassing image signal processing in order to improve the effectiveness the DLA, obtain DLA results more quickly than using conventional methods, and further allow the camera apparatus to conserve power.

A method for monitoring cleaning of a medical room includes: receiving imaging of the medical room, the imaging capturing signatures of cleaning deposits on one or more surfaces of the medical room deposited via a cleaning process; analyzing the imaging to: identify one or more surfaces in the medical room that should be cleaned, and determine which of the one or more surfaces have been cleaned by identifying the signatures of the cleaning deposits; and displaying an indication of at least one of: (1) the surfaces that have been cleaned, and (2) one or more surfaces that have not been cleaned.

Techniques for detecting anomalies in multispectral image data, and more specifically for detecting presentation attacks by using multispectral image data in biometric security applications, are provided. In some embodiments, a system may receive multispectral image data and generate an estimation of a first image of a plurality of images of the multispectral image data, wherein the estimation is based on other images of the multispectral image data, but not the first image itself. The estimation may then be compared to the first image to generate an indication as to whether the multispectral image data represents a presentation attack. In some embodiments, a system may receive multispectral training image data and may extract features from the data to generate and store a network architecture for predicting relationships of multispectral images of subjects.

Techniques for detecting anomalies in multispectral image data, and more specifically for detecting presentation attacks by using multispectral image data in biometric security applications, are provided. In some embodiments, a system may receive multispectral image data and generate an estimation of a first image of a plurality of images of the multispectral image data, wherein the estimation is based on other images of the multispectral image data, but not the first image itself. The estimation may then be compared to the first image to generate an indication as to whether the multispectral image data represents a presentation attack. In some embodiments, a system may receive multispectral training image data and may extract features from the data to generate and store a network architecture for predicting relationships of multispectral images of subjects.