A computer-implemented method for focal length validation may include receiving, by a computing system, initial image data for an optical target from a camera. The method may also include determining a distortion parameter associated with the camera, based on the initial image data. The method may also include receiving, by the computing system, a first image of the optical target, wherein the first image is associated with a first position of the camera. The method may also include receiving, by the computing system, a second image of the optical target, wherein the second image is associated with a second position of the camera. The method may also include determining an estimated displacement between the first position of the camera and the second position of the camera based on the first image and the second image. The method may further include determining a focal length based on the estimated displacement and a measured displacement of the camera between the first position and the second position.

A ground line monitoring system includes a camera mounted in a first automobile vehicle. A waveguide directs a light into the camera having a first in-coupling grating receiving a first light imaging data and passing the first light imaging data as a first frequency of the light and a second in-coupling grating receiving a second light imaging data and passing the second light imaging data as a second frequency of the light. A color filter wheel receives the first frequency of the light and the second frequency of the light. An image sensor of the camera receives the first frequency of the light and the second frequency of the light at different times due to rotation of the color filter wheel. A controller performs a calculation using directions and angles of the first frequency of the light and the second frequency of the light to correct a camera image.

Embodiments relate to correcting pixels of images captured using a quadra image sensor. A defect detection circuit analyzes the pixels in the captured image and determines whether a pixel is defective. The defect detection circuit generates a first defect indication by determining whether pixel data of a pixel under test is brighter or darker by a first threshold value than pixel data of pixels in pixel tiles surrounding the pixel tile corresponding to the pixel under test. Moreover, the defect detection circuit generates a second defect indication by determining whether pixel data of the pixel under test is brighter or darker by a second threshold value than pixel data of other pixels in the pixel tile corresponding to the pixel under test. Using the first and second defect indications, the defect detection circuit identifies whether the pixel data of the pixel under test is defective.

An imaging apparatus comprises a camera and a controller. The camera generates a captured image. The controller superimposes a calibration object movable by translation or rotation in the captured image. In the case where a plurality of indexes I located at positions determined with respect to a moveable body having the camera mounted therein are subjected to imaging, the controller moves the calibration object so that a first corresponding portion coincides with an image of a first index of the plurality of indexes, and performs distortion correction on an area in the captured image determined based on a position of the image of the first index and a position of an image of a second index in the captured image and a position at which the calibration object is superimposed so that the image of the second index coincides with a second corresponding portion.

Provided herein may be an image sensing device and a method of operating the same. The image sensing device may include an image sensor configured to acquire an image including a plurality of pixel values, a memory configured to store reference gain values of each of a plurality of block areas included in the image, and an image processor configured to calculate gain values included in each of the plurality of block areas using the reference gain values and to output a correction image in which the reference gain values and the gain values are applied to the plurality of pixel values, wherein the block areas include a first block area and a second block area having a shorter distance from a center of the image than the first block area and having a size greater than that of the first block area.

The invention is a system for color analysis, which comprises a hand-held device and a working platform. The hand-held device is provided with a camera and installed with analysis software. The work platform is placed with an object to be tested, a standard color carrier is installed at both front and rear sides or at both left and right sides of the object to be tested, a positioning frame extends upward around the working platform, the positioning frame and the working platform are mutually formed an inclination angle, and the positioning frame is used to fix the hand-held device. In this way, the camera can shoot the working platform in an inclined direction, and then the analysis software is used to compare a color difference between the object to be tested and the standard color carrier to obtain analysis result of the object to be tested.

A 3D test chart, an adjusting arrangement, a forming method, and an adjusting method thereof are disclosed. The 3D test chart provides a plurality of test patterns arranged at different depths. When testing a photographic arrangement, the photographic arrangement is only required to move for one time or even does not need to be moved, so as to obtain an image containing information of different depths, so that the testing and adjusting process of the photographic arrangement can be easily achieved.

In one aspect the invention provides a method of operating a time of flight camera which includes the steps of capturing a sequence of time of flight camera data frames using a set of step frequency modulation signals to provide a time of flight camera data set, then completing a spectral analysis of the dataset which identifies frequency and phase value pairs indicative of the range of the camera to an object represented in the data frames. Next an estimated camera range value to an object represented in the data frames is determined using the frequency value, then a corrected camera range value is determined using the estimated camera range value and the phase value. A camera output is then provided which identifies the corrected range values of at least one object represented in the data frames of the dataset.

A network management system manages the operation of a home security system in a communication network, such as a mesh network. The home security system can include multiple components such as a camera, a lighting device, a security alarm, a doorbell switch and doorbell chime, and a fingerprint sensor, which connect with the communication network to perform various operations. The network management system monitors environmental parameters of the communication network, such as parameters associated with the access points and components of the home security system, determines an access point to which a component of the home security system is to be connected for efficient operation of the home security system, and connects the component to the communication network via the determined access point.

Use of multiple sensors to determine whether motion of an object is occurring in an area is described. In one aspect, an infrared (IR) sensor can be supplemented with a radar sensor to determine whether the determined motion of an object is not a false positive.