A method for audio and video synchronization, includes: receiving audio data sent by the video player, wherein the audio data includes more than one audio sampling points; obtaining a network delay change between the audio player and the video player, wherein the network delay change refers to a time difference between the network delay monitored for the first time and the network delay monitored for the last time; determining a total amount of audio data to be adjusted according to the network delay change; and adding audio sampling points to the received audio data or deleting audio sampling points from the received audio data according to the total amount of audio data to be adjusted and a preset adjustment strategy, so that the audio player is synchronized with the video player, and playing the added or deleted audio data.

Disclosed herein are a machine architecture implementing a staging automation process, including features such as multiple IR transmitters and composite video inputs for automated high volume quality testing. Diagnostic display outputs from a unit under test are input to OCR and video quality algorithms to validate that the units under test are ready for a functional test process at the next stage.

A video quality estimation apparatus used for an encoded video, to estimate a video quality value being a value quantifying a video quality being quality of the video felt by a user when viewing and listening to the video. The apparatus includes a maximum value calculator to calculate a maximum value of the video quality value from a resolution of the video and a frame rate of the video, and a video quality calculator to calculate an estimated video quality value corresponding to an encoding bit rate having been input, based on a predetermined relationship between the encoding bit rate of the video and the video quality value. The predetermined relationship is a relationship in which the video quality value increases while the encoding bit rate increases, and the video quality value converges on the maximum value calculated by the maximum value calculator.

Various techniques include detecting noise in a network, identifying the type of noise in the network, localizing noise in the network, determining noise scores for network devices, and/or determining likelihoods that particular devices are causing noise and/or are in proximity of a point of entry of noise into the network.

An electronic component mounting apparatus includes: a transfer unit picking up an upper surface of a light emitting device package having a front surface on which a light emitting diode chip is disposed, and transferring the light emitting device package to a printed circuit board, a light source unit disposed on a transfer path of the light emitting device package, and irradiating measurement light onto the front surface of the light emitting device package, a camera capturing an image of the light emitting device package to which the measurement light is irradiated, and a control unit image-processing the image to identify excitation light, emitted when the measurement light is excited from the light emitting diode chip, in the image, and controlling the transfer unit to mount the light emitting device package on the printed circuit board when identifying the excitation light.

An imaging system may include an array of image pixels and column readout circuits coupled to each column. The column readout circuits may include test data injection circuitry and converter circuitry coupled to column memory via switching circuits. The injection circuitry may enable the switching circuits so that pixel data is stored on the column memory as rows of an image frame. The injection circuitry may disable the switching circuits and may inject test bits onto the column memory while the switching circuits are disabled. The column memory may store the test bits as one or more rows of the image frame interspersed among rows of the pixel data. Verification circuitry coupled to the column readout circuits may process the test data bits in the image frame to verify proper functionality of some or all of the imaging system without disrupting normal imaging operations by the imaging system.

A method of power signal detection of set top boxes under test is disclosed. According to certain embodiments, detection of a failure mode of a set top box (STB) under test is based on video signal detection where the video signal is associated with multiple video output types and AC power outlet signal detection.

The method includes: processing a PSNR of each segment of each sample video, determining an ePSNR predictive model according to preset parameters obtained after processing and mean opinion scores of all sample videos, and determining an enhanced mean opinion score eMOS predictive model according to the predictive model. Then, for any video that needs to be evaluated, QoE of the video that needs to be evaluated may be determined according to only the enhanced MOS predictive model and an ePSNR determined according to the ePSNR predictive model. In comparison with a prior-art method for determining QoE in which only a mean value of PERNs of all frames is considered, in this process of measuring quality of experience of a mobile video service, as many as factors that affect a PSNR of a video are considered. Therefore, accurate measurement of quality of experience of an HAS video service can be implemented.

A source device that provides contents to a sink device and a communication method thereof are provided. The communication method of the source device includes: transmitting a communication signal including a High-bandwidth Digital Content Protection (HDCP) signal to the sink device; determining a communication status with the sink device using an HDCP communication result received from the sink device; and adjusting the communication signal according to the determined communication status. Therefore, the communication method can provide a user with optimized contents.

The invention concerns a test stream generator for generating a compressed video stream for testing a video decoder, the generator including: a context-aware pseudo-random generator (202) adapted to generate pseudo-random values of syntax elements based on decoding context data; a decoding process module (206, 206′) adapted to process the syntax element values and to generate the decoding context data and binarization context data; and a binarizer module (204) adapted to encode the syntax element values based on the binarization context data in order to generate the compressed video stream.