272 results about "Window detection" patented technology

A method of executing multiple applications in an apparatus including a touch screen is provided. The method includes displaying a first window in which a first application is executed on the touch screen, detecting a division screen display event of the first application and a second application, and decreasing a size of the first window on the touch screen when the division screen display event is detected and displaying, together with the first window, a second window in which the second application is executed on the touch screen.

An initial browser window establishes itself as a “master” window for an associated server. A master window “cookie” data structure is created by the master window to share state among the windows for the server. Through the initially created master window cookie, all subsequently created browser windows detect that a master window is currently active, determine the master window's window name, and then establish themselves as slave windows through the master window. Slave windows call into the master window to request server updates / events, and provide the master window with their respective window names for future reference, e.g. when the master window distributes updates / events received from the server to the slave windows. The master window uses only a single HTTP GET command to fetch and dispatch updates / events associated with itself and all slave windows for the server.

A new system for gracefully re-establishing an expired user session in which a separate session expiration time cookie is provided to communicate the session expiration time from the Web server to the browser. The Web server further provides the browser with session validation and re-establishment routines that include logic for checking whether a current user session has expired, or is near expiration. These routines are cached by the browser. When a browser user performs an action requiring server action, a determination is made as to whether the current user session has expired, or is near expiration. If either of these cases are true, the user action just invoked is stored, and a separate browser window is opened. A protected page is loaded which closes the browser window. In order to display the protected page, the user first encounters the login page and enters the proper credentials to log-in to the server. As part of displaying the protected page, the server updates the user session expiration time cookie to the new session expiration time. At this point, the original window detects the new session expiration time and at this time the prior invoked action can be re-attempted. Since the session is not expired, or at risk of immediate expiration, the action can be completed properly.

A method and apparatus for processing data in a computer system from a keyboard wedged device and a keyboard hook device. The keyboard wedge converts the data into standard keyboard keystrokes for transmission over a keyboard line. The keyboard hook provides a window through which scanned data is detected. Scanned data is distinguished from typed data using a software data processing application. The software is configured to identify scanned data based on characteristics of the scanned data. Processing functions are next performed on the detected data according to the particular application being used.

A plasma processing system and method for operating an optical system in conjunction with a plasma processing system are provided. The plasma processing system includes an optical system in communication with a plasma processing chamber of the plasma processing system. The optical system has a window and is constructed and arranged to detect a plasma process condition through the window and a transmission condition of the window. The method includes detecting an optical emission from the plasma processing region and monitoring contamination of a window provided by the optical system.

An electro-optical imaging reader includes a chassis mounted in a housing, a window spaced from a rear wall of the chassis, an imaging module for capturing return light from a target through the window over an imaging field of view, a controller for operating the reader in a standby state in which no target is read, and for processing the captured return light to read the target during a reading state, and an object sensing assembly supported by the rear chassis wall and spaced from the window. The object sensing assembly senses the presence of an object bearing the target in front of the window by detecting return sensing light from the object through the window over a sensing field of view that at least partially overlaps the imaging field of view, and triggers the controller to change from the standby state to the reading state upon such detection.

Methods for detecting a windows in a building utilizing a building scan using an electronic computing device are presented, the methods including: causing the electronic computing device to receive the building scan; processing the building scan; detecting the windows based on no return transparency of portions of the building scan; and incorporating the detected windows into a 3D model corresponding with the building scan. In some embodiments, processing the building scan generates at least the following: a colored point cloud; a 2D floor plan of the building; and a walked path. In some embodiments, detecting the windows based on transparency of a portions of the building scan further includes: decomposing the colored point cloud into walls; rotating and pixilating the walls; extracting transparent features corresponding with the windows; and classifying and smoothing the transparent features corresponding with the windows.

The invention discloses a pedestrian image detection method based on sparse coding and a neural network. The method comprises the steps: preprocessing the samples in a sample data set, and extracting the features of an aggregation channel; constructing a BP-AdaBoost strong classifier model and training; preprocessing video frames, and scaling the video frames with different scales to obtain an image pyramid; utilizing the quick image feature pyramid calculating method to integrate with a sliding window detection method to calculate the window images to obtain the features of the aggregation channel, and utilizing the trained strong classifier to perform classification; and when the detection result of the window images is a positive sample, outputting the detection window, and fusing all the detection windows to obtain an accurate positioning window. The pedestrian image detection method based on sparse coding and a neural network is high in the calculating speed and the accuracy when the training samples are large.

The invention belongs to the technical field of radar signal processing, and discloses an object plot clotting method of radar echo data. The method includes the following steps: acquiring original echo data of a plurality of scanning periods of a radar; successively conducting multi-pulse incoherent integration on the original echo data, obtaining echo data after pulse integration; conducting constant false alarm rate detection on the echo data which is subject to pulse integration, successively conducting binary quantization on the echo data which is subject to constant false alarm rate detection and conducting binary sliding window detection along the direction of a direction-fractal dimension; the echo data which is subject to binary sliding window serving as binary image data, firstly inflating the binary image data and then corroding the binary image data so as to obtain all connected domain of the binary image data; filtering a fist connected domain and a second connected domain, obtaining residual connected domain containing object plots; on the basis of the residual connected domain which contains the object plots, obtaining object information, realizing clotting of the object plots. The method can increase object parameter estimation precision and object resolution capability.

An optical reader for decoding an encoded symbol character of a symbology includes a scan data signal processor having as an input a scan data signal encoding information representative of the encoded symbol character. The scan data signal processor includes a first time delay stage adapted to provide a primary phase waveform from the scan data signal, a second time delay stage adapted to provide an early phase waveform from the scan data signal, and a third time delay stage adapted to provide a delayed phase waveform from the scan data signal. The early phase waveform has a propagation delay less than the primary phase waveform, and the delayed phase waveform has a propagation delay greater than the primary phase waveform. The scan data signal processor further includes a peak window detection stage for generating a peak window timeframe when an amplitude of the primary phase waveform is greater than, less than, or equal to both an amplitude of the early phase waveform and the delayed phase waveform. The optical reader further includes a digitizer circuit adapted to accept, within the peak window timeframe, the scan data signal processor output.

The invention discloses an inertial pedestrian positioning method based on self adaptive zero-velocity interval adjustment, and belongs to the pedestrian positioning technical field relying on an inertial navigation system. An inertial device is fixed on a foot part of a pedestrian, positioning information of the pedestrian is calculated in real time according to the measured acceleration speed and angular velocity, at the same time, a self adaptive sliding window detection method is designed by combination of an acceleration speed and angle acceleration speed amplitude detection algorithm, the zero-velocity detection window length is self-adaptively adjusted in the system calculating process, and the zero-velocity detection accuracy is improved. The zero-velocity correction algorithm is used for compensating the pedestrian posture information in a zero-velocity interval, and the compensated posture information is taken as final positioning information and is outputted. The applicability of the inertial pedestrian positioning system at arbitrary motion speed is enhanced, the problem of insufficient error compensation caused by the change of pedestrian movement speed is reduced, positioning accuracy can be improved without any external auxiliary information, the calculation quantity is small, and the method is simple and easy to operate.

An apparatus, method, and medium for detecting a face in an image using classifiers generated by a boost algorithm are provided. The apparatus may include an image dividing unit dividing a black and white image into sub-windows; a sub-window detection unit detecting a sub-window corresponding to a face image in the divided sub-windows using the front part of the cascade of the classifiers and storing the sub-window detected as the face image; and a post-processing unit verifying whether each of sub-windows included in a group among a plurality of groups into which stored sub-windows are grouped is the face image using the number of child detections in each group and the latter part of the cascade of classifiers, integrating the sub-windows in the group according to the result of the verification, and outputting the result of the integration as the face image included in the black and white image.

The invention relates to a station caption identification method based on the combination of edge and texture features. The station caption identification method comprises the steps of extracting edge information of an image to be detected; selecting a template of a station caption to be detected, and extracting edge information and texture features of the template of the station caption; carrying out template matching by using a sliding window method, calculating a candidate station caption region in an image of a video frame to be detected, and extracting texture features thereof; and calculating similarities between the template of the station caption and the candidate region image by using the extracted texture features, and sorting the similarities from large to small, and obtaining a final identification result through threshold determination. The invention verifies and confirms the candidate station caption region by using highly descriptive image features on the basis of the sliding window detection, has good robustness for TV station video in actual environments, and can achieve higher station caption identification accuracy.

The invention discloses a seat belt not-wearing detection method based on a mixed multi-scale deformable component model, which comprises a deformable component model training process and a process for seat belt detection by using the deformable component model. The process for seat belt detection by using the deformable component model comprises steps: a picture is acquired through a picture acquisition device; the deformable component model is used for vehicle window detection; human upper body detection is carried out in the detected vehicle window area; and seat belt detection is carried out on the detected human upper body area.

The invention discloses an industrial product surface defect detection method based on sample enhancement. The method comprises the following steps: 1) carrying out size standardization, normalization, cutting and classification on an industrial product surface image; 2) carrying out data enhancement of random flipping on the picture with the defect; 3) randomly splicing and enhancing the defective picture and the normal picture; 4) carrying out iterative training by using a Cascade-RCNN algorithm; 5) acquiring a Cascade-RCNN detection model; 6) carrying out sliding window detection on the industrial product surface picture to be detected and the texture template picture determining no defect through the Cascade-RCNN detection model, splicing results detected by a sliding window, and comparing the results obtained by the sliding window detection and the texture template picture to finally obtain the defect category and region annotation of the picture to be detected. According to the method, the influence of conditions such as illumination, exposure and displacement on defect detection can be effectively reduced, the detection stability is improved, the resolution capability of thetwo-stage target detector on patterns and backgrounds is improved, and the false detection rate is reduced.

Methods, systems, and devices for wireless communication are described. A user equipment (UE) may monitor a neighbor cell and report the result to a serving base station. Based on the report, the serving base station may identify an estimated discovery reference signal (DRS) transmission window of the neighbor cell. In some cases, the UE may estimate and report parameters of the neighbor DRS transmission window, and in other cases, the UE may make a measurement report and the base station may infer DRS transmission window parameters. The base station may then provide the UE with a DRS measurement timing configuration (DMTC) based on the estimated parameters of the neighbor cell so that the UE may monitor the neighbor cell and the serving cell in an efficient manner. For example, the UE mayconserve battery life by refraining from monitoring DRS during periods when a DRS transmission is not likely.

A three-dimensional space building window detection and reconstruction method based on unmanned aerial vehicle (UAV) images includes the steps of firstly, pre-processing a scene image; secondly, performing Canny edge detection on a texture image; thirdly, establishing a Markov random field and a corresponding energy function for grid distribution of the wall; and fourthly, performing three-dimensional space mapping for two-dimensional coordinates of a detected wall window region and a three-dimensional plane of the wall. Through the above steps, the detection method combines the three-dimensional space information of a building with image information, can eliminate the influence brought by the occlusion, deformation and other structural difference change of a window in the two-dimensional image, can accurately position and reconstruct the structure of the window in a three-dimensional space, and has practical application values in other image processing fields such as target tracking, three-dimensional reconstruction, scene simulation and the like.

An optical window contamination detecting device capable of detecting even microscopic contamination on an optical window with a limited number of contamination detecting sensors. The optical window contamination detecting device is used for a scanning type distance measuring apparatus that includes a casing, formed with an optical window, which accommodates a light transmitting unit, a scanning mechanism for deflection scanning measurement light output from the light transmitting unit into a measuring space through the optical window, and a light receiving unit for detecting reflected light from an object through the optical window. The optical window contamination detecting device includes a plurality of reflection photoelectric sensors arranged along the optical window on an outer side of the optical window and a retro-reflective member attached to the scanning mechanism, the retro-reflective member for reflecting detection light from the reflection photoelectric sensor having passed through the optical window towards the reflection photoelectric sensor.

A plasma processing system and method for operating an optical system in conjunction with a plasma processing system are provided. The plasma processing system includes an optical system in communication with a plasma processing chamber of the plasma processing system. The optical system has a window and is constructed and arranged to detect a plasma process condition through the window and a transmission condition of the window. The method includes detecting an optical emission from the plasma processing region and monitoring contamination of a window provided by the optical system.

The invention discloses a pavement crack segmentation and recognition method based on deep learning. The pavement crack segmentation and recognition method comprises the following steps: firstly, manually labeling an acquired color crack sample image to obtain a crack label image; performing sub-image segmentation of the same size and position on the two types of images, marking whether the sub-images contain cracks, training a U-Net neural network by using the marked sub-images, and training the decision network by using the results of the last two layers of the U-Net neural network as the input of the decision network; and finally, obtaining a trained network model, and performing non-overlapping sliding window detection and classification on the to-be-identified image so as to obtain the segmentation and identification result of the image. According to the pavement crack segmentation and recognition method, the crack image is segmented, and whether the image contains cracks can be accurately identified, so that the purposes of efficient, accurate and low-cost pavement crack segmentation and identification can be achieved.

In a phase-locked loop circuit including a lock detection function, the phase-locked loop circuit includes a lock detection circuit. The lock detection circuit includes a lock-window-entry detection circuit and a lock-detection-signal generation circuit. The lock-window-entry detection circuit detects a front edge of an up signal or a down signal generated by a phase frequency detector at a front edge of a delayed up signal or a delayed down signal to generate a lock-window-entry detection signal, wherein the delayed up signal or the delayed down signal is delayed substantially by as much as a lock window. The lock-detection-signal generation circuit counts an input signal of a phase-locked loop circuit to generate a lock detection signal when the lock-window-entry detection signal is continuously enabled for a predetermined time period. In this manner, a lock detection signal is output only when the phase locking operation has been completed.

Midamble codes, acting as channel estimation, and information data, as well as system information, will be sent to the joint cell detector. Midamble codes are sent to the estimator of adjacent cell, as well as that of its own cell. As a matter of fact, channel response is sent to channel noise-depressed modules to be depressed. Then the depressed channel is sent to channel window activation detector to receive first activation detection, to see whether the channel windows are activated. Channel response, after detected by channel window, will be sent to multi-user jointed detection unit together with information data. The soft bit information, after having been demoduled or detected, will be transmitted to the following Transport Channel Decoding (TrCH) modules and Channel Decoding (CC) modules. This invention solves the technical problems, that is, interferences received by the user equipments in inter-frequency network from its own cell and the adjacent cells, and to combat the problems of low capacity and handovers.

The invention relates to an idle frequency band detector applied to a UHF frequency band, characterized by comprising a set of broadband receiving branches and a multi-window detector. Signals received by a broadband antenna are sequentially input to a radio frequency wave filter, a low-noise amplifier and an adjustable trap wave filter, and down conversion is carried out on the signals by a frequency mixer and a voltage controlled oscillator; the down-conversion signals are converted by an A / D converter into digital signals to be stored in a register, and the digital signals are input to the multi-window detector; the digital signals are input to a multi-window spectrum estimation module after being segmented by a signal segmenting module; a multi-window spectrum estimation method is utilized to carry out power spectrum estimation on the digital signals, and then a multi-window detection algorithm is utilized to judge whether the signals comprise ATSC DTV signals or wireless microphone signals. The idle frequency band detector not only can be used for detecting the ATSC DTV signals or wireless microphone signals in an extreme low signal-to-noise environment, but also can be used for achieving a frequency spectrum perception function of a cognitive radio system.

Methods, systems, and processor-readable media for detecting the side window of a vehicle. A spatial probability map can be calculated, which includes data indicative of likely side window locations of a vehicle in an image. A side window detector can be run with respect to the image of the vehicle to determine detection scores. The detection scores can be weighted based on the spatial probability map. A detected region of interest can be extracted from the image as extracted image patch. An image classification can then be performed with respect to the extracted patch to provide a classification that indicates whether or not a passenger is in the vehicle or no-passenger is in the vehicle.

The invention discloses a SAR image CFAR adaptive rapid detection method based on multithreading and belongs to the field of ship detection systems. The method comprises steps of: setting a CFAR value by histogram statistic, acquiring a global threshold, rapidly singling out possible target points in an image, and acquiring an index matrix; performing sliding window detection based on K distribution on selected possible target points by using the index matrix, wherein the process uses multithreading to increase local detection speed; performing four connected region area statistics on target points acquired from the local detection and singling out a possible ship according to minimum ship pixel area; and deriving a conclusion that the method is more suitable for a ship detection system by analyzing a detection result of the method to a SAR image. Compared with a Salazar algorithm, the rapid detection method is greatly increased in detection speed while not decreased in detection accuracy and is more suitable for the ship detection system.

A method of path detection in a multi-path communications system that includes selecting an object for configuring a search window, setting at least one sub-window, wherein the sub-window is smaller in size than the search window, providing a first counter for the object, setting a threshold, selecting a decision period for a duration of the object, and detecting a path in a selected region with the at least one sub-window in a plurality of modes corresponding to the threshold.

The invention discloses a 2D laser scanning based rapid detection method for a heading window of a heading machine. The detection method comprises that horizontal and vertical 2D scanning is carried out on a heading working face, outliers are removed from collected original point cloud data; linear fitting, central line solving and base point determining are carried out on outlier removed horizontal and vertical 2D scanning point cloud data, and preparation for window detection is completed; and a target distance is input, a vertical line is drawn at the position in the target distance from the base point, serving as the origin point, in the horizontal central line, another vertical line is drawn at the position in the target distance from the base point, serving as the origin point, in the vertical central line, the vertical lines intersects with two lines obtained by fitting respectively, point pairs are obtained, the spatial distance of the horizontal point pair equals the width of the heading window in the target distance, and the spatial distance of the vertical point pair equals the height of the heading window in the target distance. According to the technical scheme of the invention, the sizes of heading windows in multiple target distances can be rapidly detected, timely effective reference and correction are provided for workers, and the reasonableness of the practical heading process is ensured.