3229 results about "False detection" patented technology

An apparatus for detecting chemical substances which is high in sensitivity and selectivity is provided.

An organic acid or an organic acid salt is used to generate an organic acid gas from an organic acid gas generator 3 to be mixed with a sample gas for introduction into an ion source 4 for ionization, thereby obtaining a mass spectrum by a mass analysis region 5. A data processor 6 determines the detection or non-detection of a specific m/z of an organic acid adduct ion obtained by adding a molecule generated from the organic acid to a molecule with specific m/z generated from a target chemical substance to be detected based on the obtained mass spectrum. When there is an ion peak with the m/z of the organic acid adduct ion, the presence of the target chemical substance to be detected is determined, and an alarm is sounded. False detection can be prevented.

A method and apparatus as disclosed for face detection within images. A new vector, the discriminating feature analysis vector, is introduced to represent an image to be analyzed, from the DFA vector as processed using a Bayesian Classifier technique. The methodology provides a computationally efficient manner in which to detect faces with relatively low probability of error and false detection rate.

The invention discloses a face recognition method, device, system and apparatus based on a convolutional neural network (CNN). The method comprises the following steps: S1, face detection: using a multilayer CNN feature architecture; S2, key point positioning: obtaining the key point positions of the face by using connecting reference frame regression networks in a cascaded way in deep learning; S3, preprocessing: obtaining a face image with a fixed size; S4, feature extraction: obtaining a feature representative vector by means of a feature extraction model; and S5: feature comparison: determining the similarity according to a threshold or giving a face recognition result according to distance sorting. The method adds a multilayer CNN feature combination to a traditional CNN single-layer feature architecture to treat different imaging conditions, trains a face detection network with good robustness in the monitoring environment from massive image data sets based on a deep convolution neural network algorithm, reduces a false detection rate, and improves detection response speed.

A motion detection method, apparatus and system are disclosed in the present invention, which relates to the video image processing field. The present invention can effectively overcome the influence of the background on motion detection and the problem of object “conglutination” to avoid false detection, thereby accomplishing object detection in complex scenes with a high precision. The motion detection method disclosed in embodiments of the present invention comprises: acquiring detection information of the background scene and detection information of the current scene, wherein the current scene is a scene comprising an object(s) to be detected and the same background scene; and calculating the object(s) to be detected according to the detection information of the background scene and the detection information of the current scene. The present invention is applicable to any scenes where moving objects need to be detected, e.g., automatic passenger flow statistical systems in railway, metro and bus sectors, and is particularly applicable to detection and calibration of objects in places where brightness varies greatly.

The invention discloses a lane line detection and GIS map information development-based vision navigation method. The method comprises the following steps: acquiring GIS map information, preprocessing, carrying out real-time image acquisition and lane line detection to generate a GIS local map in real-time, carrying out coupling verification on a track line detection result and the GIS local map through an ICP algorithm, and generating a high-credibility track line result according to the coupling result. The method can realize the credibility evaluation of the lane line detection through a geographic information system, corrects when false detection or missing inspection appears, expands the application range of the lane detection algorithm, and also can improve the map positioning precision through visual perception information, so the performances of a vision navigation system in a whole intelligent driving and aided driving system are improved, thereby the system can adapt to more complex environments.

A method and a system for dynamically detecting and correcting anomalous pixels in the raw data taken from an image sensor array such as a CCD or a CMOS sensor array, thus allowing the use of dumb cameras to capture digital images for subsequent use by an intelligent host—such as being displayed on a computer monitor. This invention uses software algorithms running on an intelligent host processor to dynamically correct the anomalous pixels in the raw data taken from an image sensor array typical of those in a digital still or a video camera. Using the combination of a dumb camera which provides raw data to an intelligent host, which does all the subsequent image processing, the system works by scanning an image frame for pixels that vary more than a specified amount in their brightness value from their neighboring pixels and designating those as defective pixels. The location and frequency of the photosites sending the defective pixels are stored in a statistical database in the computer's memory. The brightness value of a defective pixel is then replaced by a local brightness value obtained from the defective pixel's neighboring pixels. The process includes video subsampling, meaning that the defective pixel detection is carried out and repeated at a pre-specified frame rate to ensure optimum detection and correction at a minimal level of scanning. A statistical database is kept so that truly anomalous pixels can over time be distinguished from false detection of true anomalies in the target image, lighting or other environmentally induced anomalies.

The present invention relates to receiving access signals from a plurality of terminals over a radio channel and in particular to determining a detection threshold level on the radio channel. A detection threshold level should balance the risk of missed detections to the risk of false detections. A problem in finding an equilibrium threshold is the radio environment, with noise and interference, change and then also the radio false detections or missed detections change. According to the present invention some access signals can be identified as being not assigned and therefore not being in use, and any detection of a non-used signal is identified as a false detection. By monitoring the ratio of false detections vs. correct detections the threshold level for detection is tuned into an equilibrium level, and that is adapted to the changing radio environments. In addition the detection threshold level for access signals detection threshold for data and/or control signalling may be adjusted in relation to the access signal threshold level.

A method and apparatus for detecting a spread spectrum signal is described. Signals can be detected using correlation techniques. When a signal is detected, declaring of signal presence is inhibited for offsets of signal parameters from the parameters of the detected signal, where the offset corresponds to a known sidelobe of the spreading code. This helps to reduce false detections caused by sidelobes of the spreading code.

The invention discloses a trademark detection method based on a convolutional neural network. According to the method, various kinds of trademark pictures and pictures without trademarks are collected, and the pictures with the trademarks are marked; the convolutional neural network is initialized and is trained through trademark samples and non-trademark samples. In the picture testing process, candidate windows which may contain the trademarks in pictures to be tested are selected through a target area selection method, and color space conversion and scaling processing are carried out on the candidate windows; then the candidate windows are input into the convolutional neural network for recognition, and the candidate windows which are recognized to be the trademarks are marked in the pictures to be tested. According to the method, target area characteristic extraction and recognition are combined through the convolutional neural network, uncertainty caused by characteristic design is avoided, besides, good invariability is maintained during rotation, translation and scale changing, detection speed is increased Based on selection of the divided target area, and meanwhile the false detection rate is lowered.

A method and system for computer assisted automatic error detection and diagnosis of file servers. Software modules periodically and continuously review monitoring statistics gathered by the file server regarding its operation. The monitoring statistics are processed by a pattern matching system and a rule-based inference system. Software modules augment known network protocols, by manipulating parameters of lower-level protocols using different higher-level protocols. Using the higher-level protocols, software modules determine if the selected parameters for the lower-level protocols are correct. Software modules track hardware and software configuration changes to the file server, and relate changes in known monitoring statistics to timing of those hardware and software configuration changes.

An object of the present invention is to provide a detection device which does not cause the false detection by receiving laser light from an oncoming car. The pulse laser light modulated with a modulation pattern set every target position is irradiated at the target position from a laser irradiation portion. DSP (Digital Signal Processor) decides that there is an obstacle at the target position only when the modulation pattern of the pulse laser light emitted from the laser emitting portion matches with the modulation pattern of the pulse laser light received by the laser receiving portion. It is suppressed that the detection device misdetects the conditions of the target position when receiving laser light from an oncoming car or the like because modulation pattern of laser light from own does not match with modulation pattern of laser light from the oncoming car or the like.

An apparatus for verifying an inspection result includes an inspection result obtaining unit to obtain inspection result indicating defect amount and defect position in a scanned image, from an inspection result of defect judgment of the scanned image with respect to an inspection reference image, the defect judgment being performed through dividing at least one of the scanned image and the inspection reference image and conducting position matching of the scanned image and inspection reference image; and a verification unit to count defect amount occurring to the scanned image, to determine whether a defect pattern occurring to the scanned image matches a pre-set condition corresponding to a false detection condition causable by failure of the position matching, and to determine that defect occurring to the scanned image is a false detection when the counted defect amount is a threshold or more, and the defect pattern matches the false detection condition.

The invention discloses a video shot detection method based on histogram improvement and a clustering algorithm, and relates to image processing techniques. According to the method, the histogram improvement and the clustering algorithm are adopted to compute an intersection of histograms of two adjacent frames of images, and whether a shot change happens is judged according to histogram similarity; if the shot change happens, secondary detection on a shot boundary of the intersection of the histograms of the two adjacent frames of images is carried out by utilizing interframe gray scale/color difference values, pixel difference value computation on each block is carried out respectively by adopting non-uniform block weighting processing, pixel difference values and preset block frame differential threshold values are compared to obtain identification variables, the identification variable of each block is weighted and summarized, and the weighing and summarizing values and the preset block differential threshold values are compared to carry out shot detection. The video shot detection method improves shot detection accuracy and solves the problems of shot false detection, frame number discontinuity, and the like.

A CAM and method for operating a CAM are presented. Copies of a CAM database are duplicated and placed in a first set of CAM locations and a second set of CAM locations. An error detector is used to determine false matches in the case of soft errors within the entries producing those false matches. While the entries producing a match should have the same index location, errors might cause those match lines to have an offset. If so, the present CAM, through use of duplicative sets of CAM locations, will detect the offset and thereafter the values in each index location that produces a match, along with the corresponding parity or error detection encoding bit(s). If the parity or error detection encoding bit(s) indicate an error in a particular entry, then that error is located and the corresponding entry at the same index within the other, duplicative set of CAM locations is copied into the that erroneous entry. Since duplicative copies are by design placed into the first and second sets of CAM locations, whatever value exists in the opposing entry can be written into the erroneous entry to correct errors in that search location. The first and second sets of CAM locations are configurable to be duplicative or distinct in content, allowing error detection and correction to be performed at multiple user-specified granularities. The error detection and correction during search is backward compatible to interim parity scrubbing and ECC scan, as well as use of FNH bits set by a user or provider.

An obstacle detection apparatus includes a transmission antenna transmitting radio waves, a reception antenna receiving radio waves transmitted to and reflected by an obstacle, an obstacle detection unit configured to detect the obstacle based on the received radio waves, a false detection determination unit configured to determine presence or absence of a false detection characteristic, which is set in advance, with regard to the detected obstacle, a camera capturing an image, and an obstacle existence determination unit configured to determine, based on the image captured by the camera, presence or absence of the obstacle on which it is determined that the false detection characteristic is present.

The invention relates to the technical field of face recognition, in particular to a rapid detection method of a face in a high-resolution color image under a complex background. The invention comprises the following steps: building a face skin color mixed model which is composed of two color space restrictions of RGB and YCbCr according to a large amount of acquired skin color sample data to determine the skin color pixel; rapidly skipping non-face regions by adopting a whole skin color pixel ratio to improve the location efficiency of a face candidate region; then using the improved face rapid detection algorithm which is based on forward characteristic selection to realize face preliminary judging of the face candidate region; and finally utilizing a false alarm restraining method which is based on space restriction and geometric restriction to further lower false detection rate and complete face detection. The invention can realize rapid location of a plurality of frontal faces in images at a high detection rate under the condition of low false alarm rate; the good performances of the invention are proved by the results of the test set of Bao open database and a plurality of video frequencies and high resolution color images.

The invention belongs to the technical field of intelligent traffic and relates to a monocular vision based front vehicle detection and ranging method. The method is implemented by comprising: (1) converting a video image acquired by a vehicle-mounted camera into a gray image; (2) selecting a region of interest according to a camera imaging range to perform histogram equalization; (3) initially detecting an equalized image by using a classifier to obtain a rectangular region containing vehicle information; (4) verifying an initial detection result by using priori knowledge to remove false detections; (5) calculating an intersecting line of a tire and the ground by utilizing a vehicle bottom shadow to obtain an accurate vehicle position; and (6) performing vehicle ranging by taking the vehicle position and a lane line detection result as priori information. According to the method, the problems of illumination sensitivity due to single use of a priori knowledge based method and excessive false detections generated in a machine vision based method are solved; the vehicle can be accurately and effectively detected and the vehicle ranging is accurate; and the real-time requirement of intelligent vehicle control can be met.

The invention discloses a multilayer convolutional neural network-based power transmission line equipment image defect detection method and system. The method comprises the steps of performing modularpreprocessing on an original training set image, and inputting the image subjected to the modular preprocessing into a multilayer convolutional neural network model for performing training; for the image subjected to the modular preprocessing, selecting different training set sizes and training parameters, repeating the step 2 for performing multi-time experiments, performing comparative analysison classification accuracy and efficiency, selecting out optimal training parameters and performing storage; and performing filtration through a judger formed based on an environment structure and priori knowledge, and correcting false detection and missing detection information to obtain a final image defect detection result. The method and the system have the beneficial effects that a machine learning model with multiple hidden layers is built, and valuable expressive features are learnt from a large amount of data, so that the classification or prediction accuracy is improved.

There is provided an environment recognizing device for a vehicle capable of reducing false detections for an artificial object such as a utility pole, a guardrail and road paintings with smaller processing load, at the time of detecting a pedestrian by using a pattern matching method. The environment recognizing device for a vehicle includes an image acquisition unit (1011) for acquiring a picked up image in front of an own vehicle; a processing region setting unit (1021) for setting a processing region used for detecting a pedestrian from the image; a pedestrian candidate setting unit (1031) for setting a pedestrian candidate region used for determining an existence of the pedestrian from the image; and a pedestrian determination unit (1041) for determining whether the pedestrian candidate region is the pedestrian or an artificial object depending on a gray-scale variation rate in a predetermined direction within the pedestrian candidate region.

The invention discloses an improved visual attention model-based method of a natural scene object detection, which mainly solves the problems of low detection accuracy rate and high false detection rate in the conventional visual attention model-based object detection. The method comprises the following steps of: (1) inputting an image to be detected, and extracting feature saliency images of brightness, color and direction by using a visual attention model of Itti; (2) extracting a feature saliency image of a spectrum of an original image; (3) performing data sampling and marking on the feature saliency images of the brightness, the color, the direction and the spectrum and an attention image of an experimenter to form a final rough set information table; (4) constructing attribute significance according to the rough set information table, and obtaining the optimal weight value of the feature images by clustering ; and (5) weighing feature sub-images to obtain a saliency image of the original image, wherein a saliency area corresponding to the saliency image is a target position area. The method can more effectively detect a visual attention area in a natural scene and position objects in the visual attention area.

The invention discloses a method for detecting the error of a program control flow and intends to overcome the difficulties in increasing the detection rate of the errors of the control flow by the conventional method and solve the difficult problem with the detection of the control flow inside basic blocks and among processes. The method comprises the following steps according to the technical scheme of the invention: firstly, identifying basic blocks and confirming the routing relation among the basic blocks; then, confirming the maximum required number of detection commands of the internal control flow of each basic block according to the requirements of the internal control flow and the constitutive characteristics of the basic blocks; designing the labels for the basic blocks on that basis, and distributing the unique static label to each basic block; then, inserting the detection commands into the head part, inner part and tail part of each basic block in the program respectively, re-assembling and re-linking the assembler of the inserted detection commands of the control flow, and generating an executable program for achieving the detection of the error of the control flow.

A communications system improves performance of detecting a signal having an indication of a request to change communications states by making at least two positive identifications of the request in a given time frame. The system may further improve performance by applying a difference in power levels for a non-request state (i.e., steady state or ‘control hold’ state) versus a request state (i.e., ‘request to change’ state). In one particular application, a base station determines a request to change communications states with a reasonably high probability of detection and a reasonably low probability of false detection. The system has a reduced number of erroneous communications states, such as erroneous traffic channel allocations. The detection technique is compatible with 1xEV-DV systems and I-CDMA systems, but general enough to support systems employing various other communications protocols used in wired and wireless communications systems.