1449 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.

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.

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.

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.

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.

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.

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.

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.

The present invention encompasses a physical or virtual, computational, analysis, fusion and correlation system that can automatically, systematically and independently analyze collected sensor data (upstream) aboard or streaming from aerial vehicles and/or other fixed or mobile single or multi-sensor platforms. The resultant data is fused and presented locally, remotely or at ground stations in near real time, as it is collected from local and/or remote sensors. The invention improves detection and reduces false detections compared to existing systems using portable apparatus or cloud based computation and capabilities designed to reduce the role of the human operator in the review, fusion and analysis of cross modality sensor data collected from ISR (Intelligence, Surveillance and Reconnaissance) aerial vehicles or other fixed and mobile ISR platforms. The invention replaces human sensor data analysts with hardware and software providing two significant advantages over the current manual methods.

The invention discloses a people counting method and device based on head shoulder detection. The people counting method based on head shoulder detection comprises steps of S1 arranging a heat area and a base line in a monitor video, S2,performing head-shoulder detection on the heat area in the image frame of the monitor video, S3,determining whether the head and the shoulder exist according to the head shoulder detection result, if yes, executing the step S4, S4 setting a head-shoulder frame and maintaining or updating a tracking list and continuing to execute the step 6, S6, performing tracking on each head-shoulder frame in the tracking list to obtain a group of tracking frames, S7, determining whether the tracked head-shoulder frame in the current frame satisfies a people counting trigger condition, S8, starting up a counter and performing people counting according to the tracked head-shoulder frame. The invention discloses a people counting device based on the head-shoulder detection. The people counting method based on the head-shoulder detection is wide in application range, high in detection, low in false detection rate and high in tracking performance.

The invention discloses a method for extracting text information from adaptive images, and relates to technology for extracting text information from images. The method comprises the following steps: 1) preprocessing the images; 2) analyzing complexities of the backgrounds of the images; 3) initially detecting texts; 4) verifying the texts; 5) extracting the texts; and 6) outputting or displaying the text information. The method adopts different text detection methods for the images with different complexities of the backgrounds by computing the complexities of the backgrounds of the images, reduces missing and false detection caused by a single text detection method, and improves the overall performance of a text extracting system. The computation method of the complexities of the backgrounds of the images is simple and effective. The method can detect text information in the images with different complexities of the backgrounds, and the text information detected by the method is free from the influence of type-font, word size and language; and the method has strong commonality.

The invention discloses a vehicle detection system based on binocular stereo vision and a method thereof. The system comprises binocular parallel cameras, a DSP processor, communication and other modules. The system is vertically installed above a lane in a top-down mode so as to carry out real-time detection on road vehicles. The method comprises the following steps of (1) carrying out main point difference calibration on left and right cameras in advance and acquiring an accurate main point difference parameter; (2) collecting left and right images in real time so as to carry out detection and extraction of a foreground moving object; (3) carrying out stereo matching on an extracted and acquired foreground object area and acquiring a current frame parallax image; (4) carrying out subsequent processing on the acquired parallax image and removing a false detection area, simultaneously acquiring a two-dimensional ground plane mapping image; (5) through calculation, acquiring correlation parameters of a speed, a vehicle height, a vehicle model and the like. In the invention, the binocular cameras are used; a stereo vision principle is used so as to acquire depth information of the object; problems that a monocular vision technology is sensitive to light changes and is easy to be disturbed by shadow are solved.

The invention discloses a vehicle detection method based on laser and vision fusion. The method comprises the following steps of 1) acquiring target detection information for an input image and laserpoint cloud; 2) performing optimal matching on the images of the front frame and the rear frame and the point cloud detection frame, and establishing a tracking sequence of an image and point cloud detection target; 3) fusing the tracking sequences of the image and the detection frame thereof and the tracking sequences of the point cloud and the detection frame thereof; 4) classifying all the target detection boxes, outputting a fusion list, and outputting a fusion result; and 5) obtaining the accurate position of the surrounding vehicle relative to the vehicle in the current frame, reading the next frame of image and the point cloud data, circulating the steps 1) to 5), and outputting a fusion detection result. According to the method, on the basis of point cloud and image target detection, the detection result is subjected to information tracking, the detection result is optimally matched, and the fusion result is preferentially input into the final fusion list, so that compared witha single sensor target detection method, the target detection precision is improved, and the false detection rate is reduced.

The patent discloses an intersection vehicle violation detection and identification method based on deep learning. The method comprises the following steps of 1, collecting intersection video detection images; 2, identifying traffic signs and vehicles; 3, tracking the vehicles; and 4, performing vehicle violation detection and identification. Based on automatic identification and tracking of the traffic signs and the vehicles in the intersection monitoring videos, the violation conditions of vehicles at the intersection can be automatically identified, and the system has few false detection and high efficiency.

An adaptive file delivery system and method transmits a data file, such as an audio-video file, over a network or collection of networks in segments, each segment transmitted during a different time period. Each time period has a transmission portion to transmit its associated file segment and a wait portion in which no further interaction with the network occurs regarding the transmitted segment. In some implementations, the duration of the transmission portion of each time period is sufficient to reach a steady-state throughput condition, which allows the traffic load status of the network or networks to be determined from rate measurements of file segment transmissions. A peak flow determination is made to assure that the delivery of file segments does not cause network congestion. The system has spurious peak rejection to avoid the false detection of network congestion.

The invention discloses a false-detection resistant annular coil vehicle detector comprising an oscillating circuit module, a parameter setting module, a frequency measuring module, a central processing module, an RS-232 communication module and the like. The annular coil is connected with the oscillating circuit module of a vehicle detector through a coupling transformer of 1:1 to form a high-frequency oscillating circuit; the frequency measuring module is used for carrying out shaping and frequency division on an oscillating signal and feeding the finally-calculated signal frequency valve to a singlechip control system; a singlechip is used for sampling a measuring value of the frequency measuring module at regular time; the measuring value is subjected to filter processing and is detected by an embedded vehicle detection algorithm; a detection state is displayed by an LED; and the detection result can be output by a pulse manner or transmitted to an upper computer through an RS-232 bus. The invention improves the design of a threshold detection algorithm, uses a single threshold method for detecting the arrival of the vehicle and uses a flatness determination method for detecting the leaving of the vehicle. In addition, by adopting the invention, the arrival and leaving moments of the vehicle can be accurately detected, the phenomena of false detection caused by multiple false triggers are reduced, and the stability of the system is enhanced.

The invention belongs to the field of automatic detection and control of textile quality and particularly relates to a method for automatically detecting defects of textiles based on support vector data description theory. The automatic textile defect detection based on computer vision is a more difficult one-class classification task in real world. In the invention, support vector data description (SVDD) of the advanced one-class classification method is applied in the textile defect detection field for the first time to obviate the problems present in textile defect detection of conventional two-class classification support vector machine, which is difficult to collect representative defect samples completely and at larger number and further fails to effectively train the detector. Additionally, the invention provides a robust new method for solving the optimization problem of parameters, in particular to scale parameter of gauss kernel function, related in SVDD training. The automatic textile defect detection system based on SVDD can prospectively and conveniently control false alarm rate (false detection rate) in practice and can obtain lower miss ratio at lower false alarm rate.

A technique in which a false detection and a wrong diagnosis can be suppressed in a capacitance sensor represented by an acceleration sensor is provided. A first capacitative element and a second capacitative element, which configure a capacitance detection unit, and a third capacitative element and a fourth capacitative element, which configure a forced oscillation generation unit, are electrically separated from each other. That is, the diagnosis movable electrode that configures the third capacitative element and the fourth capacitative element is formed integrally with the movable part. On the other hand, the diagnosis fixed electrode and the diagnosis fixed electrode are electrically separated from the detection fixed electrode and the detection fixed electrode.

The invention discloses a power transmission line intelligent patrol system based on image vision, relates to the technical field of overhauling of electric system power transmission lines, and aims to solve the problems of high cost, low efficiency and the like in existing power transmission line patrol. The power transmission line intelligent patrol system comprises an image acquisition system (1), an image storage and management system (2) and an image intelligent processing system (3), wherein the image acquisition system (1) is used for transmitting an acquired power transmission line image to be detected to the image storage and management system (2); and the image storage and management system (2) is used for outputting a classified and marked image to the image intelligent processing system (3) to perform power transmission line fault detection. Through adoption of a method disclosed by the invention, the problems of high cost, low efficiency, high false detection rate and high missing detection rate due to execution of a detection task along a line by patrol personnel in conventional power transmission line patrol are solved.

The invention relates to an identification method of a remote sensing image building, belonging to an identification method of a remote sensing target image; the method overcomes the problems of false detection and miss-detection of the building in the existing detecting method of the building for improving the accurate detecting rate. The identification method sequentially comprises the following steps: region division, initial extraction of the building, road filtration and following extraction of the building. The identification method has good stability and strong environment adaptive capacity, and can solve the problem that the buildings and the roads close to the adjacent optical spectrum are confused, and the method can detect the building target with different shape structure and optical spectrum characteristics in the same image, the extracting result of the building has high accurate rate and good robustness, and the method can effectively extract various building targets under the remote sensing images with high resolution, therefore, the identification method has practical value in the construction of a geographical information system and a digital city system.

A control apparatus for an internal combustion engine can compensate for a variation of intake pressure resulting from various factors whereby a failure detection area can be expanded, and false detection can be prevented to enable failure determination for an EGR system with high reliability. The apparatus determines whether a vehicle is decelerating, forcedly opens and closes an EGR valve, and determines whether an EGR control device is in failure by comparing a pressure change index value based on intake pressures upon the forced opening and closing of the EGR valve with a failure determination value. The apparatus adjusts the intake pressure to a predetermined state before the EGR valve is forcedly opened and closed, whereby a failure determination can be always made based on the intake pressure whose variation was compensated for with the intake pressure becoming a predetermined characteristic to the number of revolutions per minute of the engine.

A method detects similar objects in a collection of such objects by modification of a previous method in such a way that per-object memory requirements are reduced while false detections are avoided approximately as well as in the previous method. The modification includes (i) combining k samples of features into s supersamples, the value of k being reduced from the corresponding value used in the previous method; (ii) recording each supersample to b bits of precision, the value of b being reduced from the corresponding value used in the previous method; and (iii) requiring l matching supersamples in order to conclude that the two objects are sufficiently similar, the value of l being greater than the corresponding value required in the previous method. One application of the invention is in association with a web search engine query service to determine clusters of query results that are near-duplicate documents.

An object of the present invention is to detect a three-dimensional object by use of a single-eyed camera with a higher degree of accuracy by eliminating false detection of an obstacle, which is caused by a detection error of a vehicle speed sensor or that of a rudder angle sensor.

A top view of a first image including a road surface image is created. The first image is imaged by a camera mounted to a vehicle. Then, a top view of a second image is created. The second image is imaged at a timing different from the timing when the first image is imaged. The two top views are associated with each other on the basis of a characteristic shape on the road surface. In each overlapped portion of the two top views, an area in which a difference occurs is identified as an obstacle.