6039 results about "Visual detection" patented technology

Spatially Integrated Small-Format Aerial Photography (SFAP) is one aspect of the present invention. It is a low-cost solution for bridge surface imaging and is proposed as a remote bridge inspection technique to supplement current bridge visual inspection. Providing top-down views, the airplanes flying at about 1000 feet can allow visualization of sub-inch (large) cracks and joint openings on bridge decks or highway pavements. On board Global Positioning System (GPS) is used to help geo-reference images collected and facilitate damage detection. Image analysis is performed to identify structural defects such as cracking. A deck condition rating technique based on large crack detection is used to quantify the condition of the existing bridge decks.

A method of visually detecting a leak of a chemical emanating from a component. The method includes: aiming a passive infrared camera system towards the component; filtering an infrared image with an optical bandpass filter, the infrared image being that of the leak; after the infrared image passes through the lens and optical bandpass filter, receiving the filtered infrared image with an infrared sensor device; electronically processing the filtered infrared image received by the infrared sensor device to provide a visible image representing the filtered infrared image; and visually identifying the leak based on the visible image. The passive infrared camera system includes: a lens; a refrigerated portion including therein the infrared sensor device and the optical bandpass filter (located along an optical path between the lens and the infrared sensor device). At least part of a pass band for the optical bandpass filter is within an absorption band for the chemical.

The invention discloses a system for visually detecting workpiece appearance defects based on image processing, comprising an industrial personal computer, a coaxial light source, a CCD (charge coupled device) industrial camera, an image acquisition card and a rejecting mechanism; both the coaxial light source and the rejecting mechanism are connected with the industrial personal computer; the CCD industrial camera is connected with the industrial personal computer through the image acquisition card; wherein the coaxial light source is used for providing a diffuse reflection light source for a workpiece to be detected; the CCD industrial camera is used for taking an image of the workpiece at a detection station; the rejecting mechanism is used for rejecting from a production line, workpieces detected to be defective; the industrial personal computer has a defect detection module based on image processing; the system is high in detection efficiency and easy to implement.

Disclosed are methods and apparatus for automatic optoelectronic detection and inspection of objects, based on capturing digital images of a two-dimensional field of view in which an object to be detected or inspected may be located, analyzing the images, and making and reporting decisions on the status of the object. Decisions are based on evidence obtained from a plurality of images for which the object is located in the field of view, generally corresponding to a plurality of viewing perspectives. Evidence that an object is located in the field of view is used for detection, and evidence that the object satisfies appropriate inspection criteria is used for inspection. Methods and apparatus are disclosed for capturing and analyzing images at high speed so that multiple viewing perspectives can be obtained for objects in continuous motion.

The invention discloses a multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and a control method. The system includes an environment information real-time detection module which carries out real-time detection on surrounding environment through adopting a multi-sensor fusion technology and transmits detected information to an obstacle data analysis processing module, the obstacle data analysis processing module which carries out environment structure sensing construction on the received information of the surrounding environment so as to determine an obstacle, and an obstacle avoidance decision-making module which determines an obstacle avoidance decision according to the output result of the obstacle data analysis processing module, so as to achieve obstacle avoidance of an unmanned aerial vehicle through the driving of power modules which is performed by a flight control system. According to the multi-sensor fusion-based autonomous obstacle avoidance unmanned aerial vehicle system and the control method of the invention, binocular machine vision systems are arranged around the body of the unmanned aerial vehicle, so that 3D space reconstruction can be realized; and an ultrasonic device and a millimeter wave radar in an advancing direction are used in cooperation, so that an obstacle avoidance method is more comprehensive. The system has the advantages of high real-time performance of obstacle detection, long visual detection distance and high resolution.

The invention discloses a camera on-field calibration method in a measuring system, belonging to the field of computer vision detection, in particular to an on-field calibration method for solving inside and outside parameters of cameras in a large forgeable piece size measuring system. Two cameras and one projector are provided in the measuring system. The calibration method comprises the following steps of: manufacturing inside and outside parameter calibration targets of the cameras; projecting inside parameter targets and shooting images; extracting image characteristic points of the images through an image processing algorithm in Matlab; writing out an equation to solve the inside parameters of the cameras; processing the images shot simultaneously by the left camera and the right camera; and measuring the actual distance of the circle center of the target by using a left theodolite and a right theodolite, solving a scale factor and further solving the actual outside parameters. The invention has stronger on-field adaptability, overcomes the influence of impermeable and illegible images caused by the condition that a filter plate filters infrared light in a large forgeable piece binocular vision measuring system by adopting the projector to project the targets, and is suitable for occasions with large scene and complex background.

The invention provides a method for collaborative mapping and locating of multiple robots for a large-scale environment. The method comprises a single-robot laser SLAM algorithm based on a visual detection closed loop, a multi-robot pose constraint estimation algorithm and a multi-robot map fusion algorithm, wherein according to the single-robot laser SLAM algorithm based on the visual detection closed loop, a visual sensor is adopted for assisting a laser sensor in achieving the SLAM algorithm with the more stable roughness. Simultaneous locating and mapping of the multiple robots are achieved through the laser sensor and the visual sensor. The closed loop is detected by obtaining the visual characteristic of the roughness through a camera, and the problem about closed loop detection caused by the robot motion accelerative error is solved effectively; meanwhile through a multi-robot system, simultaneous locating and mapping in the large regional environment are completed efficiently, and the defect that the efficiency is low by means of a single robot is overcome. By the adoption of the method, the precise robot location and map creation of the environment are achieved in the large-scale environment, and the method is also suitable for small-scale environments.

Methods and apparatus for collecting a fluid sample using an integrated collection device are disclosed. The integrated collection device includes an analyte detector and a gradient means to actively and rapidly drive the transport of a sample fluid from the point of contact to the point of detection and reading. The analyte detector can include a visually-read colorimetric detector using a chemical or enzymatic detection process. The gradient means can include physical and/or chemical processes as described in more detail herein. In some embodiments, the device is provided as an occlusive patch. Preferably, the test device provides a reading immediately upon fluid contact with the analyte detector. Consequently, the time-to-result is sample volume and transport time dependent. By providing immediate or nearly immediate reading of results, the device is particularly useful in those applications in which immediate results are advantageous.

The invention discloses a deep convolutional neural network-based abnormal crowd behavior visual detection and analysis early warning system. The system comprises a camera mounted at a monitoring target facility, a security prevention cloud server and an abnormal crowd behavior visual detection and analysis early warning system. In the system, various human body objects in the target facility areextracted through a deep convolutional neural network technology; then motion states of human bodies are calculated, identified and judged by using an optical flow method; different states of the human body objects are subjected to clustering and crowd modeling; further crowd objects are subjected to density calculation and danger index calculation; and finally according to different combinationsof crowd density, motion vector values and duration quantitative index data, various abnormal crowd behaviors are identified and judged, and according to the states of the abnormal crowd behaviors, corresponding crowd gathering management control policies are enabled. The deep convolutional neural network-based abnormal crowd behavior visual detection and analysis early warning system provided bythe invention is unlimited in scale, relatively high in precision and relatively good in robustness, and is based on a deep convolutional neural network.

A thinning or weeding apparatus includes an image processing apparatus. The image processing apparatus includes an automated visual detection system which includes a visual sensor system and an image processing system capable of receiving an image from the visual sensor system. The image processing apparatus then processes the image in the image processing system to determine where plants are located and to determine which plants will be thinned or weeded and which will not.

A detecting and error-correcting method capable of rapidly and accurately obtaining an element center and a deflection angle is disclosed. Interested edge area can be rapidly and accurately found out through an automatic edge area extraction method based on combination of binary morphology and image reduction, and subsequent edge extraction image scope is minimized as possible. Pixel level edge is roughly positioned at first, and accordingly a sub-pixel edge is rapidly extracted by one-dimensional curve fitting method. The method overcomes the defect of complex algorithm of a conventional sub-pixel edge extraction algorithm based on two-dimensional images, and the time of extracting accurate sub-pixel edge can be shortened. Weighted least square rectangular edge fitting algorithm based on linear hazen paradigm can detect straight lines on any positions of an image, and effectively minimizes influence of outlier on fitting precision due to uneven edges. The central positions of a plurality of elements and deflect angles can be rapidly and accurately detected at once, and the efficiency of visual detection is improved.

The invention provides a solar silicon wafer defect detecting system. The solar silicon wafer defect detecting system comprises a visual image acquisition system, an image processing system and a sorting system; the visual image acquisition system is used for automatically acquiring images of silicon wafers on an automatic silicon wafer production line; the image processing system is used for analyzing the acquired silicon wafer images, automatically identifying the silicon wafer images and sending identification signals to the sorting system; and the sorting system is used for executing the signals of the image processing system, sorting out defective silicon wafers and sorting the silicon wafers with the same defects into same sorting boxes to realize accurate sorting of the silicon wafers. The invention also provides a detecting method based on the solar silicon wafer defect detecting system disclosed by the invention; the silicon wafers can be conveyed rapidly and rapid defect detection of the silicon wafer images can be carried out; and a high-speed and high-precision visual detection requirement of the production line can be met.

A three phase control arrangement is employed after visual detection of a target at greater range than otherwise available. The first and last phases employ an optimization criterion for which errors do not vary with distance from a target; limiting the initial error and process error in an intermediate phase which controls approach trajectory to the intended docking location and yielding repeatable high accuracy docking. The three phase approach with different control criteria and control gain parameters makes feasible a docking maneuver that begins at a much greater range and potentially greater lateral separation from the destination than would otherwise be possible, while providing control of both the final location and final orientation of the vehicle. A preferred visual thresholding technique provides consistency of results over a wide range of illumination and contrast conditions while limiting the computation burden for target image acquisition and tracking.

The invention discloses a device and a method for automatically detecting the flatness of road surfaces, relates to the field of road surface flatness detection, and aims at overcoming the defects of inaccurate information, a plurality of error sources, complex structure and unsolvable influence of vehicle body obliquity in the prior art. A three-dimensional optical vision detecting component of the device for automatically detecting the flatness of road surfaces comprises an angle sensor and an output end that is connected with an input end of a processing system; structured light bars that are emitted by a laser device of structured lights cover the longitudinal road surface, and the processing system is arranged inside the vehicle body. The method for automatically detecting the flatness of road surfaces comprises the followings steps: (1) the structured light bars of the laser device of structured lights implement imaging on a CCD area array after being modulated by three-dimensional road surface information, and simultaneously shaking information of the vehicle body is collected, and three-dimensional information is computed; (2) disease influence is eliminated by filtering; (3) depth displacement of the road surfaces is computed in the interval of 250mm, and an IRI result of a corresponding road section is computed; (4) data storage, analysis and display are implemented. The device and the method for automatically detecting the flatness of road surfaces have the advantages of complete and accurate extracted longitudinal outline, simple structure, and the eliminated influence of vehicle shaking.

A dog collar flashlight for providing illuminating light sufficient to perceive and visually detect items on the ground and adjacent the animal to which the dog collar flashlight is attached. A dog collar flashlight has an illuminating light that goes far beyond the providing of mere visibility but allows the visual detection of objects illuminated by the light such as cracks in the sidewalk, obstacles in the path of the dog wearing the dog collar flashlight, and the activation of reflective material by the illuminating light. The light is controlled by a selectable switch and is housed along with the switch in a casing that allows a collar to engage in the dog collar flashlight. Collar-engaging loop portions attached to the dog collar flashlight case allows a collar to engage the dog collar flashlight and fix the dog collar flashlight to the dog or other animal.

Disclosed are methods and apparatus for improvements to image capture and analysis for vision detectors. The improvements provide for asynchronous capture and analysis and allow high frame rates to be maintained when image analysis may under certain conditions comprise a significantly longer time interval than image capture. The improvements prevent memory buffer overflow and provide for short and predictable decision delays even though an arbitrary and potentially unlimited number of images are captured and analyzed for each object.

A visual detection device for parts mainly comprises an imaging system, an optical lens component, a lighting system, a mechanical adjusting system, a displacement detection system and a computer, wherein the imaging system consists of a CCD camera and an image acquisition card; the optical lens component consists of a lens body, an amplifying objective lens, and the like; the lighting system is respectively used for detecting surface defects and measuring topographic sizes; the mechanical adjusting system consists of displacement platforms used for adjusting the positions of the parts; the displacement detection system is used for recording the displacement distance of the displacement platforms; and the computer is used for recording and processing images. By shooting edge images of theparts through the imaging system and recording the displacement distance of the displacement platforms through the displacement detection system, the detection device calculates the topographic sizessuch as diameter, and the like, detects the surface defects of the whole spherical surface by the combined rotation of rotary tables, measures the defect sizes accurately, records the number of the defects and meets the two detection requirements of topography measurement and surface detection. By utilizing the visual microscopic detection technology, the device has high system resolution, good integrated performance and simple measurement process.

The high precision vision detection system includes the digital staff guage system, the illuminating system with adaptive adjusting optical intensity, the auto focus system, the optical image system, the vision detection software, the foundation, the computer or microprocessor system. The digital staff guage system is used to provide the high precision length detection base in large scale; the illuminating system is used to adjust the optical intensity according to the different of the detection distance, detection angle and the surface reflectivity of detected workpiece to provide the uniform and stable illuminating intensity to pledge the image quality and the detection precision; the auto focus system is used to adjust the working distance of the detection system to pledge the image has the good quality and constant amplification ratio and pledge the repeatability and detection precision of the detection system; the optical image system is the main part of the detection system, which is used to transform the geometry outlook of detected workpiece to the computer or processor through the optical lens image, the vidicon photoelectricity switch and collecting control circuit; the vision detection software is used to process the image and get the detection result; the foundation is the supporting frame of vision detection system, which is used to fix, support and move every part of system; the computer or microprocessor system is the core part of the whole vision detection system, which is used to coordinate and control every system.

The invention discloses a visual detection method of a road driving line. The invention comprises the following steps: firstly, detecting all of edges of a given original road image through edge detection, and obtaining an edge image; secondly, respectively defining search rules based on direction priority for a left lane line and a right lane line, using the search rules for searching the edge image, and recording each search path in the search so as to transform the edge image to a set of candidate line sections; thirdly, carrying out Hough transformation on each line section of the set of the candidate line sections, counting collinear points of the line sections in the Hough space, and filtering the line sections with the collinear points less then T2; and fourthly, utilizing luminance information of the original image for carrying on a series of transformation processing on the candidate line sections remained after processing in the third step, eliminating cracks of the road surface and regular edge interference of join of the new and old road surfaces, identifying the lane lines, and completing the positioning of the lane lines. The scheme of the invention follows an idea from coarseness to fineness, and has accurate positioning and high real-time performance when being compared with the prior scheme.

The invention discloses an automatic dispensing robot system and an automatic dispensing method, which are used for preparing an intravenous infusion solution. The system comprises a closed cavity, wherein the closed cavity can be opened, and an input module, a powder bottle shaking module, an ampoule bottle breaking module, a disinfection module, a quantitative injection module and a visual detection and motion control module are arranged in the closed cavity. According to the automatic dispensing robot system, the breaking, disinfection and quantitative suction of an ampoule bottle, the disinfection and quantitative suction of a powder bottle and the mixing with a mother solution can be automatically realized, and the solution is prevented from being polluted; additionally, nursing personnel are prevented from being radiated and hurt by harmful substances; the probability of misoperation is reduced; the operating standard of intravenous infusion dispensing is standardized; and the dispensing efficiency is increased.

The invention discloses a visual detection method of shockproof hammer defect detection. The visual detection method comprises the steps that denoising and anti-shaking preprocessing is performed on an aerial photographing image so as to obtain an original image to be detected; the existing original image is expanded by using the method of geometric transformation, scale change and contrast transformation so as to generate more data similar to the original image; samples are acquired, a shockproof hammer in the aerial photographing image is acquired and the size of the shockproof hammer is mainly acquired; a network model to be trained is determined, and the sample data are inputted to perform forward propagation and reverse propagation to adjust the weight so as to obtain the optimized detection network model parameters; the image to be detected is identified by using the trained model and the position of the hammer of the shockproof hammer is determined; and the lead in which the hammer is located is determined, and shockproof hammer defect discrimination is performed according to the relative position of the lead and the shockproof hammer and the constraints of respective directions.

The invention relates to a device and method for detecting defects on the surface of a solar cell. The device comprises a structural member and a detection circuit system. The structural member is composed of a display frame, an observation platform and an installation frame. The detection circuit system comprises an illumination unit, an image collection unit, an image processing unit and a display unit. In the detection process, an unfilled corner defect image is obtained by means of a low-angle annular white LED light source and by conducting image segmentation, wavelet transform and two-dimensional 7*7 pixel field median filtering on an image; for a crack, a defect image of the crack is obtained by conducting two-dimensional median filtering, wavelet transform, image binaryzation, edge detection and morphology operator processing on the image, the detection recognition result is obtained, and the image processing unit finally transmits the processing result to an upper computer of the display unit. The method and the device have the advantages that compared with a manual visual detection and infrared scanning detection method, detection efficiency and detection accuracy are greatly improved, the method is easy to operate and practicable, a large amount of labor force is saved, and the labor intensity is lowered.

The invention provides a sprayed character online visual detection method based on convolutional neural network. The sprayed character online visual detection method comprises the steps of dividing characters in an image under an offline status, classifying the characters, constructing a character repertoire, and performing training through an improved convolutional neural network learning method to form a stable classifier; shooting pictures, dividing the characters and classifying the characters in real time during online detection, and removing unqualified products. By means of the sprayed character online visual detection method, real-time performance is ensured while detection accuracy is improved greatly, and requirements for high real-time performance and accuracy of online detection process of the sprayed characters at bottoms of pop-top cans can be met.

The invention relates to an on-line detection grading device for a lithium ion battery pole piece and a method thereof. In the device, image data of the lithium ion battery pole piece are acquired by using an embedded visual recognition device and are analyzed and processed to judge whether the appearance quality of the pole piece meets requirements or not, so that the actions of a turnover part and a grading part are controlled to realize real-time on-line double-side detection and grading of the electrode pole piece. The method has high detection speed; generally, the detection of the frontside and the back side of one electrode pole piece can be finished within 1 second, so that the production efficiency is increased; if the pole piece is manually detected, longer time is required to be taken; the detection accuracy is high; the embedded visual detection technology is adopted, so that the accuracy is high and the stability is also realized, and a detection result has high uniformity; the running time is long, namely a detection system can uninterruptedly run for 24 hours, so that the productivity is improved and the labor cost is saved; and on-line detection can be realized, so that the on-line detection of the electrode pole piece is realized, the interference in a manual operation process is reduced, and the productivity is improved.