669 results about "Hough transform" patented technology

The present invention is to identify an individual from his or her iris captured from an imaging system. Basically the system can be divided into two processes, which are enrollment and verification. Each process consists of four steps. Both processes share the three beginning steps, which are image acquisition, image processing, and feature extraction. Image acquisition is to capture the real iris image of a user. Then image processing is applied to the acquired image. In the next step, the textural information of an iris image is generated into a signature in a process called feature extraction. For an enrollment process, the extracted iris signature will be stored in database for the future use of verification. In a verification process, the last step is to compare the iris signature generated from real time processing with the signatures previously stored. A final decision will be made to determine whether the user is successfully identified or not. The present invention introduces two new methods in the iris recognition algorithm. First, a new method called maximum vote finding method that is used during iris image processing was developed to reduce the time required for localization of inner iris after applying Hough Transform for localization of outer iris. Second, an iris signature based on fractal dimension characterization which is a novel approach used in iris feature extraction process was developed to provide satisfactory matching accuracy of iris images.

A digital image includes a plurality of pixels arranged in an array. In a method of analyzing the image, some of the pixels are purposefully not processed. In particular, only those pixels in a particular subgroup are processed according to a Hough or similar transform. The number of pixels in the subgroup is less than the total number of pixels in the image (e.g., as little as about 5% of the total pixels), and each pixel in the subgroup is pseudo-randomly selected. The Hough transform is inherently configured to function within the context of noisy images, for identifying features of interest in the image, as simulated by the pseudo-random selection and processing of less than the total number of pixels in the image. This significantly reduces the processor resources required to analyze the image.

An apparatus for recognizing gestures in a picture includes a Hough transformer configured to identify elements in the picture or in a pre-processed version of the picture as identified gesture elements and to obtain information about the identified gesture elements.The apparatus further includes a gesture description creator configured to obtain a gesture description while using the information about the identified gesture elements.Moreover, the apparatus includes a gesture classifier configured to compare the gesture description to a plurality of comparative gesture descriptions having gesture codes associated with them. The gesture classifier is configured to provide, as the result of the comparison, a gesture code of a recognized gesture.

The invention discloses an image-processing-based unmanned plane accurate position landing method, which comprises the following steps: (1) a GPS (global position system) satellite navigation system enables an unmanned plane to be located above a ground parking apron; (2) an air pressure height measurement gauge and a distance measurement module of an ultrasound radar are combined to control the ground clearance for the unmanned plane to land; (3) a vision module identifies a coarse positioning identification domain in real time, and combines Hough Transform and RGB mean value method and gate position identification to process a coordinate of a targeted landing point; (4) when landing of the unmanned plane meets the threshold condition of the coarse positioning identification domain, the algorithm in the step (3) is utilized to perform accurate positioning treatment on the accurate positioning identification domain; and (5) the unmanned plane is controlled for accurate landing by taking the treated deviation value as the input quantity and adopting the double PID algorithm. According to the invention, the defect that insufficient GPS accuracy of the unmanned plane causes a fault landing is overcome, the intelligence for the unmanned plane control is improved, and the cost for using an accurate sensor is greatly reduced.

A method and system for performing automated biological identification. The system including a preprocessing module with a histogram transform for locally and globally enhancing biological data such as fingerprints. An enhancement module with a fast smoothing and enhancement function. A feature extraction module with a fingerprint oriented thinning function. A matching module with a resolution-enhanced Hough transform function for fingerprint registration and matching score function.

The invention discloses an improved multi-instrument reading identification method of a transformer station inspection robot. In the method, first of all, for instrument equipment images of different types, equipment template processing is carried out, and position information of min scales and max scales of each instrument in a template database. For the instrument equipment images acquired in real time by the robot, a template graph of a corresponding piece of equipment is scheduled from a background service, by use of a scale invariant feature transform (SIFT) algorithm, an instrument dial plate area sub-image is extracted in an input image in a matching mode, afterwards, binary and instrument point backbone processing is performed on the dial plate sub-image, by use of rapid Hough transform, pointer lines are detected, noise interference is eliminated, accurate position and directional angel of a pointer are accurately positioned, and pointer reading is finished. Such an algorithm is subjected to an on-site test of some domestic 500 kv intelligent transformer station inspection robot, the integration recognition rate of various instruments exceeds 99%, the precision and robustness for instrument reading are high, and the requirement for on-site application of a transformer station is completely satisfied.

The invention discloses an automatic guidance system based on radio frequency identification labels and vision, and the method of the automatic guidance system. The invention is characterized in adopting a four-wheel structure, wherein two front wheels are used for steering and two rear wheels are used for driving; a direct current motor is used as the travelling and driving device, which is driven to steer by a stepping motor; the invention is provided with a wheel steering angle positioning device, so the invention has relatively high dynamic response ability; a black and white parallel guide belt is adopted as a guide path, with the radio frequency identification labels discontinuously laid below, and red work station characters arranged at both sides; CCD collects road surface information, and the brightness of light source adaptive controls according to image gray information; characters are extracted by utilizing color differences; straight lines are rapidly HOUGH transformed and identified; a control signal is sent to AGV controller after processed by an industrial control computer, and the direct current motor and the stepping motor are controlled. In order to effectively realize the communication dispatch between AGVS in real time, radio frequency identification labels are adopted for positioning, and a wireless transceiver module is adopted for communication between AGVS and a host. The invention has the advantages of good environmental adaptability and navigation precision, and lower cost.

A method of classifying radar emitters includes the steps of: (a) receiving pulses from multiple radar emitters; (b) categorizing received pulses based on pulse data descriptors (PDWs); (c) forming clusters of received pulses based on the PDWs; and (d) de-interleaving pulses from the cluster using one of a differential time of arrival (DTOA) histogram technique, a spectrum estimation technique, or a Hough transform technique. Step (a) includes receiving the pulses during a predetermined time interval and storing the received pulses as a snapshot representing the pulses present during the predetermined time interval.

The invention discloses a fast image recognition method of an insulator contour, comprising the following steps: (1) transforming a taken color image to a gray image through brightness calculation and extracting the edge contour of the image, and obtaining the shape of a known region after the extraction; (2) carrying out ellipse fitting on the edge contour of the known region, utilizing hough transform to detect a boundary curve and obtain each parameter of a prolate axis, a minor axis and a central point of an ellipse; (3) carrying out threshold processing on contour area, and setting a proper area threshold according to the contour area; (4) carrying out linear fitting on the center of the ellipse, and fitting a line through a two-dimensional point set by seeking sumi rho(ri); and (5) demarcating and outputting insulator pixels. The invention aims at specific requirements of patrol and examination of a helicopter or a robot to an electric transmission line, realizes real-time and precise extraction of the insulator, provides solid foundation for realizing close shot and part defect diagnosis of a follow-up camera, and has favorable theory and application prospect.

The present invention provides a method for the recognition of objects in an image, where the objects may consist of an arbitrary number of parts that are allowed to move with respect to each other. In the offline phase the invention automatically learns the relative movements of the single object parts from a sequence of example images and builds a hierarchical model that incorporates a description of the single object parts, the relations between the parts, and an efficient search strategy. This is done by analyzing the pose variations (e.g., variations in position, orientation, and scale) of the single object parts in the example images. The poses can be obtained by an arbitrary similarity measure for object recognition, e.g., normalized cross correlation, Hausdorff distance, generalized Hough transform, the modification of the generalized Hough transform, or the similarity measure. In the online phase the invention uses the hierarchical model to efficiently find the entire object in the search image. During the online phase only valid instances of the object are found, i.e., the object parts are not searched for in the entire image but only in a restricted portion of parameter space that is defined by the relations between the object parts within the hierarchical model, what facilitates an efficient search and makes a subsequent validation step unnecessary.

A Hough transform based method of estimating N parameters a=(a1, . . . , aN) of motion of a region Y in a first image to a following image, the first and following images represented, in a first spatial resolution, by intensities at pixels having coordinates in a coordinate system, the method including: determining the total support H(Y,a) as a sum of the values of an error function for the intensities at pixels in the region Y; determining the motion parameters a that give the total support a minimum value; the determining being made in steps of an iterative process moving along a series of parameter estimates a1, a2, . . . by calculating partial derivatives dHi=MH(Y,an) / Man,i of the total support for a parameter estimate an with respect to each of the parameters ai and evaluating the calculated partial derivatives for taking a new an+1; and wherein, in the evaluating of the partial derivatives, the partial derivatives dHi are first scaled by multiplying by scaling factors dependent on the spatial extension of the region to produce scaled partial derivatives dHNi.

The invention discloses a garment QD code recognition method. The method includes the following steps that firstly, a two-dimension code image attached to a garment raw material is collected; secondly, the image is subjected to graying, fast median filtering and binarization processing; thirdly, the image having been subjected to binarization processing is subjected to edge extraction; fourthly, two side edge regions obtained after edge extraction of a QR code are separated out; fifthly, Hough transform is adopted to detect a side-edge imaginary line so as to obtain the deviation angle of the QR code; sixthly, the image having been subjected to binarization processing is rotated according to the bilinear interpolation method, and initial correction is carried out; seventhly, the QR code is positioned, the sequence of three view finding images is determined, and the QR code is adjusted to have a correct orientation according to the image matrix transposition turning method; eighthly, decoding is carried out according to the national two-dimension code standard. According to the method, due to the combination of projection cutting and the Hough transform method, the deviation angle of the QR code can be quickly and accurately acquired, the collected image is immune from noise pollution and uneven illumination, and the two-dimension code image easy to identify can be obtained through transform.

The invention relates to a datum point positioning method based on machine vision, which belongs to the field of image processing and aims to solve the problems of poor datum point positioning accuracy and high cost of surface mounting equipment. The method comprises the following steps that a vision obtaining device is adjusted to obtain a datum point regional image; the image is preprocessed, and a threshold is set to establish a binary image; connected region labeling is performed on the binary image, so as to find out the largest connected region as a target region of a datum point; Canny edge detection is performed on an original image, so as to preliminarily determine coarse edge points; Hough transformation processing is performed on the coarse edge points, and an optimal existing circle in the image is found out; the distance between each edge point and the center of the circle is calculated; the position of a sub-pixel level of the edge point is obtained; and circular least-square fit is performed on the edge point in the position of the sub-pixel level, and then an accurate center and radius of the datum point are obtained and sent to a control system. The datum point positioning method can be widely applied to accurate positioning of the datum point.

A digital image includes a plurality of pixels arranged in an array. In a method of analyzing the image, some of the pixels are purposefully not processed. In particular, only those pixels in a particular subgroup are processed according to a Hough or similar transform. The number of pixels in the subgroup is less than the total number of pixels in the image (e.g., as little as about 5% of the total pixels), and each pixel in the subgroup is pseudo-randomly selected. The Hough transform is inherently configured to function within the context of noisy images, for identifying features of interest in the image, as simulated by the pseudo-random selection and processing of less than the total number of pixels in the image. This significantly reduces the processor resources required to analyze the image.

A detection method of double-threshold constant false alarm movement object on double-base synthetic aperture radar includes finalizing distance compression of various pulse-sampling, dividing orientation time to be multiple CPI, carrying out FFT in each CPI to enter orientation frequency domain, comparing data amplitude of frequency channel at external of clutter region with the first threshold and outputting point trace, making coagulation on point trace, making Hough transform in point trace domain and making decision of the second threshold.

The invention discloses a method for detecting lane change of a vehicle based on a vehicle-mounted camera. The method comprises the following steps: firstly, initializing a read-in image, and converting the read-in image to a gray space; secondly, segmenting an sky region and a ground region of the image, and acquiring the image of the ground region; thirdly, carrying out edge detection by utilizing the sobel operator; fourthly, carrying out binaryzation by utilizing an Otsu's method; fifthly, restricting a fitting range, wherein hough transformation is restricted by the minimum fitting points, and extracting a lane line equation; sixthly, determining the type of a lane line; seventhly, classifying lane line treatment results; and eighthly, determining the current lane change situation ofthe vehicle. According to the invention, the current lane change situation of the vehicle is detected by adopting the mode of images, the existing vehicle-mounted camera of a driving school is utilized, has low cost, high practicability, diversity detection data, and has accurate and objective evaluations of lane change level for students, the equipment is simple to install, and has wide applications.

The invention discloses a mura defect detection method based on sample learning and human visual characteristics, which belongs to the TFT-LCD display defect detection field. According to the invention, the method comprises the following steps: firstly, utilizing the Gaussian filter smoothing and Hough transform rectangle to preprocess the TFT-LCD display image, removing a large amount of noise and segmenting the image areas to be detected; then, using the PCA algorithm to conduct learning to a large amount of defect-free samples; automatically extracting the differential characteristics between the background and the target and re-constructing a background image; and then, thresholding the differential characteristics between a testing image and the background; through the reconstructing of the background and the threshold calculating, jointly creating a model. According to the invention, based on the training sample learning, a relationship model between the background structure information and the threshold value is established; and a self-adaptive segmentation algorithm based on human visual characteristics is proposed. The main purpose of the invention is to detect different mura defects in a TFT-LCD, to raise the qualification rate and to increase accuracy for the detection of mura defects.

The invention discloses a bend target identification system and method based on multi-sensor fusion, which mainly aims at a problem of front target detection of a vehicle at the bend of expressway. The lane line is divided into a straight line portion of the near view field and a curve portion of the far view field. For information acquisition of a camera, lane line fitting and tracking at the near view field are completed by using Hough transform and Kalman filtering, and curve fitting at the far view field is completed by using a BP neural network. For information acquisition of radar, information of a static object group is extracted, and curve fitting is performed by using the BP neural network. through space-time alignment, the lane line information acquired by vision and the lane line information acquired by the radar are fused to determine a travelable region of the lane where the vehicle is located, and finally a bend target identification algorithm based on the fusion of the camera and the millimeter wave radar is provided by combining the travelable region and the lane line type so as to realize detection for targets at the bend.

A method and system for performing automated biological identification. The system including a preprocessing module with a histogram transform for locally and globally enhancing biological data such as fingerprints. An enhancement module with a fast smoothing and enhancement function. A feature extraction module with a fingerprint oriented thinning function. A matching module with a resolution-enhanced Hough transform function for fingerprint registration and matching score function.

The invention discloses a fruit location identification method. The fruit location identification method includes that using a neural network color classification model to divide to obtain a fruit pixel region; using an edge detection algorithm to carry out edge detection on a fruit pixel region image without background to obtain the fruit boundary; carrying out Hough transform circle detection on the fruit edge image through a shape locating Hough transform technology in the image to obtain fruit circle and circle center position, and realizing to divide the overlapped region of the fruit; based on image depth information, camera pose information and world position information, using a world coordinate transformation algorithm to extract the world coordinates of the circle center of each fruit to realize the quick detecting, precise locating and precise counting for the fruit.

The invention discloses a method for measuring and pre-warning a lane departure distance based on monocular vision, belonging to the technical field of computer imaging processing. The method comprises the following steps of: collecting a video image through a monocular video camera installed in the front of an automobile at first, completing the detection of a lane line after processing through an image processing technology, and extracting geometrical information of the lane line; obtaining vertical distances between the automobile and the lane lines at left and right sides by utilizing thethree-dimensional geometry transformation relation of a pinhole imaging principle; and establishing a departure pre-warning decision method according to the vertical distances measured in real time, and providing effective information for an intelligent assistant driving technology. According to the method disclosed by the invention, when the lane line is detected by utilizing Hough transform, a constraint condition is added, a part of virtual lane line is excluded, and the operation speed and the lane line detection accuracy are increased; simultaneously, the lane departure pre-warning can be realized only by utilizing image information; the measurement influence of a vehicle departure angle on the lane departure distance is low; furthermore, the solving operation speed is high owing to the use of the three-dimensional geometry transform method; and the requirements of the intelligent assistant driving technology can be satisfied.

A device for identifying a traffic sign in an image includes a Hough transformer implemented to identify a plurality of line sections running in different directions through the image in the image or in an edge image derived from same. The device further includes a shape detector implemented to detect a predefined shape in the image or in the edge image derived from same based on the identified line sections. The device apart from that includes a pattern identifier implemented to select an image section corresponding to the detected predefined shape based on the detected predefined shape and to identify a traffic sign based on the selected image section.

The invention discloses a Hough transform-based lane line detection method. In view of defects that the existing lane line detection technology needs to build a specific model, the algorithm is complicated, the efficiency and the real-time performance is poor, as for an image containing the lane line after Hough transform, the position information of a lane line pixel is used for lane line detection and tendency judgment, the algorithm has good real-time performance, and a detected lane line can be obtained efficiently. The method does not need to introduce many parameters to help to tell a curve, a tedious method of lane line modeling and the like is not needed, the method can be applied to a common lane and an expressway, recognition on the curve tendency is realized simply and quickly, and the real-time performance and the accuracy are good.

The invention provides a real-time lane line detection method. According to the real-time lane line detection method, an interested area is determined through the position of a current frame vanishing point, and an upper half image where no lane lines exist is removed, and therefore, the processing time of each frame of image can be decreased; edge point scanning is performed at two directions from inside to outside of the interested area, and what is detected every time is the inner side of a lane line which is most adjacent to vehicles on a lane, and except for the interference of other edge points, jigger will not be generated because of the width of the lane line, and since an image is divided into two half parts of detection lane lines from the position of the vanishing point, a situation that two detected straight lines are located at one side of the vanishing point when the entire image is detected can be avoided, and thus, the accuracy of the detection can be improved; and further, when Hough transform lane line detection is performed, only straight lines in a range of straight lines which can form a certain included angle with a horizontal line are selected, and therefore, the accuracy of the detection can be improved, and time for calculating Hough weight of straight lines that are not in the range of the straight lines can be saved. With the real-time lane line detection method of the invention adopted, lane line detection at highways and rural areas where roads are in good condition can be realized rapidly, accurately and stably.

Computer software for and a method of determining location of a target image within a two-dimensional input image by employing a three-dimensional reference image comprising determining object edge points in the input image; given estimated seeker line-of-sight orientation and range data, computing a two-dimensional reference image from the three-dimensional reference image; applying a weighted-direction-cross-product Hough Transform to the object edge points and points of the two-dimensional reference image; classifying the input image as containing a target image or not; if the image contains a target image, identifying a location of the target image within the two-dimensional input image; computing confidence measure as to the selected location of the target image; and in the case of sequential decision, also performing confidence accumulation through multi-frames or multi-looks.

Accurate pelvic fracture detection is accomplished with automated X-ray and Computed Tomography (CT) images for diagnosis and recommended therapy. The system combines computational methods to process images from two different modalities, using Active Shape Model (ASM), spline interpolation, active contours, and wavelet transform. By processing both X-ray and CT images, features which may be visible under one modality and not under the other are extracted and validates and confirms information visible in both. The X-ray component uses hierarchical approach based on directed Hough Transform to detect pelvic structures, removing the need for manual initialization. The X-ray component uses cubic spline interpolation to regulate ASM deformation during X-ray image segmentation. Key regions of the pelvis are first segmented and identified, allowing detection methods to be specialized to each structure using anatomical knowledge. The CT processing component is able to distinguish bone from other non-bone objects with similar visual characteristics, such a blood and contrast fluid, permitting detection and quantification of soft tissue hemorrhage. The CT processing component draws attention to slices where irregularities are detected, reducing the time to fully examine a pelvic CT scan. The quantitative measurement of bone displacement and hemorrhage area are used as input for a trauma decision-support system, along with physiological signals, injury details and demographic information.

A digital image includes a plurality of pixels arranged in an array. In a method of analyzing the image, some of the pixels are purposefully not processed. In particular, only those pixels in a particular subgroup are processed according to a Hough or similar transform. The number of pixels in the subgroup is less than the total number of pixels in the image (e.g., as little as about 5% of the total pixels), and each pixel in the subgroup is pseudo-randomly selected. The Hough transform is inherently configured to function within the context of noisy images, for identifying features of interest in the image, as simulated by the pseudo-random selection and processing of less than the total number of pixels in the image. This significantly reduces the processor resources required to analyze the image.

Provided is a lane line detection method, comprising the following steps: collecting a lane line image including a left lane line and a right lane line of a lane where a vehicle is located; extracting lane edge target points from the lane line image; conducting perspective transformation on the lane edge target points; and by means of the Hough transformation, detecting a straight line formed by the lane edge target points as a lane line. According to the lane line detection method of the present invention, before the Hough transformation is conducted, the perspective transformation is conducted on the extracted lane edge target points, so that the Hough transformation calculation amount can be reduced, the system reaction time can be reduced, and the travel security of vehicles can be enhanced. In addition, also provided are a lane line detection system, and a method and system for lane deviation prewarning.

A geographic database represents roads including an altitudinal component of the geometry of the roads. The altitudinal component of the geometry of roads is represented using data that indicate straight line segments and vertical curves, in particular parabolic vertical curves. The straight lines and vertical curves are determined by providing data, indicating the altitude at a plurality of locations along portions of roads, as an input to a Hough transform to determine the straight line segments and vertical curves that coincide with the portions of the roads vertically. Then, data that define the straight line segments and vertical curves are stored to represent the altitudinal component of the geometry of the portions of the roads in the geographic database. The altitudinal variation of roads is thus expressed in closed form. From this closed form representation, the slope or grade at any point along the road can be easily computed.