80 results about "Log-polar coordinates" patented technology

A method and system for uniquely identifying a subject based on an iris image. After obtaining the iris image, the method produces a filtered iris image by applying filters to the iris image to enhance discriminative features of the iris image. The method analyzes an intensity value for pixels in the filtered iris image to produce an iris code that uniquely identifies the subject. The method also creates a segmented iris image by detecting an inner and outer boundary for an iris region in the iris image, and remapping pixels in the iris region, represented in a Cartesian coordinate system, to pixels in the segmented iris image, represented in a log-polar coordinate system, by employing a logarithm representation process. The method also creates a one-dimensional iris string from the iris image by unfolding the iris region by employing a spiral sampling method to obtain sample pixels in the iris region, wherein the sample pixels are the one-dimensional iris string.

The invention provides a method for detecting an R wave crest of an electrocardiosignal. The method takes point to point difference vector as a base characteristic. The base characteristic has translational and rotational invariance and can overcome influences of baseline drift of the electrocardiosignal. Meanwhile, logarithm polar coordinate conversion is carried out on the difference vector to measure similarity of waveforms. The measurement is sensitive to morphological characteristics of the adjacent waveforms, can capture the whole contour information of the waveforms at the same time, and has robustness on waveform swing. In addition, the method can effectively eliminate influences of interference signals by setting appropriate thresholds. The method for converting the point to point similarity measurement into measurement of waveforms of the points accurately identifies and detects the R wave crest of the electrocardiosignal. The method is applied to related electrocardiogram analytical instruments, can accurately identify the R wave crest in the electrocardiosignal, and is favorable for improving detection and analysis capabilities of electrocardiogram analytical equipment.

The invention discloses a multi-bit digital watermark method against the print scanning and the geometric transformation, which comprises the following steps: embedding the watermark in dispersion Fourier amplitude coefficient of the image; determining which Fourier amplitude coefficient every watermark bit embeds in according to the dispersion logarithmic polar coordinate of the Fourier amplitude coefficient; making the watermark detecting and extracting out-of-step when the image is carried out the geometric transformation of the pantographic rotating or the print scanning; synchronizing the information watermark according to the relation of the original mode and embedded mold when the watermark is detected and extracted because the pantograph and the rotating of the image corresponds with the translation of the Fourier logarithmic polar coordinate field at the radial and angel direction; extracting the meaning watermark information bit string; introducing the real interpolation and saving the time because the watermark embedding and detecting process doesn' t need the image interpolation arithmetic for the image and the Fourier amplitude coefficient; protecting the embedded mode. The invention can apply to the copyright protection of the digital image and video, false proof of the file and evidence, the monitoring of video broadcast.

The invention provides an electrocardiosignal R peak detection method based on waveform characteristic matching. The method utilizes waveform characteristic matching to identify R peak of electrocardiosignal, the characteristic matching method takes difference vector between points as basic characteristic, the basic characteristic has translational invariance and rotational invariance and can overcome influence of baseline drift of electrocardiosignal signal; meanwhile, logarithm polar coordinate transformation is carried out on the difference vector and partition is carried out to measure similarity of wave form, the measurement is sensitive to the adjacent morphological characteristic, can capture global outline information of wave form and has robustness to wave form ripple; besides, influence of interference signal can be eliminated by setting proper threshold, and further accurate identification and detection on R peak of electrocardiosignal are realized. The invention is applied to related electrocardiogram analyser, accurate identification on R peak of electrocardiosignal can be realized, thus being beneficial to improving detection and analysis capability of electrocardiogram analysis equipment.

The invention discloses a quick image rectification method in the presence of translation and rotation at the same time. Another image which searches for reference image relationship is called an image to be rectified; a circular template matching method is adopted to determine translation amount; after the radius of the circular template is determined, the central structure of a reference image serves as a reference template; within a certain search range of the image to be rectified, a block of graph in optimum matching with the reference template is searched, and the difference value of the circle center coordinates of the reference template and the block of graph is the translation amount of the image to be rectified relative to the reference image; on the other aspect, the circular reference template and the matching block respectively are subject to logarithm pole coordinate transformation; the corresponding reference template and a matching subblock of the image to be rectified are subject to gray-scale projection to determine the rotation angle of the image to be rectified relative to the reference image; and the image rotates according to the angle to finish the quick rectification of images. The invention realizes the quick image rectification in the presence of translation and rotation at the same time.

A data input system for a touch sensor input identifies words input as a set of points by a user. The intended word is identified by determining an origin and points associated with letters on a log polar coordinate system. The log distances and angles of the points are then compared to log distances and angles for known words stored in a computer memory. The known word having the log distances and angles that most closely match the input points is identified as the intended word.

The invention relates to a kind of method to matching the shape of persons' faces based on Shape Context. At first, preprocessing with the image pyramid and diffusion-filtering technology; then abstracting the boundary-outline information; carrying on the logarithmic coordinate transformation of the abstracted boundary-outline information to get bar chart of the logarithmic coordinate; calculating the value of Cs to get all the phase match points; calculating the value of the degree of approximation to judge the shape matching. The invention is characterized in simplicity, accuracy, being economical, expandability and so on, so the person-face shape matching can be used for entrance-exit control, safe verification, safe-guard monitoring, searching criminals and so on.

The invention relates to an automatic registering and fused splicing method of multiple images. The unordered images are enhanced in a multi-dimension Retinex method; the images match each other by utilizing a logarithm polar coordinate transformation improved phase correlation algorithm, zooming, rotation and translation parameters are calculated, an overlapped area among the images is estimated roughly, and an ordering rule is formulated according to energy peak values of an impulse function; an SUFR algorithm is used to extract characteristic points from the overlapped area to be registered, a random sampling consistent algorithm is improved to purify matching point pairs accurately, model parameters are optimized, a transformation matrix among the images is established, and sequential images are spliced successively; and an NSCT algorithm is utilized, a fusion strategy is made to further fuse spliced images, and a spliced image after fusion is output. The method of the invention can be used to reduce influence of difficult manual ordering, fuzzy image details, low resolution, high noise, nonuniform illumination and the like on image registration and splicing, provides help for reducing cost of imaging equipment and accurate diagnosis of medical staff, and has good application prospects in the medical image assisted field.

The invention discloses a target tracking method of a passive multi-sensor based on layered particle filtering. A sub-state including an azimuth angle, a change ratio of the azimuth angle, a change ratio of a logarithm radial distance and auxiliary parameters and a sub-state Psi including the logarithm radial distance are constructed to realize a structure of hierarchical filtering through rewriting a system equation of a logarithm polar coordinate and adding the auxiliary parameters indicative of process noise intensity and radial distance ratio, wherein a first layer updates the auxiliary parameters in a second layer by means of sequential importance sampling method according to observation information of various sensors; Psi is iterated and updated; and the auxiliary parameters are combined to obtain estimation of the target state; finally a fusion output result of the target state is obtained according to an optimal information fusion method. Values of the auxiliary parameters can be estimated in real time by using a method of the layered particle filtering, and errors introduced by a maximum value of the noise intensity in the use process of the filtering is avoided, such that the problem of the target tracking can be effectively solved under the conditions of unknown process noise intensity and unmeasured distance.

The invention relates to a sonar image splicing method. The method comprises the steps of removing noise in order to increase the contrast ratio through image preprocessing; transforming a scaling parameter and a rotation parameter into translation parameters through carrying out log-polar transformation to an image amplitude frequency spectrum, and carrying out algorithm analysis based on phase correlation; filtering scale and rotation factors through image geometric transformation; working out the translation parameters through an algorithm based on the phase correlation; and carry out coordinate mapping through the scaling parameter, the rotation parameter and the translation parameters which are worked out, and carrying out image interpolation through a bilinear interpolation algorithm. The registration of all sonar images is achieved by continuously repeating the above steps, then the splicing of the sonar images is achieved through brightness adjustment and image superposed area fusion. According to the invention, the problem that the detection scope visual angle of sonar is narrow in an underwater monitoring process is solved, through sonar image splicing, a series of sonar images are spliced to a large-scale sonar image, and therefore the sonar can simultaneously monitor a large-scale underwater environment.

The invention discloses a shape matching and target recognition method based on a PCA-SC algorithm. The method comprises the steps of carrying out preprocessing on a target image, filtering part of noises in the target image, extracting the edge of the target image, extracting information of boundary contour points, working out the rectangular coordinate parameters of the contour points, converting the contour points from rectangular coordinates into polar coordinates, obtaining a corresponding logarithmic polar histogram of each point to forming a local feature descriptor, forming a covariance matrix, extracting a corresponding feature vector of a larger characteristic value of the matrix, adopting a linear transformation method to drop the matrix from high dimension to low dimension, forming a new characteristic matrix, wherein the new characteristic matrix is used for the shape matching and the target recognition, calculating matching degree, and obtaining a matching degree value between the target image and each template image. According to the shape matching and target recognition method based on the PCA-SC algorithm, characteristic extracting and effective representation for the image can be achieved, scale invariance, rotation invariance and translation invariance are achieved, accuracy rate and efficiency are improved, and interference of the noise is effectively restrained.

As a feature, a local range image described in a log-polar coordinate system with a tangential plane set as an image plane is used. In a created image, ambiguity concerning an angular axis around the normal is normalized as a power spectrum using Fourier series expansion and changed to an amount invariable with respect to rotation. The power spectrum is dimensionally compressed by expanding the power spectrum in a peculiar space using a peculiar vector. Corresponding points are searched by nearest neighbor in a dimensionally compressed space to calculate a correspondence relation among the points. Wrong correspondence is removed by verification to determine a positional relation among range images. A reliable correspondence relation is narrowed down by verification by cross-correlation and a RANSAC to create a tree structure representing a link relation among the range images. A shape mode is created by applying a simultaneous registration method to plural range images of the tree structure using a result of this registration as an initial value.

The invention discloses an adaptive cross-camera multi-target tracking method and system and relates to a cross-camera multi-target tracking technology in the field of computer vision. The method comprises the following steps: firstly, fixing the size of a tracking window, obtaining a position of a current video frame target object by use of a pre-established tracking model, the size of the tracking window is converted at the obtained position, the scale of the target object is obtained by use of the tracking model, and according to the obtained scale of the target object, updating the tracking model in an online mode; and according to the updated tracking model, performing log-polar transformation on an image of the current video frame target object, performing hybrid Gauss modeling on the image of the target object after the log-polar transformation, measuring a center deviation and change degree of the target object, and determining whether the target object already disappears. The invention also discloses an adaptive cross-camera multi-target tracking system. According to the technical scheme, the accuracy and the robustness of a tracking algorithm can be effectively improved.

Provided is a method for digital image representation based upon Discrete Projective Fourier Transform (DPFT) constructed in the noncompact (DNPFT) and compact (DCPFT) realizations of geometric Fourier analysis on SL(2,C) groups. Novel characteristics are that the model is well adapted to perspective image transformations and well adapted to the retinotopic (conformal) mapping of the biological visual system. To compute the DPFT of a digital image by Fast Fourier transform (FFT), an image is re-sampled with a non-uniform log-polar sampling geometry. A “deconformalization” procedure corrects the “conformal lens optics” of the conformal camera to render image perspective transformations. DNPFT computes the convolution in the noncompact realization defined over 2-dimensional rotations in the image plane and dilations while the DCPFT computes the convolution in the compact realization (which is defines over all 3-dimensional rotations) and therefore provides basis for developing projectively invariant under all rotations object matching.

The invention provides a method for identifying a dicrotic notch point in an arterial tension signal, which is used for carrying out comprehensive analysis by combining with a waveform outline of the arterial tension signal, can overcome the influence of baseline drift of the arterial tension signal by using a differential vector between points as basic characteristics with translation and rotational invariance and adopting a log polar transformation distribution model, and is sensitive to adjacent waveform morphological characteristics, and can be used for capturing overall outline information of waveform, thus the antijamming capability of the identification of the dicrotic notch point is integrally improved; meanwhile, in an identifying process, the data calculated amount in the identifying process is greatly simplified through curvature differential identification, the integral robustness and the identification accuracy of the method provided by the invnetion are improved by adopting a chisquare statistic check as a matching means and the advantages of strong robustness and high accuracy of the chisquare statistic check. The method provided by the invention realizes that the dicrotic notch point in the arterial tension signal is identified by a computer, and has a wide application prospect.

The invention discloses a place cell bionic robot navigation algorithm which comprises the steps of: A1, firstly, capturing a panoramic photo by a robot wide angle camera, converting the panoramic photo into a gradient image, then filtering the gradient image by using a Gaussian difference filter, detecting characteristic points, carrying out log polar transformation on a local region near the characteristic points, wherein the characteristic points correspond to special road signs; A2, obtaining angle of each road sign relative to the true north direction as an azimuth angle, wherein the true north direction is provided by a compass and the azimuth angles and the road signs jointly determine a position cell of the current time; A3, jointly determining a transfer matrix by the position cell of the current time and a position cell of the former time, when a robot explores in an unknown environment, continuously forming transfer matrixes, forming a cognitive map by the transfer matrixes; and A4, jointly determining a movement transformation matrix by the transfer matrixes and the cognitive map, wherein the movement transformation matrix is in charge of sending a movement command. The invention can be applied to an intelligent ground-cleaning robot, a battlefield searching and rescuing robot, and the like.

The invention discloses a super-resolution image acquisition method and system based on a human eye retina mechanism and belongs to the field of photoelectric imaging technology. Through the method, according to the characteristics that low-resolution log-polar coordinate images with horizontal sub-pixel displacement and vertical sub-pixel displacement can be obtained according to human eye retinarotation and scale invariance, low-resolution images needed for super-resolution reconstruction are acquired through combined transformation of the horizontal sub-pixel displacement and the verticalsub-pixel displacement, image registration parameters are simplified, and the complexity of super-resolution reconstruction is lowered; and meanwhile, since a non-uniform sampling structure of a humaneye retina space has the characteristics that the middle has a high resolution in imaging and the edge has a low resolution in imaging, the data volume involved in super-resolution reconstruction isreduced, the efficiency of super-resolution reconstruction is improved, and target recognition and tracking speed after super-resolution reconstruction is further increased. The invention furthermorediscloses the super-resolution image acquisition system based on the human eye retina mechanism, and the system is used for implementing the method.

The invention discloses an eye fundus image splicing method and system, and the method comprises the steps: reading a plurality of collected eye fundus images, and selecting one eye fundus image fromthe plurality of eye fundus images as an optimal reference image for image registration; Carrying out blood vessel image extraction on the optimal reference image by adopting a blood vessel extractionalgorithm based on a Segnet image segmentation model, obtaining a corresponding optimal reference blood vessel image, carrying out blood vessel image extraction on each of the rest eye fundus images,and obtaining a corresponding eye fundus blood vessel image as a to-be-registered image; Based on the logarithmic polar coordinates, performing image registration on each to-be-registered image and the optimal reference blood vessel image to obtain a corresponding registered image; And for the plurality of registered image images, carrying out weighted fusion on the plurality of registered imageimages by adopting a pixel value weighted fusion method based on a distance matrix to obtain a final fundus image splicing image. The quality of the stitched image is effectively improved, and the problem that a traditional fundus image stitching method has a certain limitation is solved.

The invention relates to the field of image matching technology, in particular to an image matching method and system. The image matching method comprises the steps that a, a template image and a to-be-matched image are read, and sparse Fourier transformation is performed on the template image and the to-be-matched image; b, an amplitude spectrum of the template image and an amplitude spectrum ofthe to-be-matched image after sparse Fourier transformation are calculated respectively; c, log-polar transformation is performed on the template image and the to-be-matched image according to the amplitude spectra; and d, phase correlation is performed on the log-polar transformation result of the template image and the to-be-matched image, a rotational angle, a scaling coefficient and a translation quantity are obtained, and matching is performed on the template image and the to-be-matched image according to the obtained rotational angle, scaling coefficient and translation quantity. Throughthe image matching method and system, a high-pass filtering step in traditional Fourier-Mellin transformation is omitted, an error brought by high-pass filtering in a traditional image matching algorithm is avoided, phase correlation done in a later period is more precise, and algorithm intelligence is obviously improved.

The invention relates to a vein matching method based on logarithm polar coordinate transformation. According to the method, an image is pre-processed to obtain a vein line picture and a single pixel line picture, matching alternate regions of a template image and a sample image are designated according to finger vein line picture structure characteristics, then similarity measure of an LPT transformation result of the matching alternate regions of the template image and the sample image is calculated, and ultimately a matching result is judged according to the similarity measure and relative position distribution between the regions.

The invention relates to a wide view field logarithm pole coordinating mapping imaging method based on a curve surface lens array and belongs to the technical field of photoelectric imaging sensors. The wide view field logarithm pole coordinating mapping imaging method based on the curve surface lens array is sequentially composed of a fronting optical system, a curve surface non-uniform lens array and a photoelectric detection array from top to sown. According to the wide view field logarithm pole coordinating mapping imaging method based on the curve surface lens array, the curve surface optical lens array is used, so that the view field of an imaging system is enlarged, large view field imaging can be achieved, and the sensitivity of a logarithm pole coordinating mapping sensor is improved.

A method (200) of determining at least rotation and scale parameters of a transformation relating two images is disclosed. The method (200) starts by forming a spatial domain representation of each of the images that is invariant to translation of the images. A correlation in the log-polar domain is next performed between the representations. After detecting a magnitude peak in the correlation, the method (200) determines the rotation and scale parameters from the position of the magnitude peak.

The invention discloses a log-polar space based image object size and rotation estimation calculation method. A to-be-detected image and a template image are input and log-polar transformation is performed on the to-be-detected image. Characteristic extraction is performed on the object image subjected to transformation and a characteristic image is acquired. A response diagram of the image object relative to the size and rotation change of the template image is obtained through calculation by adopting a phase correlation method by utilizing extracted characteristics. Relative displacement is calculated through a response value in the perimeter zone of the maximal value in the response diagram and the coordinate position of the maximal value. The size and the rotation change of an object in the to-be-detected image relative to an object in the template image are calculated through the relative displacement. According to the invention, the log-polar space is innovatively adopted as an image operation space, so that the size and rotation change of the object are estimated effectively and quickly, so that quick algorithm support is provided for upper layer application.

An image matching system, method, and program for matching two images even if there is a difference of parallel movement, rotation angle, and scale between two images. A Fourier-Mellin transform is a Fourier transform and a log-polar coordinate transform to a registered image and a matching image. A phase only correlation unit and scalar information-rotation information generation unit generate correction information including scalar information and rotation information based on correlation strength of the phase information based on the transform result, a correction unit corrects the matching image RIM in accordance with the correction information, a parallel movement unit performs phase only correlation based on the image resulting from the correction processing and the registered image, a correlation value generation unit generates a correlation value based on the correlation image data, and a judgment unit performs judgment concerning the matching based on the correlation value.

The invention relates to an edge significance-based EFMT multi-sensor image registration method and system. The method comprises the following steps that a, an edge extraction module is used for extracting a reference image and an edge image of a to-be-registered image; b, a calculation module is used for converting the edge image to a log-polar coordinate domain, and calculating phase correlation of the log-polar coordinate domain image to obtain a rotation angle and a scale factor of the image; c, an image conversion module is used for converting the to-be-registered image according to the rotation angle and the scale factor, and the edge extraction module is used for extracting the edge image of the converted image; and d, the calculation module is used for calculating the edge image conversion in the step c, the phase correlation and the rotation angle of the edge image of the reference image in the step a to obtain an image transition parameter. According to the scheme, based on a traditional registration algorithm, the FMT conversion is carried out by utilizing the edge image of images, and the accuracy and speed of multi-sensor image registration are improved.

The invention discloses a method for improving the calculating speed of horizontal collection. Firstly the even sampling images to be treated are selected to be mapped in the logarithmic polar coordinates to obtain the heterogeneous sampling images, then the heterogeneous sampling images are carried out the evolvement calculation of horizontal collection, characterized in that the logarithmic polar coordinates model log( Rho / Rho0) is selected, the minimum sampling radius Rho0 can be determined according to the formula Rho0=N / 2Pi, the areas less than Rho0 is no longer carried out the logarithmic mapping (in which, N is the number of sampling); after the conversion of the logarithmic polar coordinates is completed for the image to be treated according to the reverse algorithm formula, the overall iterative computation of horizontal collection is carried out based on the formula of horizontal collection, the reverse conversion of the logarithmic polar coordinates is finally carried out for the images to be treated using the reverse algorithm to obtain the treating result. Since the images to be treated are mapped in the logarithmic polar coordinates to be carried out the iterative computation of horizontal collection, the size of original image is converted from 256*256 to 84*160 using the heterogeneous sampling of the logarithmic polar coordinates, then the size of image is 1 / 5 of original image, accodingly the calculating speed of the existing horizontal collection can be improved.