1118 results about "Median filter" patented technology

One or more median filter circuits are used to filter radio link control measurements corresponding to one or more radio link parameters of interest, such as received signal quality or round trip delay measurements, such as might be used by a base station to trigger mobile station handoff. As such measurements are particularly susceptible to measurement outliers arising from rapid but short-lived changes in radio link propagation paths, for example, the application of median filtering to such measurements is particularly advantageous. That is, by operation of median filtering, which is a non-linear filtering process, outliers in a stream of control measurements, such as are caused by instantaneous changes in channel fading or other propagation phenomena, are discarded rather than averaged in with the other measurements. Non-linear filtering as implemented by exemplary median filtering does not impair or otherwise limit the bandwidth of the underlying control measurements.

In a method for suppressing interferences while detecting objects in a target area, a transmitter transmits a sequence of pulses into the target area, and a receiver detects the resulting reflection signal of the pulses reflected from the objects, within successive time windows that are referenced to the moment of transmitting an individual pulse and thus represent distance gates. The time spacing between the successive individual pulses is variable and randomized according to the pseudo-noise principle within predetermined limits, and the time windows are adapted accordingly. The received reflection signal may be sampled, digitized, digitally pre-processed and digitally filtered in the individual distance gates. A non-linear digital filter, preferably a sliding median filter, is used for the filtering to suppress transient disturbances. The median is determined from an odd number of consecutive sampled values of a reflection signal detected within a distance gate.

Methods and systems for hierarchically layered adaptive median motion vector smoothing are disclosed. Aspects of one method may include generating motion vectors (MVs) for video pictures at each level of a hierarchical motion estimation process, where each level may use different resolution video pictures. The MVs may be smooth filtered at each level to reduce or remove spurious MVs. The smooth filtering may comprise scalar median filtering and/or vector median filtering. The smooth filtering may receive as inputs a plurality of MVs, for example, the MV being filtered and eight MVs from the surrounding video blocks. The vector costs of the nine MVs may be compared to a threshold vector cost, and those MVs with costs above the threshold value may be discarded. The threshold value may be dynamically changed based on, for example, content of the video pictures and/or to adjust a window size of the smoothing filter.

The invention disclose a bar code image identification method, belonging to the field of computer information automatic identification technology, the method comprises the following steps: S1. carrying out gradation to a colored image which is captured by an Android mobile phone camera, wherein the colored image is a bar code image; S2. conducting median filtering processing to a grayed image; S3. conducting binaryzation processing to the image which carries out the median filtering processing; S4. conducting bar code positioning to the image which carried out the binaryzation processing; S5. conducting geometric distortion correction to the positioned image; and S6. decoding the corrected image, so as to obtain a code word of the image. In the invention, the precision of the bar code identification is improved and the complexity is reduced.

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 discloses a method and device for acquiring a Kinect depth image. The method comprises the steps of sampling static scenes continuously by means of the Kinect to obtain a plurality of frames of depth images and colored images; carrying out median filtering and noise reduction on the depth images; carrying out edge detection on the first frame of colored image and the depth images treated with median filtering by means of the Canny operator; carrying out primary segmentation on the depth images by means of a user index value of Kinect depth data to obtain a mark sheet, wherein pixels with the same mark value belong to one region in the mark sheet; carrying out primary repairing on the depth images by means of a region growing method with edge limitation considered and updating the mark sheet according to edge information of the depth images and the colored images and a depth image segmentation result; carrying out image enhancement on the depth images by means of trilateral filtering according to the updated mark sheet. According to the method and device for acquiring the Kinect depth image, edge inconformity of the depth images and the colored images is effectively overcome, cavities in an original Kinect depth image are repaired, noise is eliminated at the same time, and the depth image which is good in quality can be obtained finally.

The invention belongs to the technical field of two-dimensional code identification, and provides a rapid positioning and identifying method based on two-dimensional code decoding. The method comprises the following steps: performing median filter processing on an entire image; scanning the image, judging whether or not a two-dimensional code exists in the image, and if so, acquiring a two-dimensional code regional coordinate; intercepting a two-dimensional code image; performing adaptive binarization processing; performing connected area disposal on black pixel points; screening four boundaries; converting the coordinate system of the image into the coordinate system of the two-dimensional code; projecting the two-dimensional code under a new coordinate system to obtain the directivity, real boundary length and coordinate of the two-dimensional code and the barycentric coordinates of black-white blocks; judging the gray values of the black-white blocks to obtain a two-dimensional code information matrix; and acquiring decoding information. The method can adapt to various working conditions, and has the advantages of high contrast, high interference resistance and low investment cost. Automatic positioning and identifying functions can be finished by only one set of industrial camera and light source; high working efficiency is achieved; and the production requirement of an assembly line is met to the maximum extent.

The invention discloses an improved image edge detection method. The improved image edge detection method comprise steps of S1, performing smoothing processing on an image and using an improved media filter to suppress noise, S2, obtaining a difference between a horizontal direction and a perpendicular direction through first-order-partial derivatives of directions of x,y,45 degrees and 135 degrees and thus obtaining a gradient amplitude and a gradient direction, S3, performing non-maximum value inhibition on the gradient amplitude, S4, using a gradient histogram to solve a high threshold and a low threshold and then using a double-threshold algorithm to perform edge detection on the image, and S5, performing sharpening processing and connecting the edges to obtain a final edge image. The improved image edge detection method use weighted media filtering to replace gauss filtering, uses the partial derivatives of four directions, uses the gradient histogram to determine the high threshold and the low threshold, reduces detection errors, improves detection accuracy, and makes the counter of the edge image more clear and continuity better.

The invention relates to a method for detecting surface defects of a dustproof cover of a bearing based on machine vision, which comprises the following steps: a, obtaining a gray level image of a to-be-detected bearing; b, carrying out separation on the gray level image so as to obtain a ring image of the dustproof cover of the bearing; c, carrying out grey level transformation and adaptive median filtering preprocessing on the ring image; d, carrying out threshold segmentation on the ring image by using a maximum interclass variance method, extracting an edge of the ring image of the dustproof cover of the bearing after threshold segmentation by using a Roberts edge detection operator; e, calculating the numbers of which the numerical values are 1 in the image area every two degrees for the ring image of the dustproof cover of the bearing; f, providing a template bearing image, and obtaining a deflection angle sigma through calculating; g, carrying out separation on the image so as to obtain character areas and non-character areas of the ring image of the dustproof cover of the bearing; and h, carrying out surface defect judgment on corresponding character areas and non-character areas in the ring image of the dustproof cover of the bearing according to the number of connected areas and the defect area. By using the method disclosed by the invention, automatic detection can be achieved, the visual detection workload of artificial detection is reduced, the detection efficiency is improved, and the method is safe and reliable.

A content-dependent scan rate converter with adaptive noise reduction that provides a highly integrated, implementation efficient de-interlacer. By identifying and using redundant information from the image (motion values and edge directions), this scan rate converter is able to perform the tasks of film-mode detection, motion-adaptive scan rate conversion, and content-dependent video noise reduction. Adaptive video noise reduction is incorporated in the process where temporal noise reduction is performed on the still parts of the image, thus preserving high detail spatial information, and data-adaptive spatial noise reduction is performed on the moving parts of the image. A low-pass filter is used in flat fields to smooth out Gaussian noise and a direction-dependent median filter is used in the presence of impulsive noise or an edge. Therefore, the selected spatial filter is optimized for the particular pixel that is being processed to maintain crisp edges.

The invention discloses a full convolutional neural network-based large-range remote sensing image semantic segmentation method. The method comprises three stages of data tagging, model training and result prediction; the method performs preprocessing operations of waveband synthesis, image fusion and image segmentation on remote sensing images for characteristics of high precision, large range, multispectral information and the like of the remote sensing images; the richness of samples is improved by applying a data enhancement technique to a training set; and if a data set with a label can be obtained, the data set can be used for training a model firstly, and target data model training is initialized to reduce the workload of manual labeling. For improving the accuracy of a result, themethod performs overlapping grid division on the images, performs prediction, splices prediction result images in sequence, and performs median filtering to reduce noises and unsmooth parts in the images; and finally, relatively high accuracy is achieved.

The invention discloses a quick motion estimation method of multi-view video coding, comprising the following steps of: carrying out spatial median filtering on a motion vector field of coded frames of adjacent views; calculating an overall parallax vector between the current view and the adjacent view by using a parallax vector field of the coded frame of the current view; selecting a reference motion vector from the filtered motion vector field by using the overall parallax vector; selecting a searching center of motion estimation by using the reference motion vector and the spatial motion vector of adjacent estimated blocks; selecting the searching range of the motion estimation by using the deviation degree of the searching center and the reference motion vector; and carrying out the final motion searching in the searching range, selecting the final motion vector of the current block, and finishing the selection of the final motion vectors of all blocks by using the same method and finishing the motion estimation of the multi-view video coding. The method is suitable for the motion estimation of the multi-view video encoding and can effectively reduce the calculation amount of the motion estimation and synchronously maintain the coding rate distortion performance.

The invention discloses a saliency-based synthetic aperture radar (SAR) image airfield runway edge detection method, which comprises the following implementation steps: (1) reading in image data; (2) carrying out median filtering on the image data which is read in; (3) carrying out enhanced processing on a filtered and de-noised image; (4) obtaining a salient map of the processed image; (5) rejecting a noisy background area on the basis of the saliency information of the salient map; (6) obtaining a seed growth point to carry out region growing; (7) carrying out aftertreatment; and (8) carrying out edge positioning. According to the saliency-based SAR image airfield runway edge detection method, the airfield runway edge can be quickly detected, the airfield runway edge information can be favorably kept, meanwhile, the interference of the noisy background area is avoided, and the saliency-based SAR image airfield runway edge detection method has better instantaneity and higher detection precision and can be applied to the SAR image airfield runway edge detection.

The disclosed picture removing-noise method based on multi-template mixed filter comprises: dividing the objective picture into MXN blocks without superposition to contain every pixel in some block; defining one group of filters including the mean filter and mid-value filter, every with different removing-noise strength; defining a numerical sequence with number standing for picture information size; obtaining the noise variance of the picture, calculating the uniformity level for the picture block to thereby select one filter for finishing the removing-noise. This invention simplifies calculation, and reduces real running time.

The invention relates to a method for extracting the regions of interest (ROIs) of a pedestrian by using an image segmentation method on the basis of road restriction and belongs to the field of vehicular pedestrian detection ROIs extraction. The method comprises steps of: reading an image I to be detected; determining whether the image I is a grayscale image; performing median filtering on the image I<gray> in order to obtain an image I<med>; performing grayscale enhancement on the image I<med> by using histogram equalization; training an optimal grayscale image segmentation threshold value of a common driving image by using a fuzzy C-means clustering algorithm; obtaining a binary image; performing edge detection on an image I<Bgrow>; performing Hough transformation on an image I<edge> in order to obtain a linear equation for cutting pavements; marking the communication regions of an image I<hough>; extracting possibly-existing ROIs of the pedestrian; performing HOG+SVM on the extracted ROIs in order to perform accurate pedestrian detection; and drawing a rectangular frame with a size of 128*64 pixel2 on the original image I. The method effectively decreases the number of traversal windows so as to improve detection speed and detection precision.