178results about How to "Enhanced edge" patented technology

A method of providing visual documentation and information for a surgical procedure. The method includes, providing at least one video camera for generating a video signal in a digital format, capturing an image of an eye and displaying the image on a monitor. A first template is created having a graphical content pertinent to the eye. The first template is displayed such that the first template is overlaid contemporaneously with the image of the eye on a display monitor.

A method of automatically capturing images with precision uses an intelligent mobile device having a camera loaded with an appropriate image capture application. When a use initializes the application, the camera starts taking images of the object. Each image is qualified to determine whether it is in focus and entirely within the field of view of the camera: Two or more qualified images are captured and stored for subsequent processing. The qualified images are aligned with each other by an appropriate perspective transformation so they each fill a common frame. Averaging of the aligned images reduces noise and a sharpening filter enhances edges, which produces a sharper image. The processed image is then converted into a two-level, black and white image which may be presented to the user for approval prior to submission via wireless or WiFi to a remote location.

A method and device for sharpening detected edges in an image to compensate for a corruption that occurs during the scanning and printing processes. Edges are enhanced by increasing the contrast between two sides of an edge region according to the amount of distortion in the image signal at that location. Each pixel in the image is analyzed in the context of neighboring pixels in the image to determine the presence of an edge and the degree of sharpening required. A filter is applied to adjust the intensity value of pixels in an edge region to correct for distortion and to emphasize the edge. The resulting final image contains sharpened edges with little effect on the smooth transition regions of the image.

A method including receiving data corresponding to an original three-dimensional (3D) reconstructed image, smoothing homogenous areas and enhancing edges of the original reconstructed image using edge enhancing diffusion (EED) to create edge-enhanced image data, and calculating a structural importance map. The structural importance map includes a measure of structural importance for each voxel of data in the original reconstructed image. Voxel intensities to be used to create a filtered image are determined according to at least one rule applied to the measure of structural importance.

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 relates to an infrared- and visible light- image fusion method, on the basis of multiresolution decomposition for the infrared- and visible light- images, utilizing their different imaging properties to obtain the relative 'object'- and 'background'- data from them, and thus dividing the fusion image into a background area, an object area and an edge part between the two areas, and then respectively adopting three different fusion rules to determine the multiresoluton expression of the fusion image, and finally making multiresolution reverse-transformation to obtain the fusion image. By an object area-based method, it fuses the infrared- and visible light- images of the same scene, and largely improves the image quality all the more.

Image refreshers enhance edge portions of field data stored in field memories, and then store the result in field memories. An intra-field interpolating unit interpolates a moving image pixel using a single piece of field data stored in the field memory, and then stores the moving image pixel in an interpolation memory. An inter-field interpolating unit interpolates a still image pixel using two pieces of field data stored in the field memories, and then stores the still image pixel in an interpolation memory. A still/moving image area determining unit determines whether each pixel of a progressive picture is a still image pixel or a moving image pixel. On the basis of a result of the determination by the still/moving image area determining unit, a selector reads a pixel value in the interpolation memory for a moving image pixel, and reads a pixel value from the interpolation memory for a still image pixel.

The invention relates to an infrared image enhancement method for electrical equipment based on non-downsampling shear wave transform. The method comprises the following steps: step S100, establishinga mapping relationship between RGB and gray value of an infrared image; Step S200, performing non-downsampling shear wave transform on the infrared image of the electric equipment obtained in the experiment; S300, calculating the maximum inter-class difference of the infrared low-frequency image of the electrical equipment, obtaining a segmentation threshold between the background and the foreground, and segmenting the low-frequency image into two classes of the environmental background and the electrical equipment; S400, enhancing the low-frequency image, linearly enhancing the low-frequencyforeground electrical equipment, and performing histogram equalization and enhancement on the low-frequency background; Step S500, designing an optimized fuzzy membership function, and carrying out fuzzy enhancement on the high-frequency image of the electrical equipment; Step S600, synthesizing the enhanced low-frequency coefficient and high-frequency coefficient according to the NSST inverse transform into a new electrical equipment infrared image. Compared with the prior art, the invention has the advantages of higher image quality, stronger practicability and the like.

Ballistic resistant fabric laminates are provided. More particularly, reinforced, delamination resistant, ballistic resistant composites are provided. The delamination resistant, ballistic resistant materials and articles may be reinforced by various techniques, including stitching one or more ballistic resistant panels with a high strength thread, melting the edges of a ballistic resistant panel to reinforce areas that may have been frayed during standard trimming procedures, wrapping one or more panels with one or more woven or non-woven fibrous wraps, and combinations of these techniques. The delamination resistant, ballistic resistant panels may further include at least one rigid plate attached thereto for improving ballistic resistance performance.

The invention discloses an image blind deblurring method based on edge self-adaption. To solve the problems that as for an existing total variation deblurring algorithm, edges and details of images are easily blurred, a de-mean gradient total variation canonical model is built, weighting coefficients are calculated in an iterated mode by means of local variance self-adaption of gradients of the images, and the ability of the deblurring algorithm to restore the edges and the details of the images. The image blind deblurring method comprises the following steps that (1) a blurred image is input, solutions to a gradient-region clear image and a blurring kernel are obtained alternately, and the initial blurring kernel of the blurred image is obtained; (2) the initial blurring kernel is used for conducting primary non-blind deblurring on the blurred image, and an initial clear image is obtained; (3) clustering is conducted on the initial clear image, the mean value and the weighting coefficient in the de-mean canonical model are updated, and a solution to the blurring kernel is obtained again; (4) the new blurring kernel is used for conducting secondary non-blind deblurring so as to obtain a clear image. Experimental results show that the image blind deblurring method based on edge self-adaption has better deburring effect than the prior art and can be used for image restoration.

A carrier for pipette tips, with

• • a frame, featuring four side walls,
  • a plate with a plurality of holes for inserting pipette tips, and
  • means for detachably connecting the frame and the plate,
  • that have contact surfaces on the upper edge of the frame and on the underside of the plate, which touch each other when the plate is put onto the frame, and
  • that have guiding elements directed transversally to the contact surfaces on the frame and on the plate, which engage into each other with lateral clearance when the plate is put onto the frame.

The invention discloses an image super-resolution method comprising the following steps of: acquiring an original image, up-sampling the original image to obtain an initial result; filtering the sampled initial result by using a plurality of impact filter waves to obtain an intermediate result; and carrying out reconstruction constraint on the intermediate result to obtain a high-resolution image. Image space information and strength information are simultaneously considered in the up-sampling algorithm, and current pixels are smoothed by using a bilateral filtering method; the impact filter waves can enhance the edge of the image; and finally reconstruction is carried out to obtain the high-resolution image. Therefore, the generated high-resolution image has smooth transition and can effectively avoid obvious boundary flaws. In addition, the invention provides an image super-resolution system.

The invention relates to a lane line detection method, and belongs to the field of automobile active safety. The method comprises the steps that (1) a camera captures a video image; (2) edge enhancement is performed on the captured video image; (3) a self-adapting threshold selection method is adopted for the image after being processed through the edge enhancement to calculate a binarized threshold, and a binarized image is obtained; (4) lane line inner side edge point extraction is performed on the binarized image; (5) partition Hought transformation is adopted for the extracted image data for fitting lane lines. In the method, a self-defining difference algorithm is adopted, so that the lane line edges are enhanced well, and the problem that in the prior art, an automobile has a traffic accident due to lane deviation is solved.

An edge detection filter comprising an array of filter coefficients having an odd number of rows and columns, a first set of zero coefficients extending along a direction traversing the array through a center position to form a first and second side, a second set of positive coefficients extending away from the direction on the first side, and a third set of negative coefficients extending away from the direction on the second side.

A noise removing filter removes noise from an input image and an edge component extracting unit extracts edge components. The edge components are extracted by calculating a difference between the input image and a smoothed image, which is obtained by smoothing the input image in a smoothed image generating portion. An edge component comparing unit compares the extracted edge components with a threshold value and a sum calculating unit calculates the sum of the edge components greater than the threshold value. A control circuit determines, the enhancement degree of the edges based on the sum and averaged luminance of the input image calculated by an average luminance calculating unit. An enhancement degree adjustment unit adjusts the determined enhancement degree, and an edge component enhancement unit enhances the edge components based on this enhancement degree and adds it to the input image to perform edge enhancement processing.

The invention belongs to the technical field of video monitoring and image processing and provides a method and device for automatically sharpening a video image. The method comprises: using the brightness image of the video image as an original image; determining a sharpening grade and a sharpening threshold value of the video image according to the brightness information of the video image; performing fuzzy processing on the original image to obtain a fuzzy image and subtracting the fuzzy image from the original image to obtain a template image; enhancing the template image according to the brightness grade, the sharpening grade, and the sharpening threshold value of the current image in order to obtain an enhanced template image; and adding the original image to the enhanced template image to obtain a target image. The technical method provided by the invention may automatically adjust the sharpening grade and the sharpening threshold value of the current video image according to the brightness information of the video image, may enhance the edges and the details of the video image in an environment with sufficient light, and may prevent noise from being excessively amplified and influencing video quality in a sharpening process in an environment with low illumination.

An image processing method includes: discriminating between a still picture area and a motion picture area in an input image; enhancing edges with a quantity of edge enhancement larger in the motion picture area than in the still picture area; and outputting the input image having the enhanced edges. The output having the enhanced edges is displayed on a display unit.

Apparatus, systems, and methods to recognize features on bottom surfaces of containers on a container production line, detect defects in the containers, and correlate the defects to specific production equipment of the container production line, based in part on the recognized features. The system includes imaging apparatus, programmable processing devices, and controllers. The methods include imaging techniques and estimation techniques.

A portable, closed-loop system of capture, analysis, and feedback uses a headset containing a small unobtrusive camera and a control computer that communicates wirelessly with a wireless network and/or remote platform. The headset may also contain user controls, an audio feedback component, a battery, interconnection circuitry, cables, and connections for an intraoral device. The camera component of the headset captures images during an activity to be analyzed, such as walking or viewing a room, and sends data (e.g., visual data) to the controller. The controller transmits the data to a database on the remote platform that includes software that instantly analyzes the image information represented in the data, then provides immediate feedback to the headset. The controller may independently process the data.

The invention discloses a sparse matrix and convolutional neural network-based picture compression method. The method comprises the following steps of converting an image into two-dimensional matrix data; assessing, optimizing and constructing a sparse matrix image by utilizing a convolutional neural network; optimizing a compression scheme through the convolutional neural network; performing compression processing on the sparse matrix image by using the selected optimal compression scheme; and finally obtaining a high-compression-ratio and low-distortion compressed image. According to the method, the problem of difficult use and identification of the image due to low compression ratio and excessively reduced quality of the compressed image in an existing compression technology is solved; and the optimization can be carried out according to picture contents, and the proper image construction and compression method can be self-selected, so that the picture feature extraction and compression method has self-optimization and learning capabilities.

Apparatus, systems and methods for improving strength of a thin glass cover for an electronic device are disclosed. In one embodiment, the glass member can have improved strength by forming its edges with a predetermined geometry and/or by chemically strengthening the edges. Advantageously, the glass member can be not only thin but also adequately strong to limit susceptibility to damage. In one embodiment, the glass member can pertain to a glass cover for a housing for an electronic device. The glass cover can be provided over or integrated with a display, such as a Liquid Crystal Display (LCD) display.