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233 results about "Ideal image" patented technology

Steel rail surface defect image adaptive segmentation method

The invention discloses a steel rail surface defect image adaptive segmentation method. The method comprises the following steps of S1, extracting a steel rail region by adopting a row grayscale mean successive summation method; S2, preprocessing a steel rail region image; S3, performing structure region and non-structure region division on the steel rail region image; S4, further distinguishing a defective region and a shadow region by utilizing a non-local feature of the image in the structure region; S5, adaptively building a background image model according to different features in the image; S6, performing image difference; and S7, performing dynamic threshold segmentation. The image is divided into the structure region and the non-structure region by utilizing image local information, the size of a pixel neighborhood window is adaptively adjusted by utilizing non-local information to calculate a mean, the accurate background image model is built, and the image difference and the dynamic threshold setting are performed, so that while a defective part of the image is highlighted, the influence of uneven illumination and steel rail surface reflection property on steel rail surface defect detection is effectively reduced, an ideal image segmentation effect is achieved, and the rail surface detection precision is ensured.
Owner:LANZHOU JIAOTONG UNIV

Converting low-dose to higher dose mammographic images through machine-learning processes

A method and system for converting low-dose mammographic images with much noise into higher quality, less noise, higher-dose-like mammographic images, using of a trainable nonlinear regression (TNR) model with a patch-input-pixel-output scheme, which can be called a call pixel-based TNR (PTNR). An image patch is extracted from an input mammogram acquired at a reduced x-ray radiation dose (lower-dose), and pixel values in the patch are entered into the PTNR as input. The output of the PTNR is a single pixel that corresponds to a center pixel of the input image patch. The PTNR is trained with matched pairs of mammograms, inputting low-dose mammograms together with corresponding desired standard x-ray radiation dose mammograms (higher-dose), which are ideal images for the output images. Through the training, the PTNR learns to convert low-dose mammograms to high-dose-like mammograms. Once trained, the trained PTNR does not require the higher-dose mammograms anymore. When a new reduced x-ray radiation dose (low dose) mammogram is entered, the trained PTNR would output a pixel value similar to its desired pixel value, in other words, it would output high-dose-like mammograms or “virtual high-dose” mammograms where noise and artifacts due to low radiation dose are substantially reduced, i.e., a higher image quality. With the “virtual high-dose” mammograms, the detectability of lesions and clinically important findings such as masses and microcalcifications can be improved.
Owner:ALARA SYST

Large-viewing-angle image distortion correction and processing method

The invention discloses a large-viewing-angle image distortion correction and processing method. The large-viewing-angle image distortion correction and processing method comprises the steps of S1, calculating a distance between any point in a corrected image and the center of the image, namely ideal image height; S2 adopting an improved distortion rate formula to calculate the distortion rate D corresponding to the point; S3, calculating distortion point coordinates according to the distortion rate D; S4 adopting a bilinear interpolation method and ideal coordinates corresponding to the obtained distortion point coordinates to perform interpolation so as to obtain a corrected image. A distortion correction approximation model of the method can conveniently obtain the distortion rate of each point, accordingly the corresponding distortion point coordinates can be calculated according to the coordinates of ideal points, and a 'void' phenomenon produced on the corrected image is avoided. The large-viewing-angle image distortion correction and processing method does not need a specially manufactured template to calibrate lens distortion parameters, accordingly a large number of iterative operation during parameter calculation is omitted, and the method is simple and easily achieved in hardware. In addition, when the image size is large, the calculation time can be effectively shortened, and the universality is good.
Owner:玉振明 +3

Fuzzy clustering image segmentation method with plane as clustering center and anti-noise ability

The invention discloses a fuzzy clustering image segmentation method with plane as clustering center and anti-noise ability. The method comprises the following steps: firstly, defining an objective function, initializing various coefficients and thresholds in the objective function, and randomly initializing a membership matrix; minimizing the objective function to calculate and update the coefficients and fuzzy membership matrices of the clustering plane. calculating the value of the objective function based on the updated fuzzy membership matrix, when the absolute value of the difference between the objective function values of the two successive iterations is less than the termination condition or the method exceeds the maximum iteration number limit, the iteration ends, otherwise, theiteration continues to perform the updating, and each pixel point is classified and marked according to the criterion of the maximum membership, so as to complete the initial classification; The edgeof the image is extracted from the classification result, and the local window is selected to divide the membership degree again with the edge point as the center pixel. According to the fuzzy membership matrix of clustering output, the membership degree of data points belonging to a certain class is obtained, and each data point is classified and marked according to the maximum probability principle, and the image segmentation is completed. The method of the invention uses a clustering plane instead of a clustering center for image segmentation, can simultaneously consider the gray value information and the position information of pixels, obtains an ideal image segmentation effect, eliminates the influence of noise well, and improves the quality of image segmentation and the stability ofthe segmentation effect.
Owner:SHANDONG UNIV

Camera calibration board, calibration data acquisition method, distortion correction method and device

The invention relates to a camera calibration board, a calibration data acquisition method and a distortion correction method and device, and relates to the technical field of machine vision, and themethod comprises the steps: collecting a checkerboard image through employing the camera calibration data acquisition method, and obtaining the serial numbers of all image corners in the checkerboardimage and the corresponding three-dimensional coordinates; selecting a plurality of angular points in the center of the checkerboard image, and determining the three-dimensional coordinates corresponding to the plurality of angular points; and optimizing the initial distortion parameter to obtain an optimized distortion parameter, and performing distortion correction according to the calculated optimized distortion parameter. Only one checkerboard image needs to be collected, and one-to-one correspondence of collected image corners and three-dimensional coordinates is completed through specialfixed corners. An ideal image corner is obtained to calculate an initial distortion parameter of the camera, and an accurate distortion parameter is obtained for correction after optimization. The accuracy of distortion correction is improved, the operation process is simplified, and the method is suitable for rapid production.
Owner:MEGVII BEIJINGTECH CO LTD

Color image super-pixel segmentation method based on similarity between pixels

The invention discloses a color image superpixel segmentation method based on similarity between pixels. The method comprises the following steps: firstly, an image to be segmented is initially clustered; then, a seed point is determined based on the initial clustering; whether a seed point needs to be added is judged; if so, the seed point is added; if so, the seed point is added; an initial superpixel is generated according to the initial clustering and the marker of the seed point; For unmarked pixel points, the defined energy function is used to calculate the energy of the seed point andthe pixels in its searching range, The superpixel marker of the seed point with the least energy is selected as the superpixel marker of the unmarked pixel. Finally, the isolated pixel satisfying thethreshold condition and the isolated very small superpixel are merged into the neighboring superpixels which are most similar to the superpixel marker until the number of the current superpixels reaches the desired number, so as to realize the superpixel segmentation of the image. The method of the invention can obtain the ideal image segmentation effect, and provides higher regularity in the image flat area, thereby improving the quality and the segmentation effect of the image segmentation.
Owner:SHANDONG UNIV

Dynamic non-uniformity correction method for linear scanned image based on image sequence analysis

The invention provides a dynamic non-uniformity correction method for a linear scanned image based on image sequence analysis. The dynamic non-uniformity correction method comprises the following steps: firstly, selecting k (k is equal to 1, 2,..., and belongs to Z) images for the existing image to be corrected, and setting an ideal desired value q; then, calculating the average value of pixel values on each row of the k images to acquire a mean vector; and finally, using a ratio of the mean vector to the set ideal desired value as a correction coefficient to correct the images, so that a novel image which is uniform in background, clear in defect contour and convenient to position a subsequent defect target is acquired. The method can effectively overcome influences of changes of such factors as parameters including material specification, thickness and the like of the detected object, detection angle, plate type consistency and light source illumination attenuation, so as to dynamically acquire in real time an ideal image which is uniform in grey distribution, high in definition and remarkably enhanced in the detected object, thus greatly simplifying subsequent image processing difficulty and effectively improving the real-time performance of the integral system.
Owner:苏州有色金属研究院有限公司

Super-smooth surface defect detection system and distortion correction method thereof

ActiveCN102661956AReduce the impact of shape changesOptically investigating flaws/contaminationIdeal imageWide field
The invention provides a super-smooth surface defect detection system and a distortion correction method thereof. The invention aims to solve the problem that defects are fractured when subimages are spliced due to the fact that optical distortion exists in the super-smooth surface defect detection system. The invention is technically characterized in that the super-smooth surface defect detection system, a distortion correction on-gauge plate and a clamping device for the on-gauge plate are designed. The on-gauge plate is collected to obtain a distortion image of a dark field by utilizing the detection system; a distortion degradation model is established through the distortion image and a computer by matching with an ideal image of the on-gauge plate reconstructed according to the relation between the dimension of an object plane and the pixel of an image plane, and the distortion correction method based on secondary polar coordinate positive and negative transformation and secondary gray level linear interpolation is provided. The method can be used for correcting the distortion in the super-smooth surface defect detection system to avoid splicing dislocation of adjacent subimages, and meanwhile, is also suitable for correcting the distortion existing in other wide-field optical systems based on image splicing.
Owner:ZHEJIANG UNIV
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