46 results about "Prewitt operator" patented technology

The invention provides a Prewitt operator-based pavement crack recognition method and system. The method comprises the steps of S1, performing first image processing on an input pavement image to remove a region outside a pavement so as to obtain a pavement region image; S2, performing second image processing on the pavement region image to remove a pavement boundary line; and S3, performing preliminary recognition and accurate recognition on a pavement crack to obtain pavement crack data. According to the method and the system, the pavement image is subjected to calculation processing based on a Prewitt operator, a useless image outside the pavement is filtered, image interference and noises of a pavement region are gradually removed, the pavement crack is extracted, the length of the crack is calculated, and quantitative output is performed, thereby facilitating comparison with an actual standard; the method and the system are mainly applied to the pavement crack detection of complex high-altitude motion background and scene; and compared with various common crack detection algorithms, the method and the system have the advantages that the adaptability is higher and a better aerial image-based crack recognition effect is achieved.

The invention discloses an infrared thermal imaging system-based fault recognition method. The method comprises the following steps of: 1, shooting electric equipment by adoption of an infrared thermal imaging system so as to obtain an infrared image of the electric equipment, and preprocessing the infrared image of the electric equipment; 2, carrying out threshold value segmentation on the preprocessed infrared image by adoption of a maximum entropy method; 3, carrying out edge detection on the infrared image after the threshold value segmentation by taking a Prewitt operator as an edge detection operator; 4, carrying out expansion processing on the infrared image after the edge detection by using an expansion algorithm; and 5, fusing the infrared image of the electric equipment after theexpansion processing with a visible image of original electric equipment so as to differentiate heating targets in the electric equipment from surrounding background. According to the method, an infrared temperature image processing technology is utilized to search temperature heating abnormal points and automatically judge operation condition and fault information of the electric equipment, so that the operation condition of the electric equipment is online and rapidly detected.

The invention discloses a method for recognizing the position of a spherical object based on contour, and the method comprises the steps: marking a target image region through obtaining an original image of a target region, and combining with the eccentricity of the target image region; carrying out the corrosion shrinkage of the image after binarization processing, and enabling the edges of the image to be symmetric, thereby reducing the noise points; further employing a Prewitt operator to detect contour points; determining a fitting circle based on the contour points; and determining that the coordinates of the center of the fitting circle as the central position of the spherical object when the number of contour points reaches a target threshold value, wherein the distances between the center of the fitting circuit and the contour points are within a set range. The method can effectively reduce the noise points, is simple in operation, and is high in contour recognition accuracy.

The present application discloses a method for image edge detection, and the method comprises the steps of performing region growth on a target image according to a gray value of each pixel in the target image, and removing the background of the target image according to a region growth result to obtain a to-be-detected image; calculating gray level differences between eight adjacent pixels of each pixel on the image to be detected by using a Prewitt operator, and determining a new gray level of the pixel according to the gray level differences; determining whether the new gray value of the pixel is greater than a preset value; if the new gray value of the pixel is greater than the preset value, setting the pixel as an edge point; and obtaining an image edge of the target image according to all the edge points. The method can reduce local interferences on the image edge detection by noises and reduce conditions of image edge interruption. The application also discloses an image edge detection system, a computer-readable storage medium and an image processing apparatus having the above beneficial effects.

The invention relates to a power plant high-temperature pipeline defect detection and segmentation method based on OTSU and a region growing method, and the method comprises the following steps: obtaining an original infrared image, carrying out the graying, and extracting a pipeline region through the improved two-dimensional OTSU pre-segmentation; finding out a gray scale range corresponding tothe normal temperature of the pipeline through the gray scale distribution histogram of the pipeline area; judging whether the maximum value of the neighborhood gray average value exceeds a normal gray range or not to finish automatic detection and positioning of the multi-defect seed points; and taking the self-adaptive threshold adjusted according to the gray average value and the standard deviation of the grown region as a growth criterion, and taking a gradient amplitude threshold calculated based on a Prewitt operator as an additional condition to realize growth and extraction of the defect region. Compared with the prior art, the system has the advantages of high reliability and accuracy and good real-time performance, and can meet application requirements.

The invention provides an improved Prewitt operator-based fire complex environment image detecting method. The method comprises the steps of: S1, filtering an analog fire complex environment image byutilizing a morphological smoothing algorithm, preserving edge information and removing noise; S2, calculating single-scale morphological gradient and multi-scale morphological gradient of the image;and S3, carrying out edge detection on the multi-scale morphological gradient image by adopting an improved Prewitt edge detection operator to obtain the edge information of the analog fire complex environment image.

The invention discloses an enhancement method suitable for a true color remote sensing image. The enhancement method mainly comprises the following steps: 1, carrying out linear stretching transformation on an input true color remote sensing image; 2, converting the image subjected to linear stretching transformation into an HSI color space; 3, calculating a gradient gray level joint histogram ofthe I component in the HSI color space; 4, adjusting and optimizing the shape of the histogram in a self-adaptive manner according to the statistical characteristics of the gradient gray level combined histogram; 5, remapping the gray value of the I component by using a histogram equalization method to obtain a globally enhanced I component; 6, calculating a gradient difference between the original I component and the global enhanced I component by using a Prewitt operator, and carrying out detail compensation on a gradient descent region of the global enhanced I component to obtain a global and local enhanced new I component; and 7, converting the new I component and the original H and S components into an RGB color space. The true color remote sensing image enhanced by the method is goodin visual effect, real in color and rich in details.

The invention, which belongs to the technical field of measurement, particularly relates to a detection method for a trace amount of dust based on microscopic image processing. The method comprises the following steps: step 1, collecting an image of eachdust particle on a certain surface by using a microscopic imaging system; step 2, performing gray processing on the dust particle images; step 3,performing illumination correction ongrayscale images by using a block background extraction method; step 4, carrying out median filtering processing on the images after illumination correction; step5, drawing gray histograms for the grayscale images; step 6, carrying out image edge detection on the images by adopting a Prewitt operator; step 7, performing binary image processing such as expansion and corrosion on the images; step 8, performing feature extraction on the images, and carrying out statistics on the number of pixel points occupied by each dust particle so as to obtain a pixel area of each dust particle; and step 9, deducing the volume of the dust particle according to the pixel area of the dust particle and acquiring the mass of each dust particle based on the volume and density to obtain the total mass of the dust particles.

The invention discloses a shipborne radar image oil spill monitoring method based on a local adaptive threshold value, and the method comprises the steps: firstly, inhibiting the same frequency interference noise in an original radar image based on an improved Prewitt operator, a robust adaptive threshold value algorithm, and a linear interpolation method; Applying a gray intensity correction matrix model to enable the whole image to be smooth; Then, a finite contrast adaptive histogram equalization algorithm is adopted, so that the contrast of inner and outer regions of the oil film is improved; And finally, obtaining an oil spilling area monitoring result image under a rectangular plane coordinate system by applying an improved local adaptive threshold method and an area threshold method, and projecting and transforming the oil spilling area monitoring result image to a polar coordinate system in the real world, thereby obtaining an oil spilling distribution image, and finally realizing offshore oil spilling real-time monitoring.

The invention discloses a rhinopithecus roxellana qinlingensis image edge detection method based on gray B-type related improvement Prewitt. A high-pixel camera is used for carrying out tracking and real-time shooting on a rhinopithecus roxellana qinlingensis base, an image sample library is established, an obtained image sample adopts a gray B-type related improvement Prewitt operator to detect a rhinopithecus roxellana qinlingensis image edge, and an image edge is extracted. A calculating particle contour line is clear, a feature and a background have a good contrast ratio, the antijamming capability of edge detection is enhanced, the accuracy and the continuity of boundary detection are obviously improved, and therefore, a foundation is laid for realizing rhinopithecus roxellana qinlingensis identification.

The present invention discloses an instantaneous frequency estimation method based on the non-delayed cost function and the PauTa test. The method employs the short-time Fourier transform to convert original signals to a time-frequency spectrogram, employs the Canny detection algorithm to obtain multi-strip ridge bands, employs the PauTa test to eliminate the abnormal value of each ridge band, employs overlapping to construct a compound ridge band having a complete and clear edge, employs the PauTa test to eliminate the abnormal value of the compound ridge band, calculates the mean curve of the compound ridge band, perform smooth processing of the mean curve, calculate a confidence interval, above the 95% confidence level, of the smooth mean curve and map the smooth mean curve and the confidence interval thereof to a target ridge to obtain the reference line and a local search interval of the target ridge, and employs a non-delayed cost function to extract the target ridge. The instantaneous frequency estimation method based on the Prewitt operators and the t test is suitable for estimation of instantaneous frequency of multi-component frequency conversion signals so as to overcome defects in the instantaneous frequency estimation of mechanical vibration signals of a traditional method, improve the accuracy and the precision of the estimation result and facilitate engineering application.

The present invention discloses an instantaneous frequency estimation method based on the Prewitt operator and the t test. The method employs the short-time Fourier transform to convert original signals to a time-frequency spectrogram, employs the Prewitt detection algorithm to obtain multi-strip ridge bands, employs the t test to eliminate the abnormal value of each ridge band, employs overlapping to construct a compound ridge band having a complete and clear edge, employs the t test to eliminate the abnormal value of the compound ridge band, calculates the mean curve of the compound ridge band, perform smooth processing of the mean curve, calculate a confidence interval, above the 95% confidence level, of the smooth mean curve and map the smooth mean curve and the confidence interval thereof to a target ridge to obtain the reference line and a local search interval of the target ridge, and employs a non-delayed cost function to extract the target ridge. The instantaneous frequency estimation method based on the Prewitt operator and the t test is suitable for estimation of instantaneous frequency of multi-component frequency conversion signals so as to overcome defects in the instantaneous frequency estimation of mechanical vibration signals of a traditional method, improve the accuracy and the precision of the estimation result and facilitate engineering application.

The invention relates to a JND prediction method and device based on direction weight, computer equipment and a storage medium. The method comprises the steps of obtaining an input to-be-predicted image; calculating the horizontal direction gradient and the vertical direction gradient of the pixel points in the image by using a Prewitt operator to obtain the directions of the corresponding pixel points; calculating weight factors corresponding to different directions according to the sensitivity difference of human eyes to different directions; respectively calculating a contrast masking metric value, a fuzzy masking metric value and a brightness masking metric value according to the brightness characteristic value in combination with the weight factor; and carrying out nonlinear superposition on the contrast masking metric value, the fuzzy masking metric value and the brightness masking metric value to obtain a final JND prediction value. According to the method, the pixel contrast masking metric values in different directions are adjusted to different degrees in combination with human eye visual characteristics, so that the contrast masking metric value corresponding to a place with relatively high sensitivity is smaller, and the contrast masking metric value corresponding to a place with relatively low sensitivity is larger.

The invention relates to a gray scale accumulation image identification method of a ground penetrating radar. The method comprises: carrying out gray scale accumulation image sharpening processing byusing a Butterworth band elimination filter, carrying out gray scale accumulation image edge detection by using a prewitt operator, and carrying out image feature target identification through Fouriertransform and convolution operation. According to the grayscale accumulation image recognition method of the ground penetrating radar, the intuition of manual image recognition and the convenience ofdirectly analyzing and displaying the recognition result by the system background can be effectively realized, and the efficiency and accuracy of the ground penetrating radar in application are improved.

The invention discloses a binocular parallax calculation method based on a convolutional neural network. Feature extraction is carried out on left and right images by using parallel small expansion convolution kernels; meanwhile, during multi-scale feature fusion, image edge features extracted by a Prewitt operator are added to reinforce the edge feature information of the binocular image; and then 4Dcost volume is constructed by using multi-scale feature information in combination with a parallax network layer, and finally cost aggregation is performed by using a 3D CNN module to obtain a parallax result of the binocular image.

The present invention relates to a NEON acceleration engine of a Prewitt operator. This method uses NEON co-processor and single instruction multi-data acceleration strategy to compute the input imagedata in a vectorized manner. And through pipelining, data splicing and multiplexing and other means to improve computing efficiency. Compared with the existing intelligent terminal core processor, the invention can effectively improve the calculation speed and reach the requirement of image real-time processing. Compared with a dedicated image processing unit (GPU), the invention has lower powerconsumption, can save hardware resources, and is more conducive to popularizing on a portable intelligent terminal.

The invention discloses an infrared image defect edge detection method based on improved mathematical morphology, which is characterized in that a pulsed eddy current nondestructive heating device is applied to ferromagnetic material damage detection; eddy current heating is performed on a test piece, and the damage characteristics of the test piece are represented in the form of a thermal image. The invention has the advantages that a detected object does not need to be contacted, the thermal imaging result is intuitive and clear, the detection efficiency is high, and a larger range can be detected in a shorter time; an infrared image of a ferromagnetic test piece is filtered and segmented by using a multi-scale and multi-direction mathematical morphology edge detection method, and the processing and experimental results show that the method has better image denoising and image segmentation effects than edge detection results of a Roberts operator and a Prewitt operator. The defect of poor anti-noise effect in edge detection is overcome, the noise in the image is effectively inhibited, the defect position in the image is accurately detected, and the edge information of the defect is reserved.

The present invention discloses an instantaneous frequency estimation method based on the Roberts operator and the t test. The method employs the short-time Fourier transform to convert original signals to a time-frequency spectrogram, employs the Roberts detection algorithm to obtain multi-strip ridge bands, employs the t test to eliminate the abnormal value of each ridge band, employs overlapping to construct a compound ridge band having a complete and clear edge, employs the t test to eliminate the abnormal value of the compound ridge band, calculates the mean curve of the compound ridge band, perform smooth processing of the mean curve, calculate a confidence interval, above the 95% confidence level, of the smooth mean curve and map the smooth mean curve and the confidence interval thereof to a target ridge to obtain the reference line and a local search interval of the target ridge, and employs a non-delayed cost function to extract the target ridge. The instantaneous frequency estimation method based on the Prewitt operators and the t test is suitable for estimation of instantaneous frequency of multi-component frequency conversion signals so as to overcome defects in the instantaneous frequency estimation of mechanical vibration signals of a traditional method, improve the accuracy and the precision of the estimation result and facilitate engineering application.

The invention relates to a substation equipment thermal fault diagnosis method and system. The method comprises the following steps: preprocessing an infrared image; determining a corresponding temperature matrix according to the preprocessed infrared image; performing coarse segmentation of a power transformation equipment target and a background on the preprocessed infrared image by adopting a K-means clustering algorithm; combining difference information obtained by detecting a target edge through a Prewitt operator with a Chan-Vese model, and determining an improved Chan-Vese model; taking the infrared image subjected to coarse segmentation as an initial segmentation condition of the model, performing fine segmentation of the power transformation equipment target and the background on the infrared image subjected to coarse segmentation by using the model, and determining a target position to be diagnosed; determining the temperature of the target position according to the target position and a temperature matrix; and diagnosing the thermal fault of the substation equipment according to the temperature of the target position. The accuracy of thermal fault diagnosis of the substation equipment can be improved.

The invention provides an image quality evaluation method and device based on an extended Prewitt operator, and the method comprises the steps: obtaining a reference image and a to-be-evaluated distorted image; preprocessing the reference image and the distorted image, and determining a brightness factor and a contrast factor of the reference image and the distorted image; performing convolution operation on the reference image and the distorted image according to the extended Prewitt operator, and calculating a first gradient value corresponding to the reference image and a second gradient value corresponding to the distorted image; determining a gradient similarity factor of the reference image and the distorted image according to the first gradient value and the second gradient value; and determining an objective evaluation result of the image quality by combining the gradient similarity factor, the brightness factor and the contrast factor. According to the method, the defects of atraditional Prewitt operator are correspondingly improved, the quality of the noise image can be evaluated, and the method has good consistency with a subjective evaluation result.