74 results about "Contour analysis" patented technology

The invention relates to the technical field of machine vision, in particular to a precision part size automatic detection method and system based on machine vision, precision part images are collected through a high-precision industrial camera, part positioning is carried out, sub-pixel-level topological feature mapping is carried out on interested area images, and precision part size automatic detection is carried out. Comprising the steps of gray histogram equalization, gray morphological processing, edge detection and edge chain code tracking, construction of an edge point topological feature space, execution of sub-pixel subdivision, obtaining of an edge line through contour analysis of a feature distance and a feature angle, and double-constraint geometric reconstruction based on the edge line. The characteristic distance and the characteristic angle are used for rotation matrix conversion and geometric dimension calculation, a relation model of the geometric dimension and the actual dimension of the part is established, precise part dimension measurement is achieved through dynamic error analysis and compensation, the measurement precision is remarkably improved, the risk caused by unreliability of a single characteristic is effectively reduced, and the measurement accuracy is improved. And the measurement stability is improved.

The invention relates to the technical field of target detection, in particular to a search and rescue task-oriented unmanned aerial vehicle thermal imaging visual target detection method, which comprises the following steps of: acquiring multiple frames of thermal imaging images of an unmanned aerial vehicle, extracting regional thermal difference characteristics according to a window, marking a non-background region to generate a candidate set, and fitting and reconstructing a suspected thermal target contour. And analyzing the track and the thermal change rate, screening background interference, identifying jump abnormity, positioning the gravity center, and generating a target repositioning signal. According to the method, the heat value range and variance index sequence in the image area is constructed, the thermal anomaly area is judged in combination with the temperature baseline difference, background disturbance comparison is executed in combination with the direction vector of the coordinate trajectory in the multi-frame image and the thermal change parameter, the false detection probability caused by background noise is reduced, and the detection accuracy is improved. The target jump identification is carried out according to the inter-frame heat value and area change rate in linkage with the thermal isoline closure degree, the target discrimination accuracy in a shielding scene is improved, and the robustness of thermal target extraction in a complex search and rescue environment is integrally improved.

The invention provides a calligraphy work automatic identification and evaluation method and system, and the method comprises the steps: collecting calligraphy pattern images of different calligraphers, fonts and styles, and forming a multi-dimensional labeling original data set; carrying out standardization processing on the acquired calligraphy images; extracting stroke-level manual statistical features by using edge detection and contour analysis based on the standardized sample, extracting high-dimensional deep features by using a convolutional neural network, and fusing to form a unified multi-dimensional style feature vector; and performing unsupervised clustering on the fusion feature vectors of all the samples, and establishing a high-dimensional style prototype library. Obtaining a multi-dimensional similarity vector of a newly input calligraphy image; performing semantic unification processing on the new sample; and performing real-time scoring output on the new sample by using the exclusive evaluation model. The method can efficiently and accurately identify and evaluate the calligraphy work, is high in adaptability, and can be widely applied to the fields of calligraphy teaching, calligraphy work evaluation, digital calligraphy management and the like.

The invention provides an AI vision-based coal cinder amount intelligent detection early warning method and system, and the method comprises the steps: synchronously collecting the surface feature information, thermal radiation feature and internal structure information of a slag hopper of a slag conveyor through a dual-spectrum camera, and obtaining a dual-spectrum image; pixel-level coal cinder segmentation is carried out on the double-spectrum image; based on the segmentation result, counting the pixel proportion of the coal cinder area, and converting the pixel proportion into the actual coal cinder total amount proportion; identifying the segmented coal cinder area by adopting connected domain analysis, dynamically adjusting a size judgment threshold value through contour analysis and geometric feature extraction in combination with the bearing capacity of the slag conveyor, and determining whether large coal cinder exists or not; when the actual coal cinder total amount proportion is larger than the preset threshold value or large coal cinder exists, the risk level is generated to trigger the multi-level early warning control action, the actual coal cinder total amount proportion and the large coal cinder are automatically recognized through double-spectrum fusion segmentation, and early warning is given out when abnormity occurs, so that the accuracy and the real-time performance of coal cinder amount detection are effectively improved.

The invention relates to the technical field of detection systems, in particular to a quartz sand impurity rapid detection system, which comprises an image processing unit for regularly shooting images on a conveyor belt and recording the images as logistics images, and determining a target area corresponding to each logistics image based on a coincident part; the impurity identification unit is used for identifying the material contour in the target area, analyzing the impurity type corresponding to the material contour, marking the material contour corresponding to the impurity as a target contour and determining the position of the target contour; the air injection control unit is used for analyzing and determining the air injection opportunity of each air injection blowing nozzle based on the position coordinates when the target contour is identified and marked in combination with the conveying speed of the conveying belt; and when the air injection opportunity corresponding to the target contour is output, analyzing the shape characteristics of the target contour to obtain a projection area and a thickness measurement value, and adjusting the air flow parameters of the air injection blowing nozzle in combination with the corresponding related impurity types. According to the invention, different types of impurities can be effectively distinguished and targeted elimination can be carried out.

The invention discloses a workpiece contour projection extraction method and system based on ordered point cloud, and is applied to the technical field of three-dimensional precision measurement. The method comprises the following steps of obtaining high-precision ordered point cloud data of a target workpiece and performing preprocessing; geometric analysis is carried out through the three-dimensional visual point cloud model, and section parameters are defined; performing rapid gridding processing on the ordered point cloud data through an efficient triangulation algorithm; calculating to obtain an intersection discrete point set of the cross section and the triangular mesh; and establishing a section plane local coordinate system and implementing two-dimensional projection transformation to obtain the contour projection of the target workpiece. According to the method, high-precision, high-efficiency and automatic extraction of the section contour of the workpiece can be realized, the actual requirements of industrial field online detection and quality control are met, and the method can be applied to scenes such as part size detection, reverse engineering, quality control and contour analysis in industrial manufacturing.

The invention relates to the technical field of industrial big data, in particular to LED light bar dispensing quality detection equipment based on visual inspection, which comprises an image processing module, a contour analysis and judgment module and an edge division compensation module, converting the dispensing area image into a grayscale image by using an image processing algorithm, and separating a dispensing area from a background area by using a threshold segmentation method; the contour analysis and judgment module is used for judging whether the glue dispensing area has defects, less glue and more glue; the edge division compensation module adopts an edge division method to extract edge pixel points in the gray level image, if the edge pixel points in the dispensing area in the image processing module are different from the edge pixel points in the gray level image in coordinate, the edge pixel points in the dispensing area are adjusted, the image processing module provides basic segmentation, the contour analysis module realizes logic judgment, and the image processing module processes the edge pixel points in the gray level image. And the edge division compensation module corrects local errors.

Techniques are provided for implementing liquid tolerance for a touch device. A sensor array of the touch device is scanned to generate response signals. In response to a response signal exceeding a touch threshold, a signal profile analysis is performed. The signal profile analysis includes sorting the response signals according to ascending order of delta positions to generate sorted signals. An extended vector of the sorted signals is formed. The extended vector of the sorted signals is analyzed using a fitted curve. In response to a feature of the fitted curve satisfying a criteria, the response signal is reported as a touch event. In response to the feature not satisfying the criteria, the response signal is rejected as a false touch.

This invention relates to the field of laser processing and automated control technology, and particularly to a laser heating system, including an equipment device and a control device. The equipment device includes a support platform, a transmission mechanism, a laser, and vision components. The control device includes image acquisition, contour analysis, error compensation, coordinate optimization, and pulse sending modules. The image acquisition module drives the vision component to acquire material images and transmits them to the contour analysis module; the contour analysis module calculates deformation parameters and sends them to the error compensation module; the error compensation module combines pre-stored mechanical errors to generate a compensation matrix and sends it to the coordinate optimization module; the coordinate optimization module calculates and outputs the target coordinates to the pulse sending module; the pulse sending module drives the laser component to move and commands it to emit light. This invention solves the positioning deviation caused by hardware errors and changes in material size, improving control accuracy.

The invention discloses a limb protection position detection method and device, equipment and a medium, and the method comprises the steps: recognizing a dangerous region and limb protection in a monitoring video frame through a trained limb protection detection model; respectively extracting the contour of the dangerous area and the contour of the limb protection, and determining the shortest distance between the contour of the dangerous area and the contour of the limb protection; and determining whether the edge protection placement position is qualified or not according to the shortest distance. According to the method, accurate segmentation and classification of the edge protection and dangerous areas in the construction site are realized, the accuracy of safety monitoring is greatly improved, and meanwhile, the introduced contour analysis and distance calculation effectively assess whether the edge protection setting reaches the standard or not, so that the safety management level of the construction site is comprehensively improved.

The invention discloses a laser cutting path optimization method of laser cutting equipment, and relates to the technical field of cutting path optimization. According to the laser cutting path optimization method of the laser cutting equipment, geometric primitive data of a to-be-cut workpiece is obtained, contour analysis processing is carried out, and a contour geometric data set of the to-be-cut workpiece is extracted; cutting sequence planning processing is conducted on the contour geometric data set of the to-be-cut workpiece based on a genetic algorithm, and an initial cutting path of the to-be-cut workpiece is generated; multi-target collaborative optimization processing is conducted on the initial cutting path of the to-be-cut workpiece, and the optimized cutting path of the to-be-cut workpiece is obtained.According to the method, the optimized cutting path of the to-be-cut workpiece is verified, the optimized verification cutting path of the to-be-cut workpiece is generated, and therefore the machining efficiency is remarkably improved while the machining precision is guaranteed; therefore, the reliability of the cutting process is comprehensively improved.

A testing method and apparatus for unmanned aerial vehicle (UAV) production includes the following steps: S1, Operating condition construction: controlling the power system of the UAV under test to operate to a preset target speed range; S2, Multi-dimensional data synchronous acquisition: generating a synchronous trigger signal based on the real-time speed signal of the power system; using the synchronous trigger signal to control a strobe light source to illuminate the rotating parts, and acquiring a freeze-frame visual image of the rotating parts during the illumination; simultaneously, acquiring acoustic signals during the operation of the power system; S3, Feature extraction: performing contour analysis on the freeze-frame visual image to extract visual feature values ​​reflecting physical deformation; performing spectral analysis on the acoustic signal to extract acoustic signature feature values ​​reflecting the mechanical operating state; S4, Fusion judgment: inputting the visual feature values ​​and acoustic signature feature values ​​into a preset multimodal fusion model to calculate the comprehensive health index of the power system, and determining whether the product is qualified based on the comprehensive health index.

This invention relates to the field of safety monitoring technology, and more particularly to an intelligent monitoring system for highway tunnel construction safety. The system includes a data acquisition module, a contour analysis module, a feature fusion module, and a data compensation module. By acquiring images of the tunnel surface, dust concentration within the tunnel, and water vapor humidity, the system divides the tunnel into several sub-image regions. The system determines the unevenness and texture complexity of each sub-image region, calculates region-sensitive feature values, and uses the tunnel dust concentration and water vapor humidity, combined with the region-sensitive feature values, to determine whether each sub-image region meets preset conditions. The system also calculates data missing characterization values ​​to determine the modeling anomaly tendency of each sub-image region. Based on the modeling anomaly tendency and the data missing characterization values, the system determines the data acquisition method for each sub-image region. This invention improves the accuracy and efficiency of model building through comprehensive analysis, data acquisition, and compensation of the tunnel environment, thereby ensuring construction safety.

The invention discloses a metal wire rope image feature segmentation method, system and device, and relates to the technical field of metal wire rope defect segmentation, and the method comprises the following steps: collecting a wire rope image; analyzing an edge threshold value between the two strands of wire ropes based on the wire rope contours; analyzing and extracting contour edge intersection points based on the wire rope contour; analyzing an initial contour line of the wire rope image, and analyzing an initial boundary between the two strands of wire ropes based on the initial contour line; calibrating the initial boundary to obtain a final boundary, and dividing the wire rope image into different stranded rope areas based on the final boundary; extracting region features of the stranded rope region, analyzing a defect region, and segmenting specific defect points in the defect region; the metal wire rope defect segmentation method is used for solving the problem that the existing metal wire rope defect segmentation technology cannot ensure whether defect segmentation is effective and accurate due to the fact that the description of image features is not detailed enough and the division of regions is not accurate enough.

This invention relates to the field of visual inspection of label bonding quality, and discloses an intelligent inspection system for label bonding quality, comprising: a polarization excitation illumination module for projecting a circularly polarized light field onto a highly reflective curved substrate; a multi-dimensional polarization imaging module for capturing spatially interwoven polarization signals; a geometric contour analysis module for analyzing the geometric contour information of the substrate; a polarization state compensation matrix generation module for determining the local incident angle and generating a compensation matrix according to Fresnel's law of reflection; a polarization distortion correction module for correcting polarization distortion and outputting a full Stokes polarization vector flow; an interface stress field feature extraction module for extracting phase delay features; and a defect location and judgment module for identifying bubble or wrinkle defects. This invention utilizes phase delay features to characterize the surface deformation of the transparent label bonding interface, and combines this with a polarization state compensation mechanism to remove geometric interference from the curved surface, thereby achieving the identification of hidden bonding defects under highly reflective environments.

This invention provides a method and system for detecting minute defects in proton exchange membranes (PEMs) in fuel cells. The method includes acquiring an original image of the PEM to be detected, preprocessing the original image to obtain a preprocessed grayscale image, the preprocessing including at least grayscale conversion and resolution normalization, extracting full-image phase consistency features from the preprocessed grayscale image to generate a phase consistency feature map, wherein the phase consistency feature map characterizes the structural abrupt changes of pixels in the grayscale image, and then performing multi-scale residual enhancement processing based on the preprocessed grayscale image and the phase consistency feature map to generate a defect-enhanced image. Finally, adaptive threshold segmentation and contour analysis are performed on the defect-enhanced image to locate the defect region in the original image. This method can locate the defect region in the original image of the PEM, thus overcoming the problems in the prior art.

The invention discloses a glue path defect detection method based on deep learning and contour analysis, and the method comprises the following steps: obtaining a semantic segmentation mask of a glue path, processing the semantic segmentation mask through a morphological refinement algorithm, obtaining a skeleton image of the glue path, and carrying out the geometric feature fitting, calculating an intersection of the fitting geometric feature and a corresponding semantic segmentation mask connected domain as an initial mark, and performing watershed segmentation to obtain a glue path segmentation mask; morphologically refining the segmentation mask of each glue path to obtain a skeleton image of the embodiment of the glue path, searching an end point and a branch point of the skeleton image by using hit-miss transform to obtain a main skeleton of the glue path, and recording pixel coordinates of the main skeleton from the end point according to an eight-neighborhood sequence; calculating the width, length and track accuracy of the glue path; and processing the glue path segmentation mask, the main skeleton coordinate, the width, the length and the track accuracy, judging whether an abnormal value is generated or not, and realizing classification, positioning and grade quantification of glue path defects.

The invention provides a method and a device for detecting a moving object. The method comprises the following steps of: performing difference operation on two adjacent frames of images by adopting an inter-frame difference method to obtain a frame difference image; carrying out binarization processing and morphological processing on the frame difference image to obtain a binarization image; performing contour analysis processing on the binarized image to obtain the area of a contour circumscribed rectangular region of the moving object in the binarized image; dividing a contour external rectangular area in the binarized image into large block motion areas or small block motion areas, performing space-to-channel compression processing on the image corresponding to each large block motion area, and performing image splicing processing on the images corresponding to all the small block motion areas to respectively obtain images to be detected; and performing target detection by using the target detection model to obtain the center point position coordinates and category information of the moving object. According to the moving object detection method and device provided by the invention, the calculation amount of the target detection model can be reduced, and the moving object in a complex scene can be rapidly and accurately detected.

The invention discloses a recognition and continuous casting judgment method based on a high-efficiency beam blank continuous casting machine. The recognition and continuous casting judgment method comprises the steps that after a high-resolution image of a beam blank in the continuous casting production process is obtained through mixed collection equipment, the high-resolution image is preprocessed; performing feature enhancement on the preprocessed image by adopting an image enhancement model based on deep learning; pixel-level segmentation is carried out on the enhanced image through a character segmentation algorithm combining contour analysis and projection features, and then segmented characters are identified; after the identification is completed, performing multi-dimensional verification and correction on an identification result by utilizing the constructed verification rule base; and the steel type of the special-shaped blank is determined according to the corrected recognition result, and the continuous casting conditions of different steel types of the special-shaped blank are judged. According to the method, the special-shaped blanks can be accurately identified, the mixed casting conditions of different steel types can be accurately judged, the stability and the high efficiency of continuous casting are guaranteed, the production efficiency and the product quality of a special-shaped blank continuous casting machine are improved, and the production cost is reduced.

The invention provides a three-dimensional high-speed vibration target clear image acquisition method and system and a medium, and the method comprises the steps: collecting a vibration target image based on a high-speed camera, carrying out the preprocessing of the vibration target image, and extracting a target contour; analyzing a target center point based on the target contour, and measuring three-dimensional position information of the target center point at different time nodes based on a laser displacement meter; analyzing plane vibration information and depth vibration information of the target based on the three-dimensional position information of the target center point at different time nodes; performing fusion processing on the plane vibration information and the depth vibration information to generate three-dimensional vibration state information of the target; adjusting a visual angle and a focal length of the high-speed camera based on the three-dimensional vibration state information of the target to obtain a clear image of the target; through dynamic zooming and angle adjustment of the high-speed camera, high-speed vibration tracking can be carried out on a complex-shape target under high magnification, and a clear image is obtained.

This invention relates to the field of image processing technology, and more specifically, to an intelligent contour analysis method for benzimidazolone pigment particles based on a graph search algorithm. The method includes: acquiring a grayscale image using an electron microscope and performing binarization segmentation; constructing a particle distance map based on Euclidean distance transformation; analyzing the curvature features of pixels in the particle distance map using the Hessian matrix to obtain the probability that a pixel in the particle distance map belongs to the core skeleton of the particle; extracting contour depression points based on the closed contour of the particle region; calculating the adhesion penalty intensity of each pixel in the particle distance map; accurately locating seed points by combining the skeleton probability and penalty intensity; and achieving precise cutting of adhered particles by constructing a graph model containing specific edge weights, using the seed points and background as constraints. This invention solves the problem of over-segmentation or under-segmentation caused by severe adhesion of pigment particles, improving the accuracy of contour recognition.

The application belongs to the field of display screen, and provides a light and dark adjusting method and system for mobile phone display screen, which comprises the following steps: pre-processing input LDR video frames by a fast guided filter to remove noise and artifacts generated by compression or sensors; expanding the brightness range of the input LDR video frames based on a global operator of mid-gray value mapping; while expanding the brightness range of the LDR video frames, iteratively removing false contours in the smooth transition area in the LDR video frames by a minimization algorithm based on iterative projection to a convex set; analyzing the LDR video frames without artifacts and their brightness channels to detect highlights and generate an expansion map, analyzing the expansion map and marking the highlight area, and fusing original brightness details by using a guided filter; and re-distributing the brightness of the LDR video frames after brightness expansion to the RGB color channels by using a Mantiuk formula; the application can realize good display effect when converting LDR to HDR.

The invention relates to the technical field of three-dimensional optical measurement, in particular to a terminal three-dimensional profile structured light measurement method, which comprises the following steps of: 1, setting and calibrating a system; 2, designing and projecting a light mode; step 3, image acquisition and preprocessing; 4, phase extraction and unwrapping are carried out; 5, three-dimensional point cloud generation and optimization are carried out, the three-dimensional point cloud of the terminal is generated through the triangulation principle based on the absolute phase diagram and system calibration parameters, then point cloud optimization is carried out, and point cloud optimization comprises outlier removal and surface smoothing; and step 6, contour analysis and output: three-dimensional contour features of the terminal are extracted based on the three-dimensional point cloud, the three-dimensional contour features comprise edge curvature, surface flatness and critical dimension, and a result is output in the form of a three-dimensional model and a dimension report. An optimized optical mode and self-adaptive frequency selection are designed for the micro size and complex surface of the terminal, and the spatial resolution and precision of measurement are improved.

The invention discloses a cursor control system based on monochromatic stick image recognition. The cursor control system comprises an image acquisition module used for acquiring continuous video frames containing monochromatic sticks in real time through a camera; the preprocessing module is used for converting the video frame from an RGB color space to an HSV color space and establishing a monochromatic hue threshold range model; the target detection module is used for carrying out noise reduction processing on the binarized image through morphological operation, and extracting a monochromatic stick-shaped object meeting the following geometrical characteristics by adopting a Canny edge detection and contour analysis algorithm; the coordinate mapping module is used for converting the detected geometric center coordinates of the monochromatic stick into screen cursor coordinates through a bilinear interpolation algorithm; the action recognition module is used for judging an operation instruction by calculating the displacement vector modulus length and the angular velocity of the single-color stick-shaped object between continuous frames; and the control module is used for mapping the geometric center position of the monochromatic stick-shaped object to a screen coordinate system and responding to the single-click signal to execute a click operation.

The invention discloses an image preprocessing method for power supply system file entry, and the method comprises the steps: separating a foreground and a background in a photo based on a semantic segmentation network, removing watermarks and stains through morphological operation, and reserving a target region, thereby obtaining a segmented target region; carrying out feature extraction on the segmented target area, extracting image features by adopting BIC, and comparing the image features with a pre-established photo type template through a feature matching algorithm to determine a key information position; according to the determined key information position, adopting an adaptive threshold segmentation algorithm to extract a target area, and accurately positioning an information boundary through edge detection and contour analysis to obtain the extracted target area; and storing the normalized photo and the extracted information in an archive database, and establishing an index and an association relationship for subsequent image retrieval and analysis.

The present application relates to the field of intelligent image processing and computer vision, and particularly relates to a badminton match video line violation intelligent visual detection method, comprising: constructing a badminton match image dataset containing foot contour and field key point annotation; designing and training a DFSNet foot segmentation network, which introduces an attention mechanism in the decoder part to realize accurate segmentation of left and right foot contours; training a key point detection model based on the annotated key points, and generating a bottom line, a service line and a center line binary mask that conforms to the actual white line in the image through secondary refinement; finally, performing pixel-level overlap detection on the foot contour output by the DFSNet and the refined field line mask, and if there are overlapping pixels, it is determined that the foot has violated the line. The present application takes foot contour analysis as the core, combines deep learning feature extraction with geometric prior optimization, realizes automatic and accurate detection of badminton line violation, and can be widely applied to sports event auxiliary judgment and sports analysis.

This invention discloses a visual detection method for small targets on the surface of an air conditioner outdoor unit based on mask-guided perspective correction. The method includes: 1. Acquiring images of the air conditioner outdoor unit using a visual inspection system, segmenting the unit casing using an improved YOLOv11 instance segmentation model to generate a binary mask; 2. Performing contour analysis on the binary mask, extracting the four corner vertices of the connected regions as source point coordinates; 3. Solving the perspective transformation matrix by combining the prior physical dimensions of the target, correcting the tilted view to a standard front view to eliminate geometric distortion; 4. Extracting candidate regions based on a preset configuration file, and using a template matching algorithm to determine the assembly state of small targets such as screws. This invention eliminates perspective distortion caused by tilted camera shooting through mask-guided perspective correction, significantly improving the detection accuracy of small targets on the surface of the air conditioner outdoor unit, and enhancing detection efficiency and accuracy.

The invention relates to the technical field of image processing, and provides an auxiliary film reading analysis system in an MRI (Magnetic Resonance Imaging) image examination process, which comprises the following steps: acquiring a plurality of kidney MRI images of a patient; performing edge detection and contour analysis on the kidney MRI image to obtain a plurality of connected domains; acquiring a banding factor of each connected domain; obtaining an offset artifact possibility of each connected domain, and screening to obtain a plurality of suspected chemical shift artifact regions; acquiring a plurality of kidney regions in the kidney MRI image; the kidney offset distance of each suspected chemical shift artifact area is obtained; obtaining the final artifact possibility of each suspected chemical shift artifact area, and screening to obtain a plurality of chemical shift artifact areas; and marking a chemical shift artifact area in each kidney MRI image, and assisting in reading and analyzing. The invention aims to solve the problem that chemical shift artifacts in MRI images affect film reading analysis.

This disclosure provides a method for calculating rock mass quality indicators based on borehole images, relating to the field of engineering geological exploration. The method includes: using a trained structural surface recognition model to identify structural surfaces and fracture zones in a target borehole image; the structural surface recognition model is configured to identify structural surfaces and fracture zones in the target borehole image based on the input target borehole image; the structural surface recognition model is trained using a training sample set of structural surfaces and fracture zones expanded by data augmentation and geometric transformation; based on the depth markers in the target borehole image, the pixel resolution is calculated using edge detection and contour analysis algorithms; based on the identification results of structural surfaces and fracture zones and the pixel resolution, the distance between adjacent structural surfaces and the length of fracture zones are calculated; based on the distance between adjacent structural surfaces and the length of fracture zones, the proportion of short rock segments with lengths less than a preset threshold and the proportion of fracture zones are statistically analyzed, and the rock quality indicator RQD is calculated based on the subtraction method.