A feature extraction method for nearshore wave breaking process based on time series video images

Abstract

The present invention provides a method for extracting features of the nearshore wave breaking process based on time series video images; wherein, the method comprises: setting at least one pixel sampling area in a plane geographic coordinate system, collecting time series video images of ocean nearshore waves, quickly converting them into plane geographic coordinate images through a coordinate model, and then stacking cross-shore pixel values ​​of several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mining the time-varying signal of the wave propagating toward the shore, combining the geometric relationship between the camera angle of view and the plane projection of the wave breaking, and calculating key wave breaking features such as the wave breaking point position, wave breaking water depth, and wave breaking height; the method can continuously monitor the nearshore wave breaking features efficiently, automatically, and stably, effectively making up for the shortcomings of traditional monitoring and analysis methods, and providing strong technical support for the refined research and management of nearshore beach dynamic landforms.

Description

Technical Field

[0001] The present invention relates to a method for extracting features of a nearshore wave breaking process based on time series video images. Background Art

[0002] The nearshore area is a buffer zone for the interaction between the ocean and the land, and is one of the most active natural areas on the earth's surface. Nearshore waves are the most active driving force behind the evolution of nearshore areas, especially the evolution of sandy coasts. Nearshore waves specifically refer to waves from the open sea that are transmitted to the vicinity of the coast and have their moving properties changed by the terrain. The crest of nearshore waves is steep in front and flat in the back. The wave surface becomes increasingly asymmetric as the water depth becomes shallower until it rolls over and breaks. The breaking of the waves will cause the water level near the shore at the breaking point to rise and the water level on the far sea to drop. During the propagation process, nearshore waves will carry sediment and move synchronously, and may encounter obstacles to cause diffraction and reflection, thereby shaping the nearshore topography.

[0003] In the ocean nearshore under the influence of nearshore waves, harbor construction, coastal protection, nearshore shipping, marine aquaculture, etc. may be constructed, so the refined management of the analysis and research of nearshore waves is very important; for example, when designing breakwaters, the theory of nearshore waves must be applied to calculate the various wave heights that may occur; if the wave height exceeds the breakwater, the seawater will directly cross the breakwater and carry sediment into the port located at the breakwater, causing siltation in the port, and will also disrupt the stability of the water surface inside the port, affecting the safe anchoring and loading and unloading operations of ships in the port; for example, in coastal protection and harbor construction, it is necessary to understand the movement of sediment in the sea, so as to choose a location where the nearshore waves are small and not easy to carry sediment.

[0004] However, traditional nearshore wave monitoring methods such as video monitoring, buoy observation, and manual observation have problems such as lack of monitoring means, low frequency of data acquisition, insufficient accuracy and automation. For example, video monitoring is a video-based nearshore wave detection system that accesses the video signal of the nearshore monitoring station and uses a video capture card to obtain video information in real time and save it locally. It is not a real-time video file, and the video information occupies a large storage space and cannot meet the requirements of high frequency, continuity, high resolution, low cost, and real-time at the same time. Buoy observation measures wave parameters by deploying buoys at sea. If the harbor has complex terrain, accurate wave measurement requires high-density deployment, and the operation and maintenance costs are high. Manual observation relies on experienced forecasters to estimate the wave height by visual inspection. This method has high personnel requirements and the prediction frequency and accuracy are difficult to guarantee.

[0005] Therefore, the present invention provides a method for extracting the characteristics of the nearshore wave breaking process from nonlinear, complex, and random nearshore waves, which can continuously monitor the nearshore wave breaking characteristics efficiently, automatically, and stably; effectively make up for the shortcomings of traditional monitoring and analysis methods, and provide strong technical support for nearshore dynamic landform research and refined management. Summary of the Invention

[0006] The present invention provides a method for extracting features of nearshore wave breaking processes based on time series video images, which can effectively solve the above problems.

[0007] The present invention is achieved in that:

[0008] A feature extraction method for nearshore wave breaking process based on time series video images is proposed. Video images of ocean nearshore waves are collected and the coordinates of each frame in the video images are converted into planar geographic coordinates to obtain a planar geographic coordinate system image.

[0009] Setting at least one pixel sampling area in a planar geographic coordinate system;

[0010] For each frame of the image sequence in the plane geographic coordinate system, based on the pixel sampling area, the cross-shore pixel value of the corresponding area is extracted from the image;

[0011] Stack the cross-bank pixel values ​​of all images and output a sequence diagram of the original cross-bank pixel value and time relationship;

[0012] Performing a time domain sliding average filter on the original cross-shore pixel value and time relationship sequence diagram within the wave period [T-2 seconds; T+2 seconds], and outputting a cross-shore pixel value and time relationship sequence diagram;

[0013] The white pixel area based on the cross-shore pixel value and time relationship sequence diagram is used as the base point for extracting the characteristics of the nearshore wave breaking process;

[0014] Among them, the horizontal axis of the cross-shore pixel value and time relationship sequence diagram is the cross-shore distance of the nearshore wave, and the vertical axis is time; T is the wave period; the pixel sampling area is the pixel area along the direction perpendicular to the coast or the wave line direction perpendicular to the nearshore wave.

[0015] Furthermore, the wave period is obtained by the following steps: collecting the cross-shore pixel intensity in the original cross-shore pixel value and time relationship sequence diagram;

[0016] Performing mean processing on the cross-bank pixel intensities to obtain a de-meaned cross-bank pixel value and time relationship sequence diagram;

[0017] Perform zero-crossing detection on the cross-bank pixel value and time relationship series diagram after de-averaging to obtain several zero-crossing points;

[0018] The time intervals between adjacent zero crossing points are calculated to obtain the wave period.

[0019] As one of the extraction steps of the present invention, based on the white pixel area of ​​the cross-shore pixel value and time relationship sequence diagram, a threshold segmentation method is used to obtain a pixel image with the initial breaking wave threshold as the dividing point, wherein the pixel point where the initial breaking wave threshold is located is the location of the breaking wave point.

[0020] Furthermore, the specific steps of the threshold segmentation method are as follows:

[0021] collecting cross-shore pixel intensities in the cross-shore pixel value and time relationship sequence diagram to determine an initial threshold value of a breaking wave;

[0022] Comparing the grayscale value of each pixel in the time series cross-shore pixel image with the initial breaking wave threshold image by image, generating a pixel image divided into a first pixel area and a second pixel area with the initial breaking wave threshold as a dividing point;

[0023] The pixel points of the first pixel area are lower than the breaking wave initial threshold, and the pixel points of the second pixel area are higher than the breaking wave initial threshold;

[0024] Alternatively, the pixel points of the second pixel area are lower than the breaking wave initial threshold, and the pixel points of the first pixel area are higher than the breaking wave initial threshold.

[0025] As one of the extraction steps of the present invention, the specific steps of obtaining the breaking wave height include:

[0026] After determining the pixel point where the wave breaking point is located, the vertical axis data of the pixel point is obtained as the wave breaking time based on the cross-shore pixel value and time relationship sequence diagram;

[0027] The horizontal projection length L of the breaking wave at the breaking wave point position is obtained. L is defined as the width at half the peak value of the wave pixel, which can be further converted into meters according to the pixel resolution.

[0028] Correct the horizontal projection length L of the breaking wave by using formula 1;

[0029] The wave height of the wave breaking point is calculated using formula 2;

[0030]

[0031] H b =(L-Cor)tanβ, formula (2)

[0032] Where L is the horizontal projection length of the extracted breaking wave; a b is the inclination angle of the wave front; Cor is the calculated correction length; β is the known camera observation angle; Hb is the breaking wave height.

[0033] As one of the extraction steps of the present invention, the extraction of the wave-breaking water depth is based on the water depth data of the nearshore ocean in the study area measured in advance or downloaded from the database.

[0034] As a further improvement of the present invention, the specific steps of obtaining a planar geographic coordinate system image are as follows:

[0035] Multiple video acquisition devices are set up on a beach near the ocean shore or a high point near the ocean shore to obtain continuous time series video images;

[0036] The coordinates of the continuous time series video images are transformed by the following coordinate model to obtain the plane geographic coordinate system image;

[0037]

[0038] Where, is a point in the plane coordinate system, and the image distortion coordinates that match it are (c, r); (u, v) represents the undistorted coordinates to be solved, and d 2 =u 2 +v 2 ; Represents the distortion coefficient; s represents the size of the pixel; (o c ,o r ) coordinates of the principal point; is the position of the camera in the planar world coordinate system; is a rotation matrix defined by the Euler angles (φ, σ, τ).

[0039] A monitoring device based on time series video images, comprising:

[0040] at least one processor, and

[0041] a memory communicatively coupled to the at least one processor, wherein:

[0042] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform a method for extracting features of a nearshore wave breaking process based on time series video images.

[0043] A readable storage medium stores a computer program, which, when executed by a processor, implements a method for extracting features of a nearshore wave breaking process based on time-series video images.

[0044] The beneficial effects of the present invention are as follows: the present invention collects time series video images of ocean nearshore waves, quickly converts them into plane geographic coordinate images through a coordinate model, and then stacks cross-shore pixel values ​​for several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mines the time-varying signal of wave propagation toward the shore, combines the geometric relationship between the camera viewing angle and the plane projection of the wave breaking, calculates key wave breaking characteristics such as the wave breaking point position, wave breaking depth, and wave breaking height, and can continuously monitor the nearshore wave breaking characteristics efficiently, automatically, and stably; effectively makes up for the shortcomings of traditional monitoring and analysis methods, and provides strong technical support for the study of nearshore beach dynamic landforms and refined management. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 It is a schematic diagram of the conversion of video images to planar geographic coordinate images provided by an embodiment of the method for extracting features of nearshore wave breaking processes based on time series video images of the present invention.

[0047] Figure 2 This is a schematic diagram of cross-shore pixel stack acquisition provided by an embodiment of the method for extracting features of nearshore wave breaking processes based on time series video images of the present invention.

[0048] Figure 3 This is a schematic diagram of wave breaking point extraction provided by an embodiment of a method for extracting features of a nearshore wave breaking process based on time series video images of the present invention.

[0049] Figure 4 The present invention provides a schematic diagram of extracting the horizontal projection length L of a breaking wave according to an embodiment of a method for extracting features of a nearshore wave breaking process based on time series video images.

[0050] Figure 5 This is a schematic diagram of the principle of calculating breaking wave height according to an embodiment of the method for extracting features of nearshore wave breaking process based on time series video images of the present invention.

[0051] Figure 6 It is a flow chart of an embodiment of a method for extracting features of a nearshore wave breaking process based on time series video images according to the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention for which protection is sought, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0054] Example 1

[0055] See also Figures 1 to 6 This embodiment provides a specific implementation method for extracting features of nearshore wave breaking processes based on time series video images, including:

[0056] Collect video images of ocean nearshore waves, convert the coordinates of each frame of the video image into plane geographic coordinates, and obtain a plane geographic coordinate system image;

[0057] Setting at least one pixel sampling area in a planar geographic coordinate system;

[0058] For each frame of the image sequence in the plane geographic coordinate system, based on the pixel sampling area, the cross-shore pixel value of the corresponding area is extracted from the image;

[0059] The cross-shore pixel values ​​of all images are stacked to output a time series diagram of the original cross-shore pixel values. This cross-shore pixel value time series diagram can reflect the time series information of the wave propagation and breaking process of the representative profile. The representative profile here refers to the sampling array, that is, the sampling array refers to the geographical location set in the field, and also refers to the elevation value of the nearshore wave profile at the geographical location;

[0060] Performing a time domain sliding average filter on the original cross-shore pixel value and time relationship sequence diagram within the wave period [T-2 seconds; T+2 seconds], and outputting a cross-shore pixel value and time relationship sequence diagram;

[0061] The white pixel area based on the cross-shore pixel value and time relationship sequence diagram is used as the base point for extracting the features of the nearshore wave breaking process.

[0062] Among them, the specific steps to obtain the plane geographic coordinate system image are:

[0063] Multiple video acquisition devices are set up on a beach near the ocean shore or a high point near the ocean shore to obtain continuous time series video images;

[0064] The coordinates of the continuous time series video images are transformed by the following coordinate model to obtain the plane geographic coordinate system image;

[0065]

[0066]

[0067] Where, is a point in the plane coordinate system, and the image distortion coordinates that match it are (c, r); (u, v) represents the undistorted coordinates to be solved, and d 2 =u 2 +v 2 ; Represents the distortion coefficient; s represents the size of the pixel; (o c ,o r ) coordinates of the principal point; is the position of the camera in the plane world coordinate system; ( is a rotation matrix defined by the Euler angles (φ, σ, τ).

[0068] Compared with the traditional "coordinate transformation" model, the coordinate transformation model in this embodiment only needs to consider 8 unknown variables that need to be calibrated: x c 、y c 、z c , φ, σ, τ, s; the calibration workload is greatly reduced, and the "coordinate conversion" model of traditional video images is simplified; while ensuring the accuracy of coordinate conversion, the efficiency of geographic coordinate conversion is improved, thereby better showing the characteristics of the nearshore wave propagation and breaking process; geographic coordinate images based on time series are obtained. In other words, the present invention is based on the "coordinate conversion" model, which further provides strong technical support for realizing efficient, automatic and stable continuous monitoring of nearshore wave breaking characteristics.

[0069] In some embodiments, at an altitude of more than 20 meters, video images of nearshore waves are collected from multiple perspectives. In the above technical solution, in order to ensure that the video camera has a sufficient observation field of view, the interference of seawater reflection on light caused by the camera is reduced. In addition, the video acquisition device includes but is not limited to a camera and an aerial camera, as long as a clear video file of the nearshore wave propagation can be obtained.

[0070] In other embodiments, the present invention can also perform distortion correction on each frame of image captured in the captured video based on the distortion coefficient k of the camera device itself, thereby improving the clarity of the video image and making it easier to obtain the position of the breaking point.

[0071] In some embodiments, the video acquisition device at each viewing angle acquires a plurality of frames of images at a preset frequency and a preset time, that is, video images are acquired at a preset frequency within a predetermined time period, and the video images within the set time are extracted as characteristic images of ocean nearshore wave breaking waves; for example, video images of the ocean nearshore of the study area are acquired at a time resolution of 2 Hz or above within 1 hour, and the video images of the first ten minutes of the hour are extracted for coordinate conversion, thereby reducing the influence of the ocean nearshore tidal phenomenon on the breaking wave feature extraction, better tracking the propagation process of the nearshore waves, and capturing the nearshore wave breaking process.

[0072] In some embodiments, the present invention converts the ocean nearshore wave image from a single perspective into a planar geographic coordinate system image through a coordinate conversion model, and directly proceeds to the next step without fusing multi-angle video images, eliminating many steps and rapidly improving the speed of extracting breaking wave features.

[0073] Among them, the pixel sampling area described in the present invention is a pixel area with a fixed position along the direction perpendicular to the coast or the wave line direction perpendicular to the nearshore waves. According to the principle of wave refraction, the waves of the nearshore ocean waves tend to be perpendicular to the isobaths and the coastline when they propagate into the shallow water area. In special weather conditions, such as typhoons, hurricanes, and strong winds, the wave lines of the nearshore ocean waves are obvious and are less affected by the tides. The fixed pixel sampling area is divided according to the wave line direction perpendicular to the nearshore ocean waves for adaptive adjustment.

[0074] In this embodiment, the wave period is obtained by the following steps: collecting cross-shore pixel intensities in the original cross-shore pixel value and time relationship sequence diagram; performing mean processing on the cross-shore pixel intensities to obtain a cross-shore pixel value and time relationship sequence diagram after de-averaging, specifically, calculating the average value of all cross-shore pixel values ​​in the cross-shore pixel value and time relationship sequence diagram, and then subtracting the average value from each cross-shore pixel value in the cross-shore pixel value and time relationship sequence diagram, thereby eliminating the long-term trend in the data and making the periodic change of the wave more obvious;

[0075] Zero-crossing detection is performed on the de-averaged cross-bank pixel value and time relationship series diagram to obtain several zero-crossing points. A zero-crossing point is a point where the pixel intensity value changes from positive to negative or from negative to positive. Each transition from a positive value to a negative value or from a negative value to a positive value marks the beginning or end of a fluctuation cycle.

[0076] The time intervals between adjacent zero crossing points are calculated to obtain the wave period.

[0077] In the above technical solution, the core of the wave period is to count the number of times the signal passes through the zero point within a period, so as to analyze the periodic characteristics of the signal.

[0078] As one of the extraction steps of the present invention, a threshold segmentation method is used to obtain a pixel image with the initial breaking wave threshold as the demarcation point based on the white pixel area of ​​the cross-shore pixel value and time relationship sequence diagram. The pixel point where the initial breaking wave threshold is located is the location of the breaking point. The principle of this method is based on the sudden change in the optical properties of the wave at the breaking point. Specifically, in the offshore area of ​​the breaking point, the main imaging mechanism corresponds to surface reflection, which is characterized by a narrow dynamic range of optical pixel intensity. When the wave breaks, the turbulent air-water mixture becomes the source of diffuse reflection, and the pixel intensity of the breaking point will jump significantly. Therefore, the sudden change in optical pixel intensity is associated with the onset of wave breaking and is further related to the wave height of each wave.

[0079] Furthermore, the specific steps of the threshold segmentation method are as follows:

[0080] The cross-shore pixel intensity in the cross-shore pixel value and time relationship sequence diagram is collected to determine the initial threshold of the breaking wave. The optimal initial threshold is I=40, because the intensity value of the breaking wave is I>80, which is significantly higher than that of the non-breaking wave. The intensity value of the non-breaking wave is I between 0 and 10. Therefore, the determination of the wave profile is highly robust to the threshold selection. Finally, the threshold value I=40 is adopted.

[0081] Normalizing the intensity of each cross-shore pixel in the time series cross-shore pixel image to a range of 0-255, and comparing the intensity with the initial breaking wave threshold image by image, to generate a pixel image divided into a first pixel area and a second pixel area with the initial breaking wave threshold as a dividing point;

[0082] The pixel points of the first pixel area are lower than the breaking wave initial threshold, and the pixel points of the second pixel area are higher than the breaking wave initial threshold;

[0083] Alternatively, the pixel points of the second pixel area are lower than the breaking wave initial threshold, and the pixel points of the first pixel area are higher than the breaking wave initial threshold.

[0084] In the above technical solution, the first pixel area or the second pixel area exceeding the initial threshold of the breaking wave is associated with a single breaking wave event through neighboring grouping; and the breaking point position and occurrence time of each breaking wave are determined by the spatiotemporal coordinates of the pixel closest to the sea in each breaking event group.

[0085] In this embodiment, the threshold segmentation method divides nonlinear, complex, and random ocean waves into simple images, directly obtaining the location of the wave breaking point, greatly compressing the data volume, simplifying the analysis and processing steps, and having the advantages of small computational complexity, stable performance, good segmentation effect, and high efficiency. At the same time, for long-term monitoring of ocean nearshore wave video images, the shorter the time spent on the entire breaking wave extraction, the faster the feedback speed, which is more beneficial for the study of nearshore beach dynamic landforms and refined management.

[0086] In the above technical solution, the feature threshold needs to be adjusted according to the actual situation due to the limitations of the altitude of the multi-angle video acquisition device, the intensity of the sun's direct radiation on the earth at different longitudes and latitudes in spring, summer, autumn and winter, and the reflection intensity of the light from the nearshore seawater. In other words:

[0087] The higher the camera's altitude, the more intuitive and distinct the lines of the waves surging near the shore are, making it easier to identify the breaking point. Conversely, the lower the camera's altitude, the wider the lines of the waves surging near the shore are, making it more difficult to identify the breaking point.

[0088] The intensity of the sun's direct radiation on the Earth's different longitudes and latitudes throughout the year, spring, summer, autumn, and winter, is strongest in summer and weakest in winter. The stronger the light, the stronger the reflected light from the sea surface near the coast, and the higher the characteristic threshold of the pixel at the breaking wave position;

[0089] The reflection intensity of the seawater near the coast of the ocean in 24 hours. The stronger the reflected light from the sea surface near the coast, the stronger the light at the time when the sun shines vertically on the sea surface near the coast, and the higher the characteristic threshold of the pixel at the breaking wave position; conversely, at night time, the sea surface near the coast is weakest, and the characteristic threshold of the pixel at the breaking wave position is lower.

[0090] Therefore, the initial threshold of breaking waves needs to be adjusted according to the actual situation in view of the differences in lighting conditions and environment in each ocean nearshore observation area. The optimal initial threshold is I = 40.

[0091] Among them, the horizontal axis of the cross-shore pixel value and time relationship sequence diagram is the cross-shore distance of the nearshore waves, and the vertical axis is time. The tidal value range of the nearshore ocean in the study area at this time is the tidal value range. The cross-shore distance is a value covering the entire tidal value range. The vertical axis is the acquisition time of each frame of video image. The data acquisition is intuitive and does not require auxiliary processing of time recording software, which instantly improves the speed of feature extraction of the nearshore wave breaking process.

[0092] As one of the extraction steps of the present invention, the specific steps of obtaining the wave height of the breaking wave include:

[0093] After determining the pixel point where the wave breaking point is located, the vertical axis data of the pixel point is obtained as the wave breaking time based on the cross-shore pixel value and time relationship sequence diagram;

[0094] The horizontal projection length L of the breaking wave at the breaking wave point is obtained. L is defined as the width at half the peak value of the wave pixel, which can be further converted into meters according to the pixel resolution.

[0095] Correct the horizontal projection length L of the breaking wave by using formula 1;

[0096] The wave height of the wave breaking point is calculated using formula 2;

[0097]

[0098] H b =(L-Cor)tanβ, formula (2)

[0099] Where L is the horizontal projection length of the extracted breaking wave; a b is the inclination angle of the wave front; Cor is the calculated correction length; β is the known camera observation angle; H b is the breaking wave height.

[0100] In this embodiment, the breaking wave height of the nearshore waves is calculated, so that the different breaking wave heights of the nearshore waves contain different energies. The higher the wave height, the greater the energy. Therefore, by guiding the flow direction of the nearshore waves, the coastal landforms can be artificially shaped or the evolution process of the coast can be mastered, the changing trend of the coast can be predicted, and the rational development and utilization of natural resources such as port construction, reclamation, aquaculture, tourism and coastal energy can be realized, thereby achieving refined management of the nearshore dynamic landforms.

[0101] As one of the extraction steps of the present invention, the wave-breaking water depth is measured in advance or the water depth data of the nearshore ocean in the study area is downloaded from a database;

[0102] Among them, the method of measuring the water depth data of the ocean shore in advance includes: an unmanned ship uses a single-beam echo sounder, a multi-beam echo sounder and other equipment to transmit a beam of sound waves or multiple beams of sound waves. The sound waves are reflected back after contacting the bottom of the water. By measuring the time interval from the emission to the reception of the sound waves, and then based on the propagation speed of the sound waves in the water, the water depth can be calculated; these data can be spatially positioned according to the positioning information of the unmanned ship, such as through GPS, and finally a water depth profile in the direction of the survey line can be drawn; or, through remote sensing images, the reflectivity of the water body is estimated by optical sensor data, and the water depth of the shallow water area is obtained; LiDAR measurement method: The LiDAR transmitter transmits to the water surface and the bottom of the water. When the laser pulse encounters the water surface and the bottom of the water, it will produce reflections; by measuring the round-trip time of the laser pulse from emission to reception, combined with the propagation speed of light in water, the water depth can be calculated; and so on; the method of measuring the water depth data of the ocean shore in advance is mainly used for development that is not recorded in the database or some unfamiliar ocean shores, and the data is more realistic.

[0103] Among them, the water depth data of the nearshore ocean in the study area is downloaded from the database, which specifically includes: first, opening the global coastline and water depth database and extracting the coastline and water depth data of the study area; second, if there are electronic nautical charts available in the study area, the water depth data is directly extracted from the electronic nautical charts, etc.; by downloading the water depth data of the nearshore ocean in the study area from the database, there is no need for manual measurement, which reduces a lot of preliminary work and directly improves the efficiency of feature extraction of the nearshore wave breaking process.

[0104] In summary, compared with traditional means that cannot simultaneously meet the requirements of high frequency, continuity, high resolution, low cost and real-time, the present invention collects time series video images of ocean nearshore waves, quickly converts them into plane geographic coordinate images through a coordinate model, and then stacks cross-shore pixel values ​​for several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mines the time-varying signal of wave propagation toward the shore, combines the geometric relationship between the camera perspective and the plane projection of the wave breaking, calculates key wave breaking characteristics such as the wave breaking point position, wave breaking depth, and wave breaking height, and can continuously monitor the nearshore wave breaking characteristics efficiently, automatically and stably; effectively makes up for the shortcomings of traditional monitoring and analysis methods, and provides strong technical support for the study of nearshore beach dynamic landforms and refined management.

[0105] Example 2

[0106] The difference between Example 1 and Example 2 lies in the different steps for obtaining a plane geographic coordinate system image. The present invention first converts the ocean nearshore wave image from a single perspective through a coordinate conversion model to obtain a plane geographic coordinate system image. Based on the clarity of the ocean nearshore wave features in the plane geographic coordinate system image, one or more plane geographic coordinate system images from different perspectives are fused to improve the clarity of the ocean nearshore wave features. The clearer the ocean nearshore wave features are, the smaller the error in the subsequent extraction of breaking wave features will be.

[0107] Among them, the fusion of one or more planar geographic coordinate system images from different perspectives adopts multi-perspective fusion technology. Multi-perspective fusion technology is based on the fact that observations of the same object or scene from different perspectives will provide complementary information; by collecting these information obtained from different perspectives, using algorithms and models, they are fused together to eliminate the limitations of a single perspective, thereby presenting the characteristics and information of the object or scene more completely.

[0108] It should be noted that the implementation principle and technical effects of this embodiment are the same as those of the first embodiment. For the sake of brief description, for matters not mentioned in this embodiment, reference may be made to the corresponding contents in the first embodiment.

[0109] Example 3

[0110] A monitoring device based on time series video images, comprising:

[0111] at least one processor, and

[0112] a memory communicatively coupled to the at least one processor, wherein:

[0113] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned method for extracting features of nearshore wave breaking processes based on time series video images.

[0114] In this embodiment, in order to better run and process the method, the above method is stored in a memory and a processor is used to execute the stored method. It should be noted that the principle and effect of each step have been described above and will not be further described here.

[0115] Example 4

[0116] A readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for extracting features of nearshore wave breaking processes based on time series video images.

[0117] In this embodiment, in order to better run and use the method, the above method is stored in a computer-readable storage medium and implemented using a processor. It should be noted that the principle and effect of each step have been described above and will not be further described here.

[0118] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for extracting features of nearshore wave breaking processes based on time series video images, characterized in that: include: Collect video images of ocean nearshore waves, convert the coordinates of each frame of the video image into plane geographic coordinates, and obtain a plane geographic coordinate system image; Setting at least one pixel sampling area in a planar geographic coordinate system; For each frame of the image sequence in the plane geographic coordinate system, based on the pixel sampling area, the cross-shore pixel value of the corresponding area is extracted from the image; Stack the cross-bank pixel values ​​of all images and output a sequence diagram of the original cross-bank pixel value and time relationship; Performing a time domain sliding average filter on the original cross-shore pixel value and time relationship sequence diagram within the wave period [T-2 seconds; T+2 seconds], and outputting a cross-shore pixel value and time relationship sequence diagram; The white pixel area based on the cross-shore pixel value and time relationship sequence diagram is used as the base point for extracting the characteristics of the nearshore wave breaking process; The horizontal axis of the cross-shore pixel value and time relationship sequence diagram is the cross-shore distance of the nearshore wave, and the vertical axis is time; T is the wave period; the pixel sampling area is the pixel area along the direction perpendicular to the coast or the wave line direction perpendicular to the nearshore wave; The steps for obtaining the wave period are as follows: Collect the cross-bank pixel intensity in the original cross-bank pixel value and time relationship sequence diagram; Performing mean processing on the cross-bank pixel intensities to obtain a de-meaned cross-bank pixel value and time relationship sequence diagram; Perform zero-crossing detection on the cross-bank pixel value and time relationship series diagram after de-averaging to obtain several zero-crossing points; The time intervals between adjacent zero crossing points are calculated to obtain the wave period.

2. The method for extracting features of nearshore wave breaking process according to claim 1, characterized in that: Based on the white pixel area of ​​the cross-shore pixel value and time relationship sequence diagram, a threshold segmentation method is used to obtain a pixel image with the initial breaking wave threshold as the dividing point, wherein the pixel point where the initial breaking wave threshold is located is the location of the breaking wave point.

3. The method for extracting features of nearshore wave breaking process according to claim 2, characterized in that: The specific steps of the threshold segmentation method are as follows: collecting cross-shore pixel intensities in the cross-shore pixel value and time relationship sequence diagram to determine an initial threshold value of a breaking wave; Comparing the grayscale value of each pixel in the time series cross-shore pixel image with the initial breaking wave threshold image by image, generating a pixel image divided into a first pixel area and a second pixel area with the initial breaking wave threshold as a dividing point; The pixel points of the first pixel area are lower than the breaking wave initial threshold, and the pixel points of the second pixel area are higher than the breaking wave initial threshold; Alternatively, the pixel points of the second pixel area are lower than the breaking wave initial threshold, and the pixel points of the first pixel area are higher than the breaking wave initial threshold.

4. The method for extracting features of nearshore wave breaking process according to claim 3, wherein: The specific steps to obtain the breaking wave height include; After determining the pixel point where the wave breaking point is located, the vertical axis data of the pixel point is obtained as the wave breaking time based on the cross-shore pixel value and time relationship sequence diagram; Get the horizontal projection length of the breaking wave at the breaking wave point position ; Correct the horizontal projection length of the breaking wave by the formula ; The breaking wave height is obtained by calculation using the formula.

5. The method for extracting features of nearshore wave breaking process according to claim 1, wherein: The wave-breaking water depth is the water depth data of the coastal area of ​​the study area measured in advance or downloaded from the database.

6. The method for extracting features of nearshore wave breaking process according to claim 1, characterized in that: Specific steps to obtain a planar geographic coordinate system image: Multiple video acquisition devices are set up on a beach near the ocean shore or a high point near the ocean shore to obtain continuous time series video images; The coordinate model is used to transform the continuous time series video images into plane geographic coordinate system images.

7. The method for extracting features of nearshore wave breaking process according to claim 6, characterized in that: The specific steps of obtaining the plane geographic coordinate system image also include: performing coordinate transformation on the continuous time series video images based on the coordinate model to obtain the plane geographic coordinate system image; Fuse two or more planar geographic coordinate system images with different perspectives to obtain a new planar geographic coordinate system image.

8. A monitoring device based on time series video images, characterized in that: include: at least one processor, and a memory communicatively coupled to the at least one processor, wherein: The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

9. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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