Ship auxiliary correction system and operation method thereof

Abstract

The present invention aims to provide a ship auxiliary correction system and its operation method, comprising a receiver, a storage, at least one sensor, a processor and a display, wherein the processor is connected to the receiver, the storage and the at least one sensor; and the display is connected to the processor. The ship auxiliary correction system determines the distance parameter of the obstacle by running a preset machine-readable grid, and confirms and corrects the distance parameter to normal according to the sensor data of the sensor, so that the distance measurement of the obstacle can be completed without using optical radar (LiDAR) or when the water is undulating.

Description

Technical Field

[0001] The present invention relates to an auxiliary correction system and an operating method thereof, and in particular to an auxiliary correction system for ships and an operating method thereof. Background Art

[0002] Route planning is a fundamental problem in the control of unmanned water vehicles. The central computer fully specifies the route path that the unmanned water vehicle should follow from the beginning of navigation to the destination. The route path must usually not collide with any obstacles in the navigation environment; or reduce the possibility of collision as much as possible.

[0003] It is known that LiDAR technology is widely used in distance detection. Unmanned water vehicles usually use optical radar (LiDAR) to detect channel scenes. However, when using LiDAR in aquatic environments, it is often affected by interference factors on the water surface (such as light reflection, undulation or water vapor on the water surface), which reduces its measurement accuracy and practicality. Therefore, in practical applications, it usually needs to be supplemented by other measurement methods to be perfect.

[0004] Compared with lidar technology, image measurement technology is relatively less affected by the environment. However, due to the fluctuations of the water surface, if there is a sudden large height difference in the water surface, the obstacle will swing up and down due to the height difference. At this time, it will cause serious errors in image measurement, affecting the navigation safety of the unmanned water vehicle; or, if the position or shape characteristics of the obstacle may change over time (such as large floating objects may move based on the direction of the water flow). Therefore, the challenge of route planning is that the processing speed of image measurement must be real-time and available for users to monitor in a timely manner, so that when the unmanned water vehicle confirms the route path, the user can monitor it synchronously according to the image of the actual navigation environment and make real-time corrections / adjustments to the route path as appropriate. Summary of the invention

[0005] To solve at least one of the above problems, the present invention relates to an auxiliary correction system and an operating method thereof, and in particular, to an auxiliary correction system and an operating method thereof for ships, which have the advantage of being able to display the distance of obstacles in real time in an image consistent with the detection environment. Specifically, it uses a preset machine-readable grid to determine the distance parameter of the obstacle, and confirms and corrects the distance parameter to normal (i.e., excluding the error caused by the detection environment) based on the sensor data of the sensor, so that the distance measurement of the obstacle can be completed without using a light radar (LiDAR); and it can also be used for obstacle measurement in waters with large fluctuations (such as the sea).

[0006] At least one embodiment of the present invention is a ship auxiliary correction system, which includes a receiver, a storage, at least one sensor, a processor and a display, wherein the processor is connected to the receiver, the storage and the at least one sensor; and the display is connected to the processor.

[0007] At least one embodiment of the present invention is a method for assisting ship correction. The method includes providing the ship assisting correction system; photographing a scene including at least one obstacle by the photographic device to generate at least one basic image; analyzing the at least one basic image and the at least one machine-readable grid by the processor to estimate a distance parameter about any obstacle in the scene; the processor determines the at least one distance parameter that needs to be corrected based on the sensor data generated by the at least one sensor; the processor corrects the determined at least one distance parameter according to a correction parameter; and displaying at least one auxiliary image by the display, wherein the at least one auxiliary image has at least one virtual mark for indicating the at least one distance parameter that does not need to be corrected, or the at least one distance parameter after correction. In this way, the distance of at least one obstacle relative to the transportation vehicle will be displayed on the at least one basic image.

[0008] The above brief description of the present invention is intended to provide a basic explanation of several aspects and technical features of the present invention. The brief description of the invention is not a detailed description of the present invention. Therefore, its purpose is not to specifically list the key or important elements of the present invention, nor is it to define the scope of the present invention. It is only to present several concepts of the present invention in a concise manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a structural schematic diagram of a partial embodiment of the ship auxiliary correction system of the present invention;

[0010] Figure 2 A schematic diagram of a scene of a partial embodiment of the ship auxiliary correction system of the present invention;

[0011] Figure 3 It is a flow chart of the operation method of some embodiments of the ship auxiliary calibration method of the present invention;

[0012] Figure 4 A schematic diagram of basic image output of some embodiments of the ship auxiliary correction method of the present invention;

[0013] Figure 5 It is a schematic diagram of basic image output of some embodiments of the ship auxiliary correction method of the present invention.

[0014]

Explanation of symbols

[0015] 1…Ship auxiliary correction system

[0016] 10…Receiver

[0017] 11…Photographic Installation

[0018] 20… Storage

[0019] 30…Sensors

[0020] 40…Processor

[0021] 50…Display

[0022] 100…Basic images

[0023] 200…Auxiliary images

[0024] P0...Scene

[0025] P1…Transportation

[0026] P2…Obstacles

[0027] 1011…Property Information

[0028] 1012…Vehicle information

[0029] 1013…Grid information

[0030] (A)~(F)…Steps DETAILED DESCRIPTION

[0031] To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention.

[0032] At least one embodiment of the present invention relates to an auxiliary correction system and an operating method thereof, and more particularly to an auxiliary correction system for a ship and an operating method thereof.

[0033] Please combine references Figure 1 and Figure 2 , Figure 1 is a schematic diagram of a partial embodiment of a ship auxiliary correction system 1 of the present invention; and Figure 2 FIG. 1 is a schematic diagram of scene P0 of a partial embodiment of the ship auxiliary correction system 1 of the present invention. Figure 1 As shown, the ship auxiliary correction system 1 is arranged in a transportation vehicle P1, including a receiver 10, a storage 20, at least one sensor 30, a processor 40 and a display 50, and the processor 40 is connected to the receiver 10, the storage 20, the display 50 and at least one sensor 30. Figure 1 The receiver 10 is configured to receive at least one basic image 100 captured by at least one photographing device 11; and selectively store the at least one basic image 100 in the storage 20 / send it directly to the processor 40.

[0034] At Figure 1 and Figure 2 In the illustrated embodiment, the transport vehicle P1 can be a small water vehicle such as a speedboat, a fishing boat, a sightseeing boat, etc.; and can be applied to other unmanned ships (such as large water vehicles such as warships and cruise ships), but the present invention is not limited thereto. At this time, the so-called photographic device 11 generally refers to a digital video recorder (DV), a digital still camera (DSC), a digital video camera (DVR), or other electronic devices / camera systems with a camera function, which are configured to capture and output a basic image 100 including an image of at least one obstacle P2. Among them, the obstacle P2 refers to any static / dynamic obstacle in an open / closed water area. In addition, the present embodiment does not specifically limit the number of photographic devices 11 used to one or more. The user of the present embodiment can determine the appropriate number of photographic devices 11 according to the size of the transport vehicle P1 to achieve the purpose of the discussion of this case. In the following embodiments, it will be assumed that the number of photographic devices 11 is one and is installed at the bow end of the transport vehicle P1 to represent the closest position of the transport vehicle P1 and the obstacle P2 in the navigation direction. In this way, the processor 40 only needs to obtain the position information of the photographing device 11 to obtain the actual shortest distance between the obstacle P2 and the transportation vehicle P1 through estimation.

[0035] Figure 1 and Figure 2 The sensor 30 is arranged inside or around the transport tool P1, and is used to detect the running state of the transport tool P1 (such as the degree of inclination or the sailing speed); or to assist in detecting the distance between the transport tool P1 and the aforementioned obstacle P2. It should be noted that the sensor 30 of this embodiment is an example of a functional module having an inclination sensor, an acceleration sensor and a speed sensor, but of course, it is not limited to this. Naturally, strain sensors, displacement sensors, optical sensors, rotation sensors, angle sensors or angular velocity sensors can also be used to assist in generating different detection parameters, which will be referred to as sensor data in the description of this embodiment.

[0036] The storage 20 may be implemented to store at least one machine-readable grid, and the machine-readable grid is read and executed by the processor 40. The storage 20 includes any device for storing information (such as machine-readable grid or instructions) in a form that can be read by the processor 40, for example, a large-capacity storage module that is volatile or non-volatile, magnetic, semiconductor, tape, optical, removable, non-removable, or a combination of the above elements. However, it should be understood that these descriptions are only for example, and the present invention is not limited thereto.

[0037] The processor 40 may be connected to / include the receiver 10 and the storage 20, and is configured to execute instructions stored in the storage 20; or to write and / or read various data related to the operation through wired / wireless communication with the storage 20. For example, one or more sensor data, distance parameters, basic images 100 or machine-readable grids, etc., to implement the operation of the ship auxiliary correction system 1 of this embodiment.

[0038] like Figure 1 and Figure 2 As shown, the processor 40 is configured to: analyze the basic image 100 and the machine-readable grid to estimate the distance parameter of the image of any obstacle P2, and determine whether the distance parameter needs to be adjusted based on one or more characteristic relationships of the sensor data, so as to display an auxiliary image 200 on the display 50. At this time, the display state of the auxiliary image 200 will simultaneously include the normal distance parameter of each obstacle P2 (i.e., the distance parameter that does not need to be corrected) or the distance parameter corrected by the processor, so as to indicate to the user the current relative position (such as relative orientation or distance value) of the transportation tool P1 and any obstacle P2; or the current navigation status (such as speed or tilt degree) of the transportation tool P1. In detail, the processor 40 divides the aforementioned basic image 100 according to the machine-readable grid as a boundary, so as to implement any distance measurement of the image of any obstacle P2 according to the width of each divided area. Specifically, the machine-readable grid can be configured to provide the coordinate position of the mapped image of the photographic device 11 and any obstacle P2 in the basic image 100. In fact, the so-called width can be understood as the average value of the width between two opposite ends of the vehicle P1 in the machine-readable grid.

[0039] It should be noted that, although the models and / or types of the processor 40 and the display 50 are not clearly defined herein, those skilled in the art will readily understand that the processor 40 may be a microprocessor; or any known processor, controller, or other component combination / configuration for implementing calculations. The display 50 may be a computer display / screen, a television device display / screen, or a virtual reality device display / screen; or it may be a display having a projection mapping function.

[0040] In order to facilitate understanding and explanation of the principle of the actual application of the above operation content to the embodiment, the following will be Figure 2 , Figure 3 as well as Figure 4-5 Explain in order.

[0041] First, please match Figure 1-2 And refer to Figure 3 . Figure 3The method comprises providing a ship auxiliary calibration system (step (A)). In this embodiment, the aforementioned Figure 1 A ship auxiliary correction system 1. Then, a scene P0 including at least one obstacle P2 is photographed by a photographic device 11 to generate a basic image 100 (step (B)). Furthermore, the basic image 100 and the machine-readable grid are analyzed by a processor 40 to estimate a distance parameter for each obstacle P2 in the scene P0 (step (C)). The distance parameter is used to represent a relative position information between each obstacle P2 and the photographic device in the machine-readable grid to characterize the actual shortest distance length between the obstacle P2 and the transportation vehicle P1. Then, the processor 40 determines the distance parameter that needs to be corrected based on the sensor data generated by the sensor 30 (step (D)). Then, the processor 40 corrects the determined distance parameter according to a correction parameter (step (E)). Finally, the display 50 displays the auxiliary image 200, wherein the auxiliary image 200 has at least one virtual mark for indicating a normal distance parameter (i.e., a distance parameter that does not need to be corrected) or a corrected distance parameter (step (F)). It should be noted that if step (D) does not determine any object (distance parameter) that needs to be calibrated, the calibration method will omit step (E) and directly execute step (F).

[0042] Among them, step (B) involves a selection procedure for scene P0 and includes step (B1). Step (B1): The processor 40 determines whether the scene P0 contains the aforementioned obstacle P2. If the scene P0 contains the obstacle P2, the photographic device performs shooting on the scene P0 to output the aforementioned basic image 100 to the receiver 10. Specifically, in the configuration example of step (B1), the sensor 30 has an optical sensor element to provide corresponding detection results to the processor 40 for reading the obstacle P2 in the scene P0. For example, the optical sensor element receives / senses the light emitted from the light source and reflected by the obstacle P2 in the scene P0, thereby generating a detection result that can be used by the processor 40 to read the presence or absence of the obstacle P2. In this configuration example, the optical sensor element can be a conventional charge-coupled device (CCD), a complementary metal-oxide-semiconductor (CMOS) or other elements with light sensing functions.

[0043] In addition, other configuration examples of step (B1) may optionally include step (B11), step (B11): determining by the processor 40 whether the obstacle P2 detected in the scene P0 satisfies a preset condition, that is, the preset condition is equivalent to determining whether the expected resolution of the image of any obstacle P2 is higher than a critical value, wherein the so-called expected resolution is determined by the number of pixels of the obstacle image (i.e., the image of any obstacle P2) in the image output by the photographic device 11; and the so-called critical value is a preset pixel number threshold value that can be programmed by the user and is designed to match the sensitivity of the processor 40. Therefore, if the processor 40 determines that the expected resolution of the image of any obstacle P2 is higher than or equal to the critical value, the basic image 100 can be generated accordingly according to the scene P0. If the processor 40 determines that the expected resolution of the image of any obstacle P2 is lower than the critical value, the scene P0 is discarded and step (B1) is re-executed.

[0044] In the present embodiment, step (C) further includes steps (C1)-(C3), which are to calculate the distance parameters of the image of the obstacle P2 in the basic image 100 one by one by the processor 40. First, step (C1): set a first reference point representing the photographic device 11 on the machine-readable grid, and set a second reference point representing the two opposite end points of the transportation vehicle P1 in the machine-readable grid according to the first reference point. Next, step (C2): map the feature points of the image of each obstacle P2 in the basic image 100 to the corresponding target points of the machine-readable grid. Then execute step (C3): calculate and obtain the distance parameters of the image of any obstacle P2 according to the distance between the individual second reference point and the first reference point and each target point. In the above steps, a trigonometric function algorithm can be used, and steps (C2) and (C3) are repeatedly executed until the definition of the distance parameters of the images of all obstacles P2 is completed. Generally speaking, the execution of steps (C1)-(C3) can also be implemented in conjunction with iterative calculations. In this case, steps (C1) and (C3) may include steps that are understandable to those skilled in the art.

[0045] The feature point mentioned in step (C2) is to select at least one possible neighboring point from the edge endpoints of the images of multiple obstacles P2. Here, the neighboring point is defined with different distance lengths according to the actual endpoint position of the transport tool P1 simulated by the processor 40, so as to identify the virtual point position (i.e., edge endpoint) where each obstacle P2 and the transport tool P1 actually have a higher probability of collision. The actual endpoint position of the transport tool P1 can be preset information; or it can be obtained by using a programming language (such as Python) in combination with iterative calculation; similarly, the edge endpoint of the image of the obstacle P2 can also be determined by the same method.

[0046] And, it can be understood from the previous description that the target point of step (C2) is the relative coordinate of the individual feature points presented on the machine-readable grid after the transformation matrix. It should be noted that the transformation matrix at this time involves the position correspondence between the image of each obstacle P2 in the basic image 100 and the machine-readable grid, and the transformation matrix can be pre-stored in the memory 20, or generated by the processor 40 based on the position correspondence obtained at that time. In addition, considering that the calculation of the transformation matrix is ​​only a common application of a simple algorithm, it will not be repeated here.

[0047] Wherein, step (D) involves the determination of the relevant calibration object (i.e., the distance parameter that needs to be calibrated), and further includes steps (D1)-(D2). Step (D1): The processor 40 determines whether the first shake coefficient of the sensor data is greater than the first threshold value, and whether the second shake coefficient is greater than the second threshold value. Wherein, assuming that if any of the first shake coefficient and the second shake coefficient is higher than (or higher than or equal to) the corresponding threshold value (the first threshold value or the second threshold value), it is necessary to calibrate all distance parameters of the basic image 100; step (D2): The processor 40 uses the first shake coefficient and the second shake coefficient to provide the calibration parameters. In this embodiment, the calibration parameters are obtained by multiplying the first shake coefficient by the second shake coefficient; of course, the present invention can also use a specific calculation model to provide the calibration parameters on the first shake coefficient and the second shake coefficient, and is not limited thereto. It is worth mentioning that the first threshold value and the second threshold value here are both predetermined values, which are only selected according to actual application requirements. For example, when the first sway coefficient is used to represent the sway degree of the transport vehicle P1 in the horizontal direction, the first threshold value is determined according to the corresponding anti-sway degree of the camera device 11 equipped therewith; similarly, when the second sway coefficient is used to represent the sway degree of the transport vehicle P1 in the horizontal direction, the same is true. In addition, one of the first sway coefficient and the second sway coefficient can also be used to represent the sway degree of the transport vehicle P1 in the vertical direction, which is defined depending on the different waters where the transport vehicle P1 is sailing.

[0048] When the sensor 30 includes a timer, step (D3) can be selectively performed between steps (D1) and (D2): the processor 40 further determines whether the duration of the first sway coefficient or the second sway coefficient exceeds the allowable value, wherein, if the duration does not exceed the allowable value, the distance parameter is not corrected (i.e., step (D2) is not continued), and the processor 40 sends the auxiliary image 200 generated by step (C) to the display 50 (i.e., step (F)) for the user to view. In this embodiment, the allowable value related to the duration is determined according to the calibration specification of the adaptive algorithm of the photographic device 11, and can also be dynamically defined or defined in other types according to actual conditions (such as environmental factors such as wind speed and flow rate), and the present invention is not limited to this.

[0049] In other possible embodiments, based on the different correction parameters required to be output by the transport vehicle P1 (such as when the transport vehicle P1 is located in a sea lane), steps (D1)-(D2) can also be replaced by steps (E1)-(E4) in step (E). Step (E1): The processor 40 extracts the first horizontal line according to the predefined standard image, and extracts the second horizontal line in the basic image 100; Step (E2): The processor 40 superimposes the basic image 100 on the standard image to form a superimposed data, and the superimposed data will contain information of the first horizontal line and the second horizontal line at the same time; Step (E3): A simulation element in the processor 40 projects a mark to the first horizontal line and the second horizontal line to form a reference mark (first horizontal line) and a correction mark (second horizontal line) with an offset; Step (E4): The processor 40 calculates the offset value between the reference mark and the correction mark to form the correction parameter.

[0050] Please cooperate Figure 2 and Figure 3 Reference Figure 4 and 5 , Figure 4 and 5 This is a schematic diagram of the auxiliary image 200 output of a partial embodiment of the ship auxiliary calibration method of the present invention. Figure 4 The output type when the present invention is applied to close range detection is shown; and Figure 5 It is to show the output type when the present invention is applied to long-distance detection, wherein the so-called short distance, medium distance and long distance have no special distance value limit, and are only a conceptual representation of the relative distance between the obstacle P2 and the transportation tool P1. In view of the fact that the present embodiment is applied to an unmanned vehicle traveling on water, there are many interference factors on the water surface, so it is necessary to appropriately display an image consistent with the waterway scene P0 to adjust the path of the transportation tool P1 in a timely manner. In addition, in order to improve the efficiency of monitoring, in the actual application of the present embodiment, the display 50 is configured to display an auxiliary image 200 with a virtual identifier in response to the output information (such as the distance parameter) of the processor 40. Specifically, before executing step (E), the processor 40 uses each distance parameter to generate a virtual identifier corresponding to it, so as to implant the virtual identifier in the basic image 100 to form an auxiliary image 200 and output it to the display 50. In this way, the distance parameter used as the basis for determining the probability of collision will first be identified based on the virtual identifier.

[0051] Figure 4 and Figure 5The virtual identification may include object information 1011 and vehicle information 1012, but is not limited thereto. In other practical applications, the virtual identification may also selectively include grid information 1013. The object information 1011 is a collection of the distance value (cm) between any obstacle P2 and the transport vehicle P1 and the direction (orientation) of any obstacle P2 relative to the transport vehicle P1. It should be noted that the distance value here is equivalent to the value of the aforementioned distance parameter; the vehicle information 1012 is the speed value (knot) of the real-time speed of the transport vehicle P1; and the grid information 1013 is a visual form of the machine-readable grid represented in line form.

[0052] In addition, the virtual identification can also selectively include other information represented by linear representation. For example, the detection range of the sensor 30 or the outline of the obstacle P2. In order to effectively identify the virtual identification implanted in the basic data, the present invention can further use the processor 40 to color the object information 1011, the vehicle information 1012 and the grid information 1013 according to the attributes before executing step (E). For example, the close distance (i.e., the distance value is smaller) in the object information 1011 is given red to improve the warning effect; similarly, the collision boundary (i.e., the linear extension of the two opposite ends of the vehicle P1) in the grid information 1013 is given yellow; and so on. At this time, the so-called attribute can be a further definition of the object information 1011, the vehicle information 1012 and the grid information 1013, such as: the close distance, the long distance of the object information 1011, or the idling, the speeding of the vehicle information 1012, or other types of definition forms, which are not limited by the present invention. The corresponding relationship between the attribute and the coloring can be a preset standard lookup table; or different coloring representations can be randomly given according to actual operation requirements (ie, one attribute corresponds to one coloring).

[0053] In summary, although the present invention has been disclosed by way of embodiments, it is not intended to limit the present invention. A person skilled in the art of the present invention may make various modifications and improvements without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the following claims.

Claims

1. A ship auxiliary correction system, characterized in that: include: a receiver for receiving at least one basic image captured by at least one photographic device, wherein the at least one photographic device is disposed on a water vehicle; a storage device for storing at least one machine-readable grid; At least one sensor, used to detect the state of the water vehicle and generate at least one sensing data; The at least one sensing data includes a first sway coefficient and a second sway coefficient, and the first sway coefficient and the second sway coefficient are selected from any two of a horizontal lateral sway degree, a horizontal longitudinal sway degree, and a vertical sway degree of the water vehicle; a processor connected to the receiver, the storage and the at least one sensor, and configured to: generate at least one distance parameter based on the at least one base image and the at least one machine-readable grid, and determine whether the at least one distance parameter needs to be corrected according to the at least one sensor data; The processor determines whether the first shake coefficient of the at least one sensing data is greater than a first threshold, and whether the second shake coefficient is greater than a second threshold; The processor uses the first shake coefficient and the second shake coefficient to provide a calibration parameter; The processor determines whether the duration of the first sway coefficient or the second sway coefficient exceeds an allowable value according to the at least one sensor data; The processor determines whether a scene has at least one obstacle. If the scene includes the at least one obstacle, the photographic device photographs the scene and outputs at least the basic image to the receiver. The processor determines whether the at least one obstacle read in the scene satisfies a preset condition, wherein if the at least one obstacle satisfies the preset condition, the processor generates the at least one basic image according to the scene; a display, connected to the processor, configured to present at least one auxiliary image; Wherein, assuming that if any one of the first shake coefficient and the second shake coefficient is higher than the corresponding first threshold value or the second threshold value, it is necessary to perform correction processing on all the at least one distance parameter of the at least one basic image; The first threshold and the second threshold depend on the anti-shake degree of the at least one photographic device.

2. The ship auxiliary correction system according to claim 1, characterized in that: The at least one sensor is a tilt sensor, an acceleration sensor or a combination thereof.

3. A ship auxiliary correction method, characterized in that: The following steps are involved: (A) providing a ship auxiliary correction system as claimed in claim 1; (B) photographing the scene including the at least one obstacle by the at least one photographing device to generate the at least one basic image, wherein (B1) the processor determines whether the scene includes the at least one obstacle, and if the scene includes the at least one obstacle, the photographing device photographs the scene and outputs the at least one basic image to the receiver; wherein step (B1) further comprises: (B11) the processor determines whether the at least one obstacle interpreted in the scene satisfies the preset condition, wherein, assuming that if the at least one obstacle satisfies the preset condition, it is confirmed that the at least one basic image corresponding to the scene can be generated; (C) analyzing, by the processor, the at least one base image and the at least one machine-readable grid to estimate the at least one distance parameter for any obstacle in the scene; (D) the processor determines the at least one distance parameter that needs to be corrected based on the sensing data generated by the at least one sensor, wherein (D1) the processor determines whether the first shake coefficient of the at least one sensing data is greater than a first threshold, and whether the second shake coefficient is greater than a second threshold, wherein if any one of the first shake coefficient and the second shake coefficient is higher than the corresponding first threshold or the second threshold, it is necessary to perform correction processing on all the at least one distance parameter of the at least one basic image; (D2) the processor uses the first shake coefficient and the second shake coefficient to provide a calibration parameter; (D3) the processor determines whether the duration of the first sway coefficient or the second sway coefficient exceeds the allowable value according to the at least one sensor data, wherein if the duration does not exceed the allowable value, no correction is performed on all of the at least one distance parameter; (E) the processor calibrates the determined at least one distance parameter according to the calibration parameter; and (F) displaying the at least one auxiliary image on the display, wherein the at least one auxiliary image has at least one virtual marker for indicating the at least one distance parameter that does not need to be corrected, or the at least one distance parameter after correction; The first threshold and the second threshold depend on the anti-shake degree of the at least one photographic device; Wherein, step (D3) is performed between steps (D1) and (D2).

4. The ship auxiliary correction method according to claim 3, characterized in that: Step (C) includes executing steps (C1) to (C3) with the processor: (C1) setting a first reference point representing the photographic device on the at least one machine-readable grid, and setting a second reference point representing two opposite end points of the water vehicle in the at least one machine-readable grid according to the first reference point; (C2) mapping feature points of the image of the at least one obstacle in the at least one base image to corresponding at least one target point of the at least one machine-readable grid; and (C3) Calculating based on the distance between the second reference point, the first reference point and the at least one target point, and obtaining the at least one distance parameter of the image of the at least one obstacle, and repeating steps (C2) and (C3) until the definition of the at least one distance parameter of the images of all obstacles is completed.

Images