CN110702066B - Underwater binocular camera vision positioning method - Google Patents
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Abstract
The invention discloses a visual positioning method for an underwater binocular camera, which comprises the following steps: step 1: underwater sounding compensation; step 2: shooting an underwater calibration image; and step 3: carrying out algorithm correction to obtain a correction formula; and 4, step 4: and reading the underwater picture and giving the distance from the specified point to the center of the image. The invention can realize the approximate positioning function of the underwater binocular vision system without the precise calibration equipment, can save the cost for purchasing the precise calibration equipment, and can approximately achieve the positioning function of the underwater binocular vision system calibrated by the precise calibration equipment.
Description
Technical Field
The invention belongs to the field of underwater vision positioning, and particularly relates to a vision positioning method for an underwater binocular camera.
Background
With the rapid development of computer vision technology, the vision technology is applied to underwater intelligent fishing more and more. In an aquatic product culture pond, the depth is usually within 3 meters, the bottom surface is flat, and the underwater binocular camera positioning is the premise of underwater automatic intelligent fishing.
At present, researchers have proposed a plurality of underwater binocular camera positioning methods, in order to ensure the reliability of calibration, a high-precision underwater calibration plate is generally required, and a calibration result is finally obtained through complicated underwater optical path calculation and measurement correction.
Disclosure of Invention
Aiming at the prior art, the invention aims to provide a simple underwater binocular camera vision positioning method which can reduce the cost of underwater vision positioning. According to the method, the depth measurement algorithm of the binocular camera in the air is compensated into the underwater depth measurement algorithm through depth measurement compensation and plane distance measurement correction of the camera, and the underwater binocular vision positioning algorithm is completed.
In order to solve the technical problem, the invention provides a visual positioning method of an underwater binocular camera, which comprises the following steps:
step 1: underwater sounding compensation;
step 2: shooting an underwater calibration image;
and step 3: carrying out algorithm correction to obtain a correction formula;
and 4, step 4: and reading the underwater picture and giving the distance from the specified point to the center of the image.
The invention also includes:
1. step 1: underwater sounding compensation comprising:
step 1-1: fixing the camera at a certain depth under water, and measuring the vertical distance from the camera to the water bottom at the moment;
step 1-2: opening a camera depth measurement program to obtain depth information given by the camera at the moment;
step 1-3: repeating the two steps at the same distance;
step 1-4: drawing a relation curve between the manually measured depth distance and the depth information given by the camera;
step 1-5: and fitting the curve obtained in the last step by using a function to obtain a camera depth compensation formula.
2. Step 2: shooting an underwater calibration image, comprising:
step 2-1: placing a checkerboard image or a graduated steel ruler on the underwater horizontal ground;
step 2-2: fixing the camera at a certain depth under water, and measuring the vertical distance from the camera to the water bottom at the moment;
step 2-3: opening a camera, shooting n underwater checkerboard or steel ruler pictures, wherein n is more than or equal to 5, and recording current depth information;
step 2-4: repeating step 2-2 and step 2-3 at equal intervals.
3. And step 3: and (3) carrying out algorithm correction to obtain a correction formula, wherein the correction formula comprises:
step 3-1: selecting a steel ruler or a checkerboard picture shot at a certain depth, selecting two scale endpoints on the steel ruler or on the checkerboard, recording pixel coordinates of the two endpoints and the distance between the two clear endpoints, and calculating the distance represented by each pixel point at the current depth;
step 3-2: selecting n pairs of end points with different directions to calculate the data in the step 3-1, wherein n is more than or equal to 5, and taking an average number;
step 3-3: and (3) selecting pictures with different depths, repeating the steps 3-1 and 3-2, drawing a relational graph between the depth and the distance represented by the unit pixel point, and fitting by using a function to obtain a correction formula.
4. And 4, step 4: reading the underwater picture and giving the distance of the specified point from the center of the image comprises the following steps:
step 4-1: opening a camera depth measurement program, measuring the current depth, and performing depth compensation according to the compensation formula obtained in the step 1;
step 4-2: reading an underwater picture to obtain pixel coordinate information of a pixel point needing to be positioned;
step 4-3: according to the correction formula obtained in the step 3 and the distance coordinate (x) from the specified point to the central point of the imagew,yw) Calculating the relative distance between the point and the central point of the image by a calculation formula;
5. step 3-1, calculating the distance represented by each pixel point according to the following formula:
khi=f(i)
wherein k isijThe depth is represented by the distance represented by the unit pixel point when the ith measurement is carried out, d represents the distance displayed on the steel ruler, (x)1,y1) And (x)2,y2) Pixel coordinates, k, representing two end points on a steel ruleiRepresenting the average value of the distances represented by the unit pixel points when the depth is i, m represents the measurement times, khiRepresents the distance represented by the unit pixel at depth i after fitting.
6. Distance coordinate (x) from the designated point to the image center point of step 4-3w,yw) The calculation formula satisfies:
xw=khi(x-x0)
yw=khi(y-y0)
wherein k ishiThe distance represented by the unit pixel point under the current depth is represented, the (x, y) represents the pixel coordinate of the appointed point, and the (x) represents the current depth0,y0) Pixel coordinates of the center point of the image.
The invention has the beneficial effects that: the invention can realize the approximate positioning function of the underwater binocular vision system without precise underwater calibration equipment, is not limited by environmental factors such as seawater, fresh water, illumination temperature and the like, reduces the calibration complexity, improves the calibration efficiency, can save the expenditure for purchasing the precise calibration equipment, but also can approximately achieve the positioning function of the underwater binocular vision system calibrated by the precise calibration equipment.
Drawings
FIG. 1 is an overall flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of a camera position during underwater depth measurement compensation and underwater calibration image shooting.
Fig. 3 is a schematic of the linear fit data.
FIG. 4 is a diagram illustrating the distance represented by a unit pixel when the calculated depth is i.
Fig. 5 is a schematic diagram of reading an underwater picture and showing the distance of a specified point from the center of the image.
Fig. 6 is a schematic diagram of program output coordinate information.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Firstly, carrying out underwater depth measurement compensation on a binocular camera to obtain compensated underwater depth information; then, shooting an underwater calibration image, and calculating actual distances corresponding to unit pixels in different depths and different directions; and finally, carrying out algorithm correction and compensation to obtain an approximate underwater camera positioning system. The method provided by the invention can obtain good effects in the aspects of accuracy of image segmentation and boundary smoothness of the image-adhered rice grains, and can be applied to an automatic detection system for rice grain quality to effectively improve detection precision.
The invention discloses a visual positioning method of an underwater binocular camera, which comprises the following steps:
step 1: and (3) underwater sounding compensation:
1-1) fixing the camera at a certain depth under water and measuring the vertical distance from the camera to the water bottom at that time.
1-2) opening a camera depth measurement program to obtain the depth information given by the camera at the moment.
1-3) repeating the above two steps every 1 cm.
1-4) drawing a relation curve between the depth distance measured manually and the depth information given by the camera.
1-5) fitting the curve obtained in the last step by adopting a function to obtain a camera depth compensation formula.
Step 2: shooting an underwater calibration image, mainly comprising:
2-1) placing a checkerboard image or a graduated steel ruler on the underwater horizontal ground;
2-2) fixing the camera at a certain depth under the water, and measuring the vertical distance from the camera to the water bottom at the moment.
And 2-3) opening a camera, shooting 5-10 underwater checkerboard and steel ruler photos, and recording current depth information.
2-4) repeating steps 2-2) and 2-3) every 2 cm.
And step 3: the algorithm correction mainly comprises the following steps:
3-1) selecting a steel ruler photo shot at a certain depth, selecting two clear scale endpoints on the steel ruler or on the checkerboard, recording pixel coordinates of the two endpoints and the distance between the two clear endpoints, and calculating the distance represented by each pixel point at the current depth according to the following corresponding calculation formula:
wherein k isijThe depth is represented by the distance represented by the unit pixel point when the ith measurement is carried out,d represents the distance shown on the steel ruler, (x)1,y1) And (x)2,y2) The pixel coordinates of the two end points on the steel ruler are shown.
3-2) selecting multiple pairs of end points with different directions to calculate the data in the step 3-1), and taking an average number, wherein a corresponding formula is as follows:
wherein k isiAnd when the representative depth is i, the average value of the distances represented by the unit pixel points is represented, and m represents the measurement times.
3-3) selecting photos with different depths, repeating the steps 3-1) and 3-2), drawing a relation graph between the depth and the distance represented by the unit pixel points, and fitting by using a function, wherein the corresponding formula is as follows:
khi=f(i) (3)
wherein k ishiRepresents the distance represented by the unit pixel in depth after fitting.
And 4, step 4: reading an underwater picture and giving the distance from a specified point to the center of an image, and mainly comprising the following steps:
4-1) opening a camera depth measurement program, measuring the current depth, and performing depth compensation according to the compensation formula obtained in the step 1.
And 4-2) reading the underwater picture to obtain the pixel coordinate information of the pixel point needing to be positioned.
4-3) calculating the relative distance between the point and the central point of the image according to the correction formula obtained in the step 3, wherein the corresponding formula is as follows:
xw=khi(x-x0) (4)
yw=khi(y-y0) (5)
wherein k ishiThe distance represented by a unit pixel point at the current depth calculated in formula (3) is represented, and (x, y) represents the pixel coordinate of a designated point, and (x)0,y0) Pixel coordinates of the center point of the image.
Example 1
Referring to FIG. 1, FIG. 1 is a main flow chart of the method of the present invention. The simple underwater binocular camera vision positioning method mainly comprises the following four steps: step 1, underwater depth measurement compensation, step 2, shooting an underwater calibration image, step 3, carrying out algorithm correction, and step 4, reading the underwater image and giving the distance from a specified point to the center of the image.
Example 2
Step 1 will be specifically described with reference to fig. 2 and 3. Fig. 2 is a schematic diagram of the position of the underwater depth measurement compensation camera, and the step 1 is underwater depth measurement compensation. Step 1 comprises five parts: 1-1) fixing a camera at a certain depth under water, measuring the vertical distance from the camera to the water bottom at the moment, 1-2) opening a camera depth measurement program to obtain depth information given by the camera at the moment, 1-3) repeating the two steps at intervals of 1 cm, 1-4) drawing a relation curve of the manually measured depth distance and the depth information given by the camera, and 1-5) fitting the curve obtained in the previous step by adopting a function to obtain a camera depth compensation formula.
Step 1-1), firstly, fixing the underwater binocular camera at a certain depth by using a support, and paying attention to submerging all cameras into the water, as shown in fig. 2. Step 1-2), step 1-3) to obtain depth data given by the camera and manually measured depth data. Step 1-4) fitting the data given by the camera and the manually measured depth data by multi-segment linear fitting to obtain a compensation formula, as shown in fig. 3.
Example 3
Step 2 is specifically described with reference to fig. 1. Fig. 2 is a schematic diagram of the position of the underwater depth measurement compensation camera, only a steel ruler or a checkerboard image needs to be placed on the bottom surface and inside the camera view, and step 2 is to acquire an underwater calibration image. Step 2 comprises four parts: 2-1) placing a checkerboard image or a graduated steel ruler on the underwater horizontal ground; 2-2) fixing the camera at a certain depth under water, measuring the vertical distance from the camera to the water bottom at the moment, 2-3) opening the camera, shooting 5-10 underwater checkerboard and steel ruler photos, recording current depth information, 2-4) repeating the steps 2-2) and 2-3) every 2 centimeters.
Example 4
Step 3 will be specifically described with reference to fig. 4. Step 3 is algorithm correction and comprises three parts.
3-1) selecting a steel ruler or a checkerboard picture shot at a certain depth, selecting two clear scale endpoints on the steel ruler or the checkerboard, recording pixel coordinates of the two endpoints and the distance between the two clear endpoints, and calculating the distance represented by each pixel point at the current depth according to the following corresponding calculation formula:
kijthe depth is represented by the distance represented by the unit pixel point when the ith measurement is carried out, d represents the distance displayed on the steel ruler, (x)1,y1) And (x)2,y2) The pixel coordinates of the two end points on the steel ruler are shown.
3-2) selecting multiple pairs of end points with different directions to calculate the data in the step 3-1), and taking an average number, wherein a corresponding formula is as follows:
wherein k isiAnd when the representative depth is i, the average value of the distances represented by the unit pixel points is represented, and m represents the measurement times.
3-3) selecting photos with different depths, repeating the steps 3-1) and 3-2), drawing a relation graph between the depth and the distance represented by the unit pixel points, and fitting by using a function, wherein the corresponding formula is as follows:
khi=f(i) (8)
wherein k ishiRepresents the distance represented by the unit pixel at depth i after fitting.
Example 5
Step 4 is specifically described with reference to fig. 5 and 6. Step 4 is visual positioning, which comprises three parts, namely 4-1) measuring depth, 4-2) reading underwater images and 4-3) carrying out underwater visual positioning.
And 4-1) opening a camera depth measurement program, measuring the current depth, and performing depth compensation according to the compensation formula obtained in the step 1.
And 4-2) reading the underwater picture to obtain pixel coordinate information of the pixel point needing to be positioned.
Step 4-3) calculating the relative distance between the point and the central point of the image according to the correction formula obtained in the step 3, wherein the corresponding formula is as follows:
xw=khi(x-x0) (4)
yw=khi(y-y0) (5)
wherein (x)w,yw) For the distance coordinates of a specified point from the center point of the image, (x, y) denotes the pixel coordinates of the specified point, (x0,y0) Pixel coordinates of the center point of the image.
Claims (6)
1. The underwater binocular camera vision positioning method is characterized by comprising the following steps of:
step 1: underwater sounding compensation;
step 2: shooting an underwater calibration image;
and step 3: carrying out algorithm correction to obtain a correction formula;
and 4, step 4: reading an underwater picture and giving the distance from a specified point to the center of the image;
the step 1 comprises the following steps:
step 1-1: fixing the camera at a certain depth under water, and measuring the vertical distance from the camera to the water bottom at the moment;
step 1-2: opening a camera depth measurement program to obtain depth information given by the camera at the moment;
step 1-3: repeating the two steps at the same distance;
step 1-4: drawing a relation curve between the manually measured depth distance and the depth information given by the camera;
step 1-5: and fitting the curve obtained in the last step by using a function to obtain a camera depth compensation formula.
2. The underwater binocular camera vision positioning method of claim 1, wherein: the step 2 comprises the following steps:
step 2-1: placing a checkerboard image or a graduated steel ruler on the underwater horizontal ground;
step 2-2: fixing the camera at a certain depth under water, and measuring the vertical distance from the camera to the water bottom at the moment;
step 2-3: opening a camera, shooting n underwater checkerboard or steel ruler pictures, wherein n is more than or equal to 5, and recording current depth information;
step 2-4: repeating step 2-2 and step 2-3 at equal intervals.
3. The underwater binocular camera vision positioning method of claim 1, wherein: the step 3 comprises the following steps:
step 3-1: selecting a steel ruler or a checkerboard picture shot at a certain depth, selecting two scale endpoints on the steel ruler or on the checkerboard, recording pixel coordinates of the two endpoints and the distance between the two clear endpoints, and calculating the distance represented by each pixel point at the current depth;
step 3-2: selecting n pairs of end points with different directions to calculate the data in the step 3-1, wherein n is more than or equal to 5, and taking an average number;
step 3-3: and (3) selecting pictures with different depths, repeating the steps 3-1 and 3-2, drawing a relational graph between the depth and the distance represented by the unit pixel point, and fitting by using a function to obtain a correction formula.
4. The underwater binocular camera vision positioning method of claim 1, wherein: step 4 comprises the following steps:
step 4-1: opening a camera depth measurement program, measuring the current depth, and performing depth compensation according to the compensation formula obtained in the step 1;
step 4-2: reading an underwater picture to obtain pixel coordinate information of a pixel point needing to be positioned;
step 4-3: according to the correction formula obtained in the step 3 and the distance coordinate (x) from the specified point to the central point of the imagew,yw) Calculating the relative distance between the point and the central point of the image by a calculation formula;
5. the underwater binocular camera vision positioning method of claim 3, wherein: step 3-1, calculating the distance represented by each pixel point according to the following formula:
khi=f(i)
wherein k isijThe depth is represented by the distance represented by the unit pixel point when the ith measurement is carried out, d represents the distance displayed on the steel ruler, (x)1,y1) And (x)2,y2) Pixel coordinates, k, representing two end points on a steel ruleiRepresenting the average value of the distances represented by the unit pixel points when the depth is i, m represents the measurement times, khiRepresents the distance represented by the unit pixel at depth i after fitting.
6. The underwater binocular camera vision positioning method of claim 4, wherein: 4-3 distance coordinate (x) from the specified point to the central point of the imagew,yw) The calculation formula satisfies:
xw=khi(x-x0)
yw=khi(y-y0)
wherein k ishiThe distance represented by the unit pixel point under the current depth is represented, the (x, y) represents the pixel coordinate of the appointed point, and the (x) represents the current depth0,y0) Pixel coordinates of the center point of the image.
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