JP2796085B2 - Simulation method of underwater laser visual recognition device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for simulating an underwater laser visual recognition device, and more particularly to a technique for simulating an output image of an underwater laser visual recognition device that irradiates a laser pulse to an underwater visual target and visually recognizes the object. About.

[0002]

2. Description of the Related Art Japanese Unexamined Patent Publication (Kokai) No. 7-072505 discloses a technique relating to an underwater laser visual recognition device capable of accurately visually recognizing a target in the sea, for example, in marine construction in a turbid and poorly transparent sea area. I have. The laser visual recognition device described in this known document irradiates a laser pulse to the visual recognition target from an irradiation / imaging device located at a position distant from the visual recognition target, and detects reflected light thereof to thereby form an image of the visual recognition target. Is obtained.

[0003]

When such an underwater laser visual recognition device is used, the visible distance (viewing distance) differs depending on the turbidity of seawater (light propagation medium). Therefore, it is necessary to determine the installation location of the irradiation / imaging device according to the turbidity of the seawater. In addition, the specifications of the underwater laser viewing device, such as the repetition number and pulse width of the laser pulse in the irradiation device, the irradiation energy of the laser pulse,
It is necessary to change specifications such as a zoom lens and a shutter speed of a camera provided in the imaging apparatus according to the turbidity.

Conventionally, the study of the installation location of such an irradiation / imaging device and the change of the specification of the underwater laser visual recognition device have been performed based on the results of actually measuring the turbidity of seawater at the work site. Therefore, the conventional underwater laser visual recognition device has a problem in that the preparation time is required until the visual recognition target is actually visually recognized, and thus the usability is poor.

The present invention has been made in view of the above-mentioned problems, and has as its object to provide a simulation method of an underwater laser visual recognition device capable of improving the usability of the underwater laser visual recognition device.

[0006]

In order to achieve the above object, a first means is to irradiate a laser pulse to an object to be viewed arranged in a light propagation medium and capture reflected light of the laser pulse. In a simulation method for generating an output image of a laser visual recognition device that obtains an image of a visual target, a test image including a plurality of different reference luminance portions is set as a visual target, and light is reflected based on reflected light from the test image. Means of calculating the contrast value of the test image according to the turbidity of the propagation medium and the viewing distance to the test image is employed.

As a second means, the above-mentioned first means employs a means in which a test image in which a black stripe is formed on a white background is used.

As a third means, in the first or second means, the test image is divided into a plurality of pixels, and a contrast value is calculated based on a maximum value and a minimum value of reflected light obtained from each pixel. Means is adopted.

As a fourth means, in any of the first to third means, a direct reflected light component, a back scattered light component and a forward scattered light component are calculated for the reflected light, respectively, and based on each of these components. Means for calculating a contrast value by using the method.

As a fifth means, in any one of the first to fourth means, when the laser viewing device captures the reflected light of the laser pulse through the shutter, the opening time of the shutter is divided into a plurality of time sections. Means for calculating the contrast value based on the average value of the reflected light in each time section.

As a sixth means, in any one of the first to fifth means, a means for calculating a contrast value based on reflected light obtained from a central portion of a test image is employed.

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a simulation method for an underwater laser visual recognition device according to the present invention will be described below with reference to the drawings.

FIG. 1 is a plan view showing a schematic configuration of an underwater laser visual recognition device. In this figure, reference numeral 1 denotes an irradiation device, 2 denotes an imaging device, and 3 denotes an object to be viewed. Irradiation device 1
Is arranged at a distance R1 from the visual target 3 and irradiates the visual target 3 with a laser pulse of a specific repetition number. For example, as shown in FIG. 2A, a test image in which white portions (reference luminance portions) and black portions (reference luminance portions) are alternately drawn as vertical stripes on a flat member as shown in FIG. Is done.

The imaging device 2 is arranged at a distance (viewing distance) R2 from the viewing target 3 and detects the intensity of the reflected light of the laser pulse from the viewing target 3. The imaging device 2 includes a shutter, and the shutter detects the reflected light only during a time when the shutter is opened and closed in synchronization with the laser pulse (opening time: ta). In addition, between the visual recognition target 3 and the irradiation device 1 and the imaging device 2,
There is a light propagation medium 4 with a specific turbidity c.

The simulation method according to the present embodiment is realized by a computer such as a workstation, and its storage device stores various setting conditions relating to the underwater laser visual recognition device as initial setting data.

For example, the initial setting data includes the following. The distance R1 from the viewing target 3 to the irradiation device 1. Distance from the viewing target 3 to the imaging device 2 (viewing distance)
R2. The angle γ between the normal L of the visual recognition target 3 and the incident direction of the laser pulse. Turbidity of the light propagation medium 4 (given as an attenuation coefficient of the light propagation medium 4 for laser pulses) c. The wavelength λ of the laser pulse. Time function indicating the laser pulse. Optical characteristic values of the imaging device 2, such as f-number, focal length, shutter opening time ta, and the like. Image data of the test image.

The functions for calculating the direct reflected light component Ed, the backscattered light component (backscatter component) Ebs, and the forward scattered light component (forward scatter component) Efs included in the reflected light based on the initial setting data are as follows. It is stored in the storage device. This function is a function represented by the above-mentioned initial setting data such as the viewing distance R2 and the turbidity c of the light propagation medium 4, and is, for example, the University of Washington, Ishimaru
Author: Use those described in "Wave propagation and scattering in random media".

The computer simulates the underwater laser visual recognition device based on the initial setting data and input data input from an input device such as a keyboard, and the intensity of reflected light (brightness of a test image) captured by the imaging device 2. Is calculated, and a contrast value indicating a ratio between the luminance of the white part and the luminance of the black part is calculated as follows based on the luminance. Then, the result is output to an output device such as a display device or a printing device.

Next, the details of the simulation method of the present embodiment will be described with reference to the flowchart shown in FIG.
First, as a simulation range, a simulation range for turbidity c, ie, a turbidity range G, and a simulation range for visible distance, ie, a visible distance range H, are input from a keyboard or the like (step S1). The step size indicating whether to execute is the turbidity step width △
c and the visible distance step width Δr (step S)
2).

When the simulation range is input in this way, the test image shown in FIG. 2A is divided into M equal parts by the pixel division number M (integer) in the X-axis direction (for example, the horizontal direction) and the Y-axis direction ( For example, the pixel is divided into a plurality of pixels by dividing the pixel into N (integer) in the vertical direction (N) (integer), and coordinates are assigned to each pixel to generate a pixel map (step S3). For example, as shown in the figure, the test image is a two-dimensional array of pixels A11 to Aij (i and j are integers) to Amn in which the pixel A11 is near the upper left end and the pixel Amn is near the lower right end.
And each pixel A11 to Amn has a horizontal coordinate x1.
Xi to xm and vertical coordinates y1 to yj to yn are created. This pixel map is stored in a storage device in, for example, a table format.

Further, in the above step S1, for example, the minimum turbidity ca and the maximum turbidity cb as the turbidity range G, and the minimum visible distance R2a and the maximum visible distance R2b as the visible distance range H, for example.
Is input, the viewing distance R2 is initialized to the minimum viewing distance R2a (step S4), and the turbidity c is initialized to the minimum turbidity ca (step S5), and the following calculation is performed. .

Subsequently, in step S6, the luminance of each of the pixels A11 to Amn is calculated. Hereinafter, the details of this processing will be described with reference to the flowchart of FIG.

First, the integer j is initialized to "1" (step Sa1), the integer i is initialized to "1" (step Sa2), and the process for the pixel A11 is started. The shutter opening time ta is divided into P by the number of time divisions P (integer), and a plurality of division times t1 to tk (k
Is an integer) to tp (step Sa3), and an integer k
Is initially set to "1" (step Sa3). And
Thereafter, the processing of steps Sa5 to Sa7 is sequentially repeated to calculate the direct reflection component Ed, the back scattered light component Ebs, and the forward scattered light component Efs for the pixel A11 for all the divided times t1 to tk.

That is, when the direct reflection component Ed, the back scattered light component Ebs, and the forward scattered light component Efs for the division time t1 are calculated, the integer k becomes the integer P indicating the number of divisions of the opening time ta in step Sa6. It is determined whether they are equal. Now, the integer k is initially set to "1",
The determination is "NO", the integer k is incremented (step Sa7), and the processing of steps Sa5 to Sa7 is repeated.

The processing of steps Sa5 to Sa7 is repeated P times, and the direct reflection component E is obtained for all divided times t1 to tk.
When d, the back scattered light component Ebs, and the forward scattered light component Efs are calculated, the determination in step Sa6 becomes “YES”, and the direct reflection component Ed calculated for all the division times t1 to tk of the pixel A11 and the backward The average value, that is, the direct reflection component average value <Ed>, the backscattered light component average value <Ebs>, and the forward scattered light component average <Efs> are calculated by the scattered light component Ebs and the forward scattered light component Efs, respectively. (Step Sa8). Then, the luminance (reflected light intensity) D11 of the pixel A11 is calculated based on the following equation (step Sa9). D11 = <Ed> / (<Ed> + <Ebs> + <Efs>) (1)

The processing in steps Sa3 to Sa9 described above is performed for all the pixels A11 to Am1 in the horizontal direction by the processing in steps Sa10 and Sa11 described below. That is, in step Sa10, it is determined whether or not the integer i is equal to the integer M indicating the number of divisions of pixels in the horizontal direction. If this determination is "NO", the integer i is incremented in step Sa11, and the processing of steps Sa3 to Sa9 is repeated for the pixel A21 located on the right of the pixel A11.

This series of processing is repeated M times to calculate the luminances D11 to Dm1 for all of the pixels A11 to Am1 in the horizontal direction, and the processing of steps Sa12 and Sa13 is performed for the pixels A12 to Am2 to the pixels A1n to Amn. The luminances D12 to Dmn are calculated for all the pixels arranged in the vertical direction. In this way, the luminances D11 to Dmn are calculated for all the pixels A11 to Amn of the test image, and the processing in step S6 ends.

Subsequently, in step S7, for example, a pixel located at the center of the test image is selected, and a ratio between the maximum value and the minimum value is calculated to calculate a contrast value between a white portion and a black portion of the test image. , Are stored in association with the pixel map. In this case, all the pixels A11 to A11
The contrast value may be calculated by selecting mn and calculating the maximum value and the minimum value of the luminance.

By the above processing, the turbidity c is reduced to the minimum turbidity ca
In addition, the contrast value when the viewing distance R2 is the minimum viewing distance R2a is calculated, and the contrast value is calculated over the entire turbidity range G by the processing of steps S8 and S9. That is, it is determined whether or not the turbidity c is within the turbidity range G, that is, a value from the minimum turbidity ca to the maximum turbidity cb (step S8). If this determination is "NO", the current turbidity is determined. The turbidity step width △ c is added to the degree c (step S9), and the processing from step S6 is repeated.

Further, when the turbidity c exceeds the turbidity range G, the determination in step S7 becomes "YES", and
By the processing of S11, the contrast value is calculated over the entire simulation range of the turbidity range G and the visible distance range H. Then, in step S12, the turbidity c giving the same contrast value and the visible distance R2 are extracted and grouped, and a contrast chart showing the relationship between the visible distance and the turbidity using the contrast value as a parameter is created.
FIG. 5 is a diagram showing an example of the contrast chart.

[0031]

As described above, according to the simulation method of the underwater laser visual recognition device according to the present invention,
The following effects can be obtained. That is, a test image including a plurality of different reference luminance portions is set as a visual target, and the contrast of the test image according to the turbidity of the light propagation medium and the visual distance to the test image based on the reflected light from the test image. Since the value is calculated, by measuring only the turbidity of the light propagation medium at the site where the underwater laser visual recognition device is used and corresponding to the simulation result,
The relationship between the contrast value and the viewing distance for the turbidity can be known. For example, it is possible to estimate in advance how long a viewing distance must be taken when attempting to view a viewing target object with a predetermined contrast value at the site, and determine the installation location and specifications of the underwater laser viewing device.
As a result, there is no need to determine and change the installation location and specifications of the underwater laser visual recognition device on site, and the usability of the underwater laser visual recognition device is greatly improved.

[Brief description of the drawings]

FIG. 1 is a plan view showing an example of a schematic configuration of a laser visual recognition device in a simulation method of an underwater laser visual recognition device according to the present invention.

FIG. 2 is a plan view showing an example of a test image set as a visual recognition target in the simulation method of the underwater laser visual recognition device according to the present invention.

FIG. 3 is a main flowchart showing one embodiment of a simulation method of the underwater laser visual recognition device according to the present invention.

FIG. 4 is a flowchart showing a main part of the main flowchart.

FIG. 5 is a diagram showing an example of a contrast chart generated by simulation in the simulation method of the underwater laser visual recognition device according to the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Irradiation device 2 Imaging device 3 Visual recognition object 4 Light propagation medium c Turbidity △ c Turbidity step width Ed Direct reflection component Ebs Backscattering component Efs Forward scattering component i, j, k Integer M In the horizontal direction (X-axis direction) Number of pixel divisions N Number of pixel divisions in the vertical direction (Y-axis direction) P Number of time divisions R2 Viewing distance △ r Viewing distance step width G Turbidity range H Viewing distance range

──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Kenji Hirose 4-3778 Irifunecho, Niigata City, Niigata Prefecture Inside the Niigata Machinery Maintenance Office, First Port Construction Bureau, Ministry of Transport (72) Inventor Hirotoshi Igarashi 4- Irifunecho, Niigata City, Niigata Prefecture 3778 Inside the Niigata Machinery Maintenance Office, First Port Construction Bureau, Ministry of Transport (72) Inventor Junichi Akizono 3-1-1 Nagase, Yokosuka City, Kanagawa Prefecture Inside the Port and Harbor Research Institute, Ministry of Transport (72) Eiji Sato Nagase, Yokosuka City, Kanagawa Prefecture 3-1-1, Inside the Port and Harbor Research Institute, Ministry of Transport (72) Inventor Toshinari Tanaka 3-1-1, Nagase, Yokosuka City, Kanagawa Prefecture Inside the Port and Harbor Research Institute, Ministry of Transport (72) Yoshiaki Takahashi 2-Toyosu, Toyosu, Koto-ku, Tokyo No. 1-1 Ishikawa Shima-Harima Heavy Industries Co., Ltd., Tokyo No. 1 Factory (72) Inventor Shiro Ishida 3-2-1, Toyosu, Koto-ku, Tokyo Kawashima Harima Heavy Industries, Ltd.Toyosu General Office (72) Inventor Haruwa Asazuma 2-1-1 Toyosu, Koto-ku, Tokyo Ishikawa Shima Harima Heavy Industries, Ltd.Tokyo First Plant (72) Inventor Toshiki Saito Tokyo 3-1-1-15, Toyosu, Koto-ku Ishikawa Shima-Harima Heavy Industries, Ltd. In the Toji Technical Center (56) References JP-A-7-72250 (JP, A) (58) Fields investigated (Int. Cl. ⁶ , DB G01S 17/00-17/95 G01S 7/40 G09B 9/54-9/56

Claims (6)

(57) [Claims] 1. A simulation for generating an output image of a laser viewing device that irradiates a laser pulse to a visual target arranged in a light propagation medium and captures reflected light of the laser pulse to obtain an image of the visual target. A method, wherein a test image including a plurality of different reference luminance portions is set as the viewing target object, and the turbidity of the light propagation medium and a viewing distance to the test image are determined based on reflected light from the test image. A method for simulating an underwater laser visual recognition device, comprising: calculating a contrast value of a test image obtained. 2. The simulation method for an underwater laser visual recognition device according to claim 1, wherein a test image having a black stripe formed on a white background is used. 3. The underwater image according to claim 1, wherein the test image is divided into a plurality of pixels, and a contrast value is calculated based on a maximum value and a minimum value of reflected light obtained from each pixel. Simulation method of laser visual recognition device. 4. The method according to claim 1, wherein a direct reflected light component, a back scattered light component, and a forward scattered light component are calculated for the reflected light, and a contrast value is calculated based on each of the components. The simulation method of the underwater laser visual recognition device according to any one of the above. 5. When the laser viewing device captures reflected light of a laser pulse via a shutter, the laser aperture is divided into a plurality of time sections, and a contrast value is determined based on an average value of reflected light in each time section. The simulation method of the underwater laser visual recognition device according to any one of claims 1 to 4, wherein the calculation is performed. 6. The simulation method for an underwater laser visual recognition device according to claim 1, wherein a contrast value is calculated based on reflected light obtained from a central portion of the test image.