JP2008268183A - Underwater detection device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an underwater detection device capable of automatically tracking multiple adjacent shoals of fish as an identical shoal of fish. <P>SOLUTION: An underwater detection device that detects a shoal of fish based on the echoes, obtained through underwater detection by transmission and reception of ultrasonic waves, and for causing a screen to display an echo image of the shoal of fish thus detected includes binarization means for binarizing the echo data, based on the threshold; and a labeling means for performing labeling process on the echo data binarized by the binarizing means. The underwater detection device automatically tracks multiple adjacent shoals of fish as an identical shoal of fish, based on the result of the labeling process. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an underwater detection device such as a scanning sonar, and more particularly to an underwater detection device having a function of automatically tracking a school of fish.

  Scanning sonar transmits an ultrasonic beam from the transducer at a specified tilt angle in all directions in the water, receives the eco from the fish by horizontal scanning, and displays the fish image based on the echo It is an underwater detection device. When underwater detection is performed with scanning sonar, a wide detection area can be obtained, so a wide range of underwater information can be acquired.

  By the way, in fishing, it is important not only to know the position of the school of fish, but also to know the direction and speed of movement of the school of fish in order to set the net accurately. For this reason, a scanning sonar having a function of automatically tracking a school of fish has been put into practical use. For example, Patent Document 1 below discloses a scanning sonar that performs automatic tracking with a target lock. To perform automatic tracking with the target lock type sonar, the target lock mark is inserted at the position of the fish echo displayed on the screen by operating the operation unit. When auto-tracking starts, for sonar with horizontal and vertical modes, the tilt angle of the horizontal mode is adjusted based on the position of the target lock mark in the vertical mode, and the beam is launched toward the mark position . Then, the echo reflected by the fish school is scanned and received, the position of the fish school is detected from the echo near the mark position, and this position is set as a new target lock mark position. Automatic tracking is performed by repeating such an operation, and the movement trajectory of the fish school is displayed on the screen as time passes.

JP 2003-315453 A

  A school of fish is a collection of a large number of fish, so its shape, size, etc. are not constant, but it is fluid and changes over time. For this reason, the echo image of a school of fish may follow temporal changes as shown in FIGS. 21 (a) to (c), for example. In the example of FIG. 21, a single fish echo A shown in (a) is then separated into two echoes B and C as shown in (b) and then again into a single echo D as shown in (c). I'm back. Here, FIG. 21 (b) shows a case where a part of the school of fish happens to be separated from the school, and these two echoes B and C are originally obtained from the same school of fish.

  However, when tracking a school of fish based on echoes as shown in FIG. 21, if it is determined only by the center-of-gravity movement distance, A → B → D is tracked and C is not tracked. However, in the conventional technique, when tracking a plurality of fish schools, B and C are tracked as different fish schools, so it is determined from the area and signal intensity which echo is the same as the previous school. It is necessary to track. Further, when trying to display / accumulate fish school information, the information differs greatly between A → B → D tracking and A → C → D tracking.

  The present invention solves the above-described problems, and an object thereof is to provide an underwater detection apparatus capable of automatically tracking a plurality of adjacent fish schools as the same fish school.

  An underwater detection device according to the present invention is an underwater detection device that detects a school of fish based on echoes obtained by underwater detection by transmission and reception of ultrasonic waves, and displays an echo image of the detected fish school on a screen. Binarization means for binarization based on a threshold value, and labeling means for performing a labeling process on the echo data binarized by the binarization means. Then, based on the result of the labeling process, a plurality of adjacent fish schools are automatically tracked as the same fish school.

  In this way, even if a single school of fish is separated into a plurality of fish, these multiple school of fish can be tracked as a single school of fish. Obtainable. Moreover, since the fish school can be accurately tracked, the accuracy of the fish school information acquired from the fish school is improved. Further, in the present invention, a school of fish is automatically searched, detected, labeled, and tracked in the detection area, so that a plurality of school of fish can be automatically detected without performing the target lock operation as in Patent Document 1. Can be tracked automatically.

  The present invention further includes contraction / expansion processing means for performing contraction and expansion processing on the echo data binarized by the binarization means. The contraction / expansion processing means performs contraction / expansion processing on the binarized data using an irregular neighborhood in which the number of neighboring data in one direction is larger than the number of neighboring data in the other direction. If an anomaly is used for the contraction / expansion process, a portion with a low signal level between the echoes is also determined as a school of fish, so the school of fish echoes are displayed in a connected state. In addition, a portion with a low signal level is also subject to calculation of fish school information.

  In the present invention, when performing binarized data labeling processing, the anomaly vicinity described above may be used. If an anomaly is used for the labeling process, the portion with a low signal level between the echoes is not determined as a fish school, so the fish echoes are displayed separately. In addition, a portion with a low signal level is not a target for calculating fish school information.

  In the present invention, the labeling means calculates fish school information including at least one of the area, echo signal intensity, and shape of the fish school during the labeling process, and the fish information obtained by the computation is calculated for each fish school. indicate. According to this, this data can be used as resource information by displaying the fish school information in numerical form. Also, by accumulating this data, it is possible to accurately analyze the amount of resources and their fluctuations.

  Moreover, in this invention, the matching means which matches with the fish school information obtained by the labeling process until the last time and this fish school information is further provided. The matching means determines that the fish school is a true fish school when matching is obtained a predetermined number of times or more, and determines that the fish school is a temporary fish school when matching is not obtained more than a predetermined number of times. According to this, since a true fish school and a temporary fish school can be distinguished and extracted, even an inexperienced person can correctly identify a true fish school.

  Further, in the present invention, the true fish school is classified into a detected fish school that is still detected and a lost fish school that is not currently detected by the matching means, and the temporary fish school, the detected fish school, and the lost fish school, respectively. It is preferable to display in different colors. According to this, in the true fish school, the currently detected fish school and the lost fish school not currently detected can be discriminated clearly. Lost school of fish is often detected again after a lapse of time even if it is not detected once out of the detection area, and the position of the lost school of fish can be predicted by making it possible to identify the lost school of fish by color. .

  In the present invention, a mark indicating the size and moving direction of the fish school based on the fish school information may be added to the echo image of the fish school and displayed. By adding such a mark to the echo image, the fish school information is visualized and becomes easier to understand.

  ADVANTAGE OF THE INVENTION According to this invention, the underwater detection apparatus which can track automatically the several fish school which adjoined as the same fish school can be obtained.

  FIG. 1 is a system configuration diagram showing an embodiment of the present invention. 1 is a scanning sonar that detects underwater and displays an echo image, 2 is a navigation device composed of GPS, a gyro, and the like, 3 is a depth-measuring device that measures the depth in water, and 4 is a flow velocity and direction of tidal current. It is a tide meter.

  FIG. 2 shows the principle of detecting underwater using scanning sonar. In the figure, 1 is the above-described scanning sonar, which is mounted on the ship 5. Reference numeral 6 denotes a transmitter / receiver provided in the scanning sonar 1, reference numeral 7 denotes an ultrasonic transmission beam transmitted from the transmitter / receiver 6 to the water, and reference numeral 8 denotes a reception beam for receiving an echo reflected by a fish group in the water. is there. 9 represents the water surface. The transmission beam 7 is transmitted simultaneously from the transmitter / receiver 6 in all directions in the water at a certain depression angle (tilt angle) to form an omnidirectional umbrella beam. The reception beam 8 is a beam having directivity formed by scanning the transducer 6 in the circumferential direction, and rotates 360 ° in a spiral at a high speed. By receiving echoes with the reception beam 8 and analyzing the received signal, underwater information such as the distribution status and movement of fish over a wide area can be obtained. Note that the navigation device 2, the sounding device 3, and the tide meter 4 shown in FIG. 1 are also mounted on the ship 5.

  FIG. 3 is a block diagram showing an electrical configuration of the scanning sonar 1. Reference numeral 10 denotes an element (ultrasonic transducer) that constitutes the above-described transducer 6, and one transmission / reception channel Ch (Ch 1, Ch 2, Ch 3...) Is provided for each element 10. Since the configuration of each transmission / reception channel is the same, the transmission / reception channel Ch1 will be described below. In the transmission / reception channel Ch1, 11 is a transmission / reception switching circuit that switches between transmission and reception operations, 12 is a transmission circuit that applies a pulse-width modulated transmission signal to the element 10, and 14 is amplification and noise removal for the signal received by the element 10 15 is an A / D converter that converts a received signal output from the receiving circuit 14 into a digital signal, and 16 and 17 are interfaces for transmitting and receiving signals to and from subsequent circuits. It is.

  A transmission beam forming unit 18 calculates a delay amount, a weight value, and an azimuth angle of each channel for each transmission cycle, and forms a transmission beam for each channel. An operation unit 19 operates a key, a dial, or the like provided on the operation unit 19 to set a range, input a tilt angle or azimuth, and set automatic tracking on / off. Reference numeral 20 denotes a host CPU as a control unit that controls the entire operation of the scanning sonar 1. A reception beam forming unit 21 calculates the phase and weight of the reception signal output from each element 10 and combines the signals to obtain a combined reception signal. An image processing unit 22 performs echo display processing, which will be described later, based on echo data obtained by detecting and sampling the reception signal output from the reception beam forming unit 21.

  Reference numeral 23 denotes a display unit composed of, for example, a liquid crystal display, which displays underwater information such as a school of fish in the detection area as an echo image based on the image data generated by the image processing unit 22. Reference numeral 24 denotes a memory constituting a storage unit, which stores a display program 25 for displaying an echo image. In addition, the memory 24 is provided with a fish information area 26 in which fish information described later is stored. In addition to this, the memory 24 is provided with storage areas for various programs, control parameters, and the like, but they are not shown because they are not directly related to the present invention.

  In the above, the scanning sonar 1 constitutes an embodiment of the underwater detection device in the present invention, and the image processing unit 22 in FIG. 3 includes the binarization unit, the contraction / expansion processing unit, the labeling unit, and the matching unit in the present invention. One embodiment is configured.

  Although not shown in FIG. 3, the navigation device 2, the sounding device 3, and the tide meter 4 shown in FIG. 1 are connected to the scanning sonar 1. In addition, a fluctuation sensor for detecting the fluctuation of the ship and controlling the transmission / reception beam to always face a predetermined direction is also connected. A known device can be used for each of these devices.

  FIG. 4 is a flowchart showing an echo image display procedure in the scanning sonar 1 described above. The details of the process of displaying an echo image will be described below according to this flowchart.

  First, in step S1, binarized data is initialized. The binarized data here refers to binary data of the echo level of each coordinate point in a data area (not shown) secured in the memory 24. These data are all reset to 0 by the initialization process.

  Next, in step S2, level conversion processing is performed. The level conversion process is a process of detecting the sea bottom and reducing the level of the echo signal from the sea bottom in order not to erroneously detect sea bottom echo or the like as a school of fish. In step S2, filter processing for removing noise may also be performed. Setting of these processes is performed in the operation unit 19.

  Subsequently, in step S3, a mask outside the detection range is set for the binarized data. FIG. 5 shows an example of setting the out-of-detection range mask. R1 is a region where the fish school detection process is performed, and R2 to R4 are areas where the fish school detection process is not performed. A mask outside the detection range is set in R2 to R4. R2 is a region affected by an oscillation line near the bottom of the ship, R3 is a region where echoes of the sea bottom are detected, and R4 is a region affected by stern propeller noise. By masking these regions, fish detection processing is not performed for the regions R2 to R4, and erroneous detection of the fish school can be prevented. In addition to R2 to R4, for example, a mask may be set in a portion where a virtual image such as a seabed due to a grating lobe occurs. The area outside the detection range mask can be arbitrarily set by the user using the operation unit 19. Moreover, the detection end depth of FIG. 5 can also be automatically set using the water depth data acquired by the depth measuring device 3 of FIG. Even in the masked portion, the echo is received and displayed.

  Next, in step S4, binarization processing is performed on the received echo data, that is, unmasked data, using a preset threshold value. In this process, the signal level of the echo at each coordinate point is compared with a threshold value, and “1” is assigned if the signal level is greater than or equal to the threshold value, and “0” is assigned if the signal level is less than the threshold value.

  Subsequent to the binarization processing, in step S5, data contraction / expansion processing is performed. FIG. 6 is a diagram for explaining the principle of the contraction / expansion process. The expansion process is a process for setting a pixel of interest to “1” if there is at least one “1” in the pixel itself or in the neighborhood data (neighboring pixels) of the pixel. If there is at least one “0” in the pixel itself or in the neighborhood data (neighboring pixel) of the pixel for a certain pixel of interest, this is processing for setting the pixel of interest to “0”. Use of a combination of expansion processing and contraction processing has the effect of eliminating holes in the binarized image. For example, when the dilation processing is performed on each pixel of the binarized image as shown in FIG. 6 (a) using four neighborhoods as shown in (b), an image as shown in (c) is obtained. ) Can eliminate holes in the image that existed. Then, when a contraction process using four neighborhoods is performed on each pixel of the image of (c), an image as shown in (d) is obtained. In (d), the broken line pixel becomes “0” by the contraction process, and the image is reduced so as to have the same contour as in (a), but the state without a hole is maintained as it is.

  FIG. 10 shows an example of an echo image displayed on the screen of the display unit 23 through the binarization process and the contraction / expansion process described above. This image represents a horizontal image obtained by the horizontal scan shown in FIG. The same applies to the subsequent image examples. A portion surrounded by a white circle in the figure is an echo image of a school of fish (exactly a fish school candidate), and this echo image is displayed in pink, for example. The user can arbitrarily set the threshold while viewing this screen. When the threshold is changed, all the processes are performed again, and when the binarization result is displayed, the binarized echo image is immediately displayed.

  Next, in step S6, a labeling process is performed on the binarized echo data. In the labeling process, an ID number is assigned to each echo and a display color is assigned. It also calculates fish school information such as the center of gravity coordinates, area, average signal strength, shape (circularity) of the fish school. Then, each obtained fish school information is weighted, and the school of fish is extracted based on the result.

  FIG. 11 shows an example of an echo image that has undergone labeling processing. A portion surrounded by a white circle in the figure is an echo image of a fish school (fish school candidate), and this echo image is displayed in orange, for example. When other fish schools are detected, they are displayed in different colors such as light blue and yellow. The user can perform labeling settings (specifically, what kind of neighborhood is used) while viewing this screen. When the setting is changed, all the processes are performed again, and when the labeling result is displayed, the echo image after the labeling is immediately displayed.

  By the way, in the labeling process, in order to treat a plurality of adjacent fish schools as the same fish school, an irregular neighborhood having a larger number of neighboring data in one direction than the number of neighboring data in the other direction is used. For example, with respect to three echo images that are close to each other in the distance direction (radiation direction of the beam) as shown in FIG. 7, the normal four neighborhoods shown in FIG. 8A or the one shown in FIG. If the normal 8 neighborhood is used, the echoes are labeled separately and detected as three school of fish. Therefore, in order to determine that this echo is a single school of fish and can be tracked, the vicinity of anomaly 4 as shown in FIG. 9A or the vicinity of an anomaly 8 as shown in FIG. 9B is used. In the vicinity of the anomaly used here, the number of neighboring data in the distance direction is larger than the number of neighboring data in the azimuth direction.

  When using the irregular neighborhood described above, one labeling target area is expanded in the distance direction as compared with the case of the normal 4 neighborhood or 8 neighborhood, so that the three echoes that are close to each other with an interval as shown in FIG. The same labeling process is also performed. That is, the same ID number is assigned to three fish schools, and these fish schools are handled as one fish school. And by this labeling process, the echo image of each fish school is displayed with the same color, and three fish school can be automatically tracked as one fish school. The irregularity degree in the vicinity of the irregularity (ratio of the neighborhood data added to the normal neighborhood) can be arbitrarily set by the user using the operation unit 19.

  The vicinity of the irregularity may be used in the above-described contraction / expansion process. In this case, since the region of the contraction / expansion processing for the binarized data is expanded in the distance direction as compared with the case of the normal vicinity of 4 or 8, the blank portion between the echoes in FIG. ) Is also judged as a school of fish. For this reason, when calculating fish school information, this blank portion is also considered. On the other hand, when an irregular neighborhood is used in the labeling process, there is no contraction / expansion of the binarized data, so the blank part between each echo in FIG. 7 is not judged as a fish school, and only the black part is judged as a fish school. become. Accordingly, blank portions are not considered in calculating fish school information.

  Hereinafter, an example of an image that has been subjected to processing based on the vicinity of anomalies will be described. FIG. 12 is an echo image before coloring by labeling. Two fish schools are displayed in the white circles in the figure. FIG. 13 shows the result of labeling the echo image of FIG. 12 using a normal neighborhood (for example, 4 neighborhoods). In the white circle in the figure, two fish echoes are displayed, one in red and the other in light blue. That is, the two echoes are labeled separately and are judged to be different schools of fish.

  FIG. 14 is an echo image when the vicinity of anomalies is used for the contraction / expansion process. Two fish echoes are displayed in orange in the white circle in the figure. In this case, the two echoes are labeled as one echo and are judged to be the same school of fish. However, as described above, the part where the signal level between the echoes is low is also judged to be a school of fish, so the two school echoes are connected. It is in a state.

  FIG. 15 is an echo image when an irregular neighborhood is used for the labeling process. Two fish echoes are displayed in orange in the white circle in the figure. In this case, the two echoes are labeled together and are considered to be the same school of fish, but the portion with the low signal level between the echoes is not considered to be a school of fish, so unlike FIG. 14, the two school echoes are clearly separated. ing.

  After the labeling process as described above, a matching process is performed in step S7 of FIG. In the matching process, the previous school of fish information obtained by the labeling process and the current school of fish information are matched. In this case, the fish speed limit value is set, the fish movement range is obtained from the previous reception time and the current reception time, and the fish center of gravity movement distance is within this fish movement range, for example, Find the ratio of the previous value and current value such as the area, average signal strength, and shape (circularity) of the school of fish, add the weights to the obtained ratios, and calculate the similarity. Are considered to be the same school of fish, and matching is obtained. When the matching is obtained a predetermined number of times (for example, five times) or more, the fish school is determined to be a true fish school. In addition, when the matching is not obtained a predetermined number of times or more, the fish school is determined as a temporary fish school. By doing so, the true fish school and the temporary fish school can be distinguished and extracted, so that even the inexperienced person can accurately identify the true fish school.

  By the way, even if it is determined to be a true school of fish, the school of fish may deviate from the beam range of the detection area and may not be detected. Therefore, a true school of fish has been matched more than a predetermined number of times and is still detected (hereinafter referred to as “detected fish school”), and a matching has been obtained more than a predetermined number of times, but it is currently detected. There is no school of fish (hereinafter referred to as “lost school of fish”). A temporary fish school that has not been matched a predetermined number of times or more may be referred to as a “fish school candidate” below.

  Thus, when the true fish school and the temporary fish school are determined by the matching processing, next, in step S8, the fish information obtained by the calculation is displayed on the screen on which the echo image is displayed, A mark indicating the size and moving direction of the school of fish based on the school of fish information is added to the echo image and displayed.

  FIG. 16 shows an example of the school of fish information displayed in step S8. This fish school information is all digitized and can be used as resource information. In FIG. 16, the # column at the left end in FIG. 16 displays the color assigned for each echo in the labeling process, making it easy to understand the correspondence between the school of fish displayed in the echo image and the data of that school of fish. . In the ID column next to it, the ID number assigned for each echo in the labeling process is also displayed. Here, the 1-digit ID number represents a true fish school, and the 10-digit ID number represents a temporary fish school (fish school candidate).

  In addition to the fish school information of FIG. 16, fish school information as shown in FIG. 17 may be displayed. In FIG. 17, the movement direction, the fish speed, the predicted position, etc. are displayed for those determined to be true fish schools, and the detailed history information is displayed for the fish schools with the ID selected in the upper column. ing. In addition, about the position (latitude / longitude) of a school of fish, you may use the smoothing position which is a spatial internal dividing point of the last position and this position as shown in the said patent document 1. FIG. The predicted position may be obtained from the previous detected position and the last detected position. However, when data is accumulated and obtained from the first detected position and the last detected position, the prediction accuracy is improved. Furthermore, if it calculates | requires from the approximate curve with respect to all the detected points, prediction accuracy will improve more.

  In this way, by displaying the fish school information as a list in numerical form, this data can be used as resource information. Also, by accumulating this data, it is possible to accurately analyze the amount of resources and their fluctuations. Note that the fish school information does not necessarily have to be all the information shown in FIGS. 16 and 17, and may be information including at least one of the fish school area, echo signal intensity, and shape.

  FIG. 18 shows an example in which a mark M indicating the size and moving direction of the fish school is added to the echo image and displayed in step S8. This mark M is drawn with a fish illustration, and the size of the fish indicates the size of the school of fish, and the direction of the fish face indicates the direction of movement of the school of fish. Further, the detected fish school is displayed in different colors such as red, the lost fish school is orange, and the fish school candidate is gray. By adding such a fish mark M to the echo image, the school of fish information is visualized and becomes easier to understand.

  In addition, among the true fish school, the currently detected fish school and the lost fish school not currently detected can be distinguished at a glance. Lost school of fish is often detected again after a lapse of time even if it is not detected once out of the detection area, and the position of the lost school of fish can be predicted by making it possible to identify the lost school of fish by color. . In addition, you may make it display the movement locus | trajectory of the school of fish as shown in patent document 1 on the screen of FIG.

  FIG. 19 shows another display example of the fish mark, in which the fish mark M is added to the echo image when the echo image at each point is updated and displayed as the ship moves. In this case, as shown in FIG. 20, the echo hidden under the mark M may be made visible by increasing the transparency of the mark M.

  As described above, according to the above-described embodiment, even when a single school of fish is divided into a plurality of fish as shown in FIG. 21B, these multiple school of fish are displayed in the same color on the screen. Therefore, it is possible to obtain a highly reliable device without being erroneously tracked. Moreover, since the fish school can be accurately tracked, the accuracy of the fish school information acquired from the fish school is improved. Furthermore, since a school of fish is automatically searched, detected, labeled, and tracked in the detection area, the user does not need to set a target lock mark as in Patent Document 1 for automatic tracking.

  In the present invention, various embodiments other than those described above can be adopted. For example, in the fish mark display shown in FIGS. 18 to 20, the transparency of the fish candidate mark is decreased as the number of detections is increased so that the color of the mark gradually becomes darker or the mark of the lost fish school mark is changed. The transparency may be increased as the number of detections is increased, so that the color of the mark gradually becomes lighter.

  In the above embodiment, the anomaly neighborhood has an extension region in the distance direction, but the anomaly neighborhood has an extension region in the azimuth direction, or has an extension region in both the distance direction and the azimuth direction. It may be a thing.

  In the above-described embodiment, the vicinity of the anomaly 4 and the vicinity of the anomaly 8 are given as examples of the anomaly vicinity.

  Further, instead of using the irregular neighborhood, the distance between the echoes may be determined, and when this distance is equal to or less than a certain value, the same labeling process may be performed on each echo.

  In the above embodiment, the case where an echo image is displayed on the display unit 23 of the scanning sonar 1 has been described. However, a PC (personal computer) is connected to the scanning sonar 1 and the echo image is displayed on the monitor of the PC. It may be. Alternatively, data collected by the scanning sonar 1 in the ship may be recorded on a recording medium such as an optical disk, and this recording medium may be mounted on a PC installed at another location for data analysis.

  Furthermore, in the above embodiment, the scanning sonar is taken as an example of the underwater detection device, but the present invention can be applied to an underwater detection device such as a fish finder in principle.

It is a system configuration figure showing an embodiment of the present invention. It is the figure which showed the principle which detects underwater with a scanning sonar. It is the block diagram which showed the electrical structure of the scanning sonar. It is the flowchart which showed the display procedure of the echo image. It is the figure which showed the example of a setting of a mask outside a detection range. It is a figure explaining the principle of contraction expansion processing. It is the figure which showed the echo by several fish school. It is the figure which showed 4 neighborhood and 8 neighborhood. It is the figure which showed the anomaly 4 vicinity and the anomaly 8 vicinity. It is an example of the echo image which passed through the binarization process and the contraction expansion process. It is an example of the echo image which passed through the labeling process. It is an echo image before coloring by labeling. It is an echo image at the time of labeling using the normal vicinity. It is an echo image at the time of using an irregular vicinity for a contraction expansion process. It is an echo image at the time of using an irregular neighborhood for labeling processing. It is an example of the fish school information displayed. It is another example of fish school information. This is an example in which a fish mark is added to an echo image and displayed. It is another example of a display of a fish mark. It is another example of a display of a fish mark. It is a figure which shows the echo image of the isolate | separated fish school.

Explanation of symbols

1 Scanning sonar (underwater detector)
6 Transmitter / Receiver 7 Transmit Beam 8 Receive Beam 22 Image Processing Unit 23 Display Unit 50 Fish M Mark

Claims (7)

In an underwater detection device that detects a school of fish based on echoes obtained by underwater detection by transmission and reception of ultrasonic waves, and displays an echo image of the detected school of fish on the screen,
Binarization means for binarizing the echo data based on a threshold;
Labeling means for performing a labeling process on the echo data binarized by the binarization means,
An underwater detection apparatus, wherein a plurality of adjacent fish schools are automatically tracked as the same school based on the result of the labeling process. The underwater detection device according to claim 1,
A contraction / expansion processing means for performing contraction and expansion processing on echo data binarized by the binarization means;
The underwater detection device, wherein the contraction / expansion processing means performs contraction / expansion processing of binarized data using an irregular neighborhood in which the number of neighboring data in one direction is larger than the number of neighboring data in the other direction. The underwater detection device according to claim 1,
The underwater detection device, wherein the labeling means performs a labeling process on the binarized data using an irregular neighborhood in which the number of neighboring data in one direction is larger than the number of neighboring data in the other direction. The underwater detection device according to claim 1,
The labeling means calculates fish school information including at least one of the area of the fish school, the echo signal intensity, and the shape during the labeling process,
An underwater detection device that displays fish school information obtained by the calculation for each school of fish. The underwater detection device according to claim 4,
It further includes a matching means for performing matching between the previous fish school information obtained by the labeling process and the current fish school information,
The matching means determines that the fish school is a true fish school when matching is obtained a predetermined number of times or more, and determines that the fish school is a temporary fish school when the matching is not obtained more than a predetermined number of times. Underwater detection device. The underwater detection device according to claim 5,
The matching means classifies the true fish school into a detected fish school that is still detected and a lost fish school that is not currently detected,
The underwater detection device, wherein the temporary fish school, the detected fish school, and the lost fish school are displayed in different colors. The underwater detection device according to claim 4,
An underwater detection apparatus, wherein a mark indicating the size and moving direction of a fish school based on the fish school information is added to an echo image of the fish school and displayed.

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