Object detection device, object detection method, and recording medium

Abstract

Provided is a configuration capable of suppressing unnecessary detection of an object on a curve or the like.　This object detection device is provided with: a first acquisition unit for acquiring an image; a second acquisition unit for acquiring road information or sensor information at a position corresponding to the image; a region determination unit for determining, on the basis of the road information or the sensor information, a region in the image that serves as an object detection range; and an object detection unit for detecting an object in the region.

Description

Object detection device, object detection method, and recording medium

[0001] The present invention relates to an object detection device, an object detection method, and a recording medium.

[0002] There is known an object detection device that sets a certain area in an image captured by a camera and detects an object in that area. For example, Patent Document 1 discloses an example of an object detection device that can appropriately detect an object such as a vehicle ahead. More specifically, the publication describes that the object detection device includes a search area determination unit that determines an area in the image that includes a road surface as a search area, and that the search area determination unit determines the search area based on white lines on the road.

[0003] JP 2017-68700 A

[0004] When an image from which an object is detected is taken by a camera or the like fixed to a moving object, there is a problem that unnecessary objects may appear in the image when the vehicle is around a curve or the like.

[0005] An object of the present disclosure is to provide an object detection device, an object detection method, and a recording medium that are capable of suppressing the detection of unnecessary objects on curves and the like.

[0006] According to a first aspect, there is provided an object detection device comprising: a first acquisition unit that acquires an image; a second acquisition unit that acquires road information or sensor information of a position corresponding to the image; an area determination unit that determines an area in the image that is a detection range for an object based on the road information or the sensor information; and an object detection unit that detects an object within the area.

[0007] According to a second aspect, an object detection method is provided, which acquires an image and road information or sensor information of a position corresponding to the image, determines an area in the image that is a detection range for an object based on the road information or the sensor information, and detects an object within the area.

[0008] According to a third aspect, there is provided a recording medium having recorded thereon a program that causes a computer to execute the following processes: a process of acquiring an image and road information or sensor information of a position corresponding to the image; a process of determining an area in the image that is a detection range for an object based on the road information or the sensor information; and a process of detecting an object within the area.

[0009] The present disclosure can contribute to providing a configuration that can suppress the detection of unnecessary objects on curves, etc.

[0010] FIG. 1 is a diagram illustrating one configuration of the present disclosure. FIG. 2 is a flowchart illustrating the operation of the present disclosure. FIG. 3 is a diagram illustrating an example of an object detection area. FIG. 4 is a diagram illustrating another example of an object detection area. FIG. 5 is a diagram illustrating an example of setting an object detection area according to the present disclosure. FIG. 6 is a diagram illustrating one configuration of the present disclosure. FIG. 7 is a diagram illustrating an example of road information held by an object detection device of the present disclosure. FIG. 8 is a flowchart illustrating the operation of the present disclosure. FIG. 9 is a diagram illustrating another example of setting an object detection area according to the present disclosure. FIG. 10 is a diagram illustrating another configuration of the present disclosure. FIG. 11 is a flowchart illustrating the operation of the present disclosure. FIG. 12 is a diagram illustrating operation plan information held by an object detection device of the present disclosure. FIG. 13 is a diagram illustrating the operation of the present disclosure. FIG. 14 is a diagram illustrating the operation of the present disclosure.

[0011] First, an overview of one embodiment of the present disclosure will be described with reference to the drawings. In this disclosure, the drawings relate to one or more embodiments. The reference numerals in the drawings attached to this overview are attached to each element for convenience as an example to facilitate understanding, and are not intended to limit the present disclosure to the illustrated form. Furthermore, connecting lines between blocks in the drawings and the like referred to in the following description include both bidirectional and unidirectional lines. Unidirectional arrows are used to schematically indicate the flow of main signals (data) and do not exclude bidirectionality. A program is executed via a computer device, which includes, for example, a processor, a storage device, an input device, a communication interface, and, if necessary, a display device. Furthermore, this computer device is configured to be able to communicate with internal or external devices (including computers) via the communication interface, whether wired or wireless. Although ports or interfaces are present at the input / output connection points of each block in the drawings, they are not shown.

[0012] In one embodiment, the present disclosure can be realized by an object detection device 10 including a first acquisition unit 11, a second acquisition unit 12, a region determination unit 13, and an object detection unit 14, as shown in FIG. 1 . More specifically, the first acquisition unit 11 acquires an image. The second acquisition unit 12 acquires road information or sensor information for a position corresponding to the image. The region determination unit 13 determines a region in the image that is a detection range for an object, based on the road information or the sensor information. The object detection unit 14 detects an object within the region.

[0013] The object detection device 10 configured as above operates as follows: First, the object detection device 10 acquires an image for object detection using the first acquisition unit 11 (step S01 in FIG. 2).

[0014] Next, the object detection device 10 acquires road information or sensor information for the position corresponding to the image (step S02 in FIG. 2).

[0015] Next, the object detection device 10 determines an area in the image that is a detection range for an object based on the road information or the sensor information (step S03 in FIG. 2).

[0016] Finally, the object detection device 10 detects an object within the area (step S04 in FIG. 2).

[0017] 3 to 5 are diagrams illustrating a method for determining an object detection range according to the present disclosure. The shaded area in Fig. 3 indicates an object detection area set on a straight road. In this case, the object detection device 10 can appropriately detect a pedestrian P on the path.

[0018] The shaded area in Fig. 4 indicates an object detection area set by an object detection device that does not include the second acquisition unit 12 and the area determination unit 13. As shown in Fig. 4, the same area as in Fig. 3 is applied to the road that curves to the right. In this case, the object detection device will detect a pedestrian P who is not on the path.

[0019] 5 shows an object detection area set by the object detection device 10 including the second acquisition unit 12 and the area determination unit 13 of the present disclosure. As shown in FIG. 5, the object detection device 10 of the present disclosure sets an area that curves to the right along the road for a road that curves to the right, based on road information or the sensor information. In this way, the area determination unit 13 sets the area along the road on the image based on the road information or the sensor information, allowing the object detection device 10 to appropriately detect objects that are not on the path.

[0020] 3 to 5, for straight roads, a substantially triangular region with its vertex at the vanishing point is set, and for curved roads, a region with a curved tip that matches the curvature is set, but the method of setting the region is not limited to this. The region for object detection can be changed as appropriate depending on the type of object to be detected. For example, if it is desired to more accurately detect pedestrians walking on the sidewalk, the regions shown in FIGS. 3 and 5 can be expanded toward the sidewalk, respectively, to more accurately detect pedestrians on the sidewalk.

[0021] As described above, according to the present disclosure, it is possible to prevent the object detection device 10 from detecting unnecessary objects on curves and the like.

[0022] [First embodiment] Next, a first embodiment in which the present disclosure is applied to a vehicle equipped with a camera will be described. Fig. 6 is a diagram showing one configuration of the present disclosure. Referring to Fig. 6, a vehicle V is shown equipped with an object detection device 100 including a camera C, a GPS, a road information storage unit 102, an area determination unit 103, an object detection unit 104, and a display unit 105.

[0023] The camera C captures an image in the traveling direction of the vehicle V (moving body). Therefore, the camera C corresponds to the first acquisition unit 11.

[0024] Map information including road shapes is stored in the road information storage unit 102. Fig. 7 shows an example of road information stored in the road information storage unit 102.

[0025] The region determination unit 103 uses the position information obtained from the GPS and the traveling direction, which is a change over time, to identify the shape of the road ahead of the vehicle V, and uses the result to determine a region that will be a detection range for an object in the image. For example, if the road ahead of the vehicle V is a straight road, the region determination unit 103 determines a region having the hatched shape in FIG. 3. Also, for example, if the road ahead of the vehicle V curves to the right, the region determination unit 103 determines a region having the hatched shape in FIG. 5. The region determination unit 103 notifies the object detection unit 104 of the determined region. In the example of FIG. 6, the region determination unit 103 is configured to include the second acquisition unit 12 described above.

[0026] The object detection unit 104 uses a previously created inference model to perform object detection processing on the area determined by the area determination unit 103 in the image captured by the camera C, thereby detecting the object. This inference model is learned and tuned using previously prepared training data, and is generated so that it can detect various objects in the image. The object detection method used by the object detection unit 104 is not limited to this, and for example, a method of detecting an object using a difference image or a frame difference may also be used. When the object detection unit 104 detects an object that is a previously set notification target, it displays information about the object on the display unit 105.

[0027] The display unit 105 displays the object detection results and associated information notified by the object detection unit 104. As the display unit 105, for example, a display device of a car navigation terminal or a driving assistance system mounted on the vehicle V can be used.

[0028] Next, the operation of this embodiment will be described in detail with reference to the drawings. Fig. 8 is a diagram showing the operation performed at predetermined time intervals in object detection device 100 according to one configuration of the present disclosure. Referring to Fig. 8, object detection device 100 acquires a camera image from camera C (step S001).

[0029] Next, the object detection device 100 acquires road information and GPS information (location information) (step S002). Because it is necessary to determine the direction of travel, it is desirable to retain the GPS information (location information) for a certain period of time or to acquire the GPS information (location information) multiple times in step S002. Of course, instead of using the change in the GPS information (location information) over time, the direction of travel may be identified using the value of a direction sensor.

[0030] Next, the object detection device 100 refers to the GPS information (location information) and road information corresponding to the direction of travel of the vehicle V, identifies the shape of the road ahead of the vehicle V, and uses the results to determine the area that will be the detection range for the object in the image (step S003).

[0031] Next, object detection device 100 performs an object detection process on the determined region to detect an object (step S004).

[0032] If an object is detected in step S004, object detection device 100 displays information about the detected object on display unit 105. If an object cannot be detected, object detection device 100 omits displaying information on display unit 105, or displays on display unit 105 that the route is safe.

[0033] The operation of the object detection device 100 will be described with reference to Figures 5, 7, and 9. For example, when vehicle V reaches position A in Figure 7, object detection device 100 determines from road information and GPS information (location information) that there is an intersection ahead, and sets the area shown in Figure 9. In the example of Figure 9, in addition to the road surface in the straight-ahead direction, an area is set that extends to the areas where crosswalks are located on both sides of the intersection. Setting such an area makes it possible to quickly detect the presence of pedestrian P at intersections where accidents are likely to occur.

[0034] Similarly, when vehicle V reaches position B in Fig. 7, object detection device 100 determines that there is a right curve ahead and sets the area shown in Fig. 5. As described above, by setting such an area, it becomes possible to detect fallen objects and the like on the true path of the vehicle and to exclude pedestrians P who are not in the vehicle's path from the detection target.

[0035] As described above, according to the present disclosure, it is possible to allow object detection device 100 mounted on vehicle V to appropriately detect objects on its path. In particular, in this embodiment, the object detection area is configured to extend onto the sidewalk area at an intersection or the like, making it possible to achieve early detection of objects in locations where crossings with pedestrians or the like are expected.

[0036] 6 has been described with reference to an example in which the object detection device 100 is disposed in the vehicle V, the location of the object detection device 100 is not limited to this. For example, the object detection device 100 may be realized as a function of an edge server that receives images from the vehicle V. By using such an edge server, it becomes possible to appropriately notify the vehicle V and the control center that controls the vehicle V of the object detection results.

[0037] Second Embodiment Next, a second embodiment will be described in which the object detection device 100 is provided with a function for detecting road portions in an image. FIG. 10 is a diagram showing an example configuration of another object detection device 100a according to the present disclosure. The difference from the example configuration shown in FIG. 6 is that the object detection device 100a includes a road detection unit 106 instead of the road information storage unit 102 and GPS, and the area determination unit 103a determines an area based on the output of the road detection unit 106. The other configurations are the same as those of FIG. 6, so the following description will focus on the differences.

[0038] The road detection unit 106 detects roads in the image captured by the camera C and sends the shape information of the roads to the area determination unit 103a. FIG. 11 shows the detection results of the road shapes detected by the road detection unit 106. Note that the road detection function of the road detection unit 106 can utilize white line detection technology, etc., adopted in self-driving cars and ADAS (Advanced Driver Assistance Systems). In the example of FIG. 10, the area determination unit 103a includes a second acquisition unit 12 that acquires sensor information.

[0039] The region determination unit 103a determines a region that is a detection range for an object in the image based on the road shape detected by the road detection unit 106. For example, if a road shape like that shown in Fig. 11 is detected, the region determination unit 103a selects a part of the road that curves to the right as shown in Fig. 5 as the region.

[0040] Fig. 12 is a flowchart showing the operation of the object detection device 100a. The difference from the flowchart shown in Fig. 8 is that after acquiring a camera image in step S001, the object detection device 100a detects the road shape from this image (step S102). The subsequent processing is the same as the flow shown in Fig. 8, so a description thereof will be omitted.

[0041] As described above, according to this embodiment in which the road detection unit 106 is added, it is possible to determine an area in which an object is to be detected appropriately without using GPS or road information.

[0042] [Third Embodiment] Next, a third embodiment will be described in which an area determination function based on a train schedule (train diagram) is provided in the object detection device 100. FIG. 13 is a diagram showing an example configuration of another object detection device 100b according to the present disclosure. The difference from the example configuration shown in FIG. 6 is that the object detection device 100b includes an operation plan information storage unit 107 and a clock T instead of the road information storage unit 102 and GPS, and the area determination unit 103b determines an area based on the contents of these. Other configurations are the same as those in FIG. 6, so the following description will focus on the differences.

[0043] The operation plan information storage unit 107 stores operation plan information for the vehicle V. FIG. 14 is a diagram for explaining an overview of the operation plan information. The double-headed arrow on the map on the left side of FIG. 14 indicates the round-trip route of the vehicle V, and the vehicle V travels back and forth between position G and position H. The table on the right side of FIG. 14 indicates the time when the vehicle V departs from position G or H and the time when the vehicle V arrives at position H or G. Note that, if the vehicle V is a route bus, a delivery truck, or the like, its operation diagram can be used as such operation plan information. Furthermore, if the vehicle V is a regular vehicle, route information to the destination set in a car navigation device and predicted passing times at each point on the route can also be used as the operation plan information.

[0044] The area determination unit 103b refers to the operation plan information stored in the operation plan information storage unit 107, estimates the current location and direction of travel of the vehicle V corresponding to the current time indicated by the clock T, and determines the area that will be the detection range for objects in the image.

[0045] Fig. 15 is a flowchart showing the operation of the object detection device 100b. The difference from the flowchart shown in Fig. 8 is that after acquiring a camera image in step S001, the object detection device 100b identifies the road shape from the current time and operation plan information (step S202). The subsequent processing is the same as the flow shown in Fig. 8, so a description thereof will be omitted.

[0046] Fig. 16 is a diagram for explaining the operation of object detection device 100b. In the example of Fig. 16, vehicle V departs from position G, and the current time is 9:10. At this time, vehicle V is located at position E in Fig. 16, and vehicle V is traveling toward position H, so the road in the traveling direction curves to the right. In this case, object detection device 100b determines the shaded area in Fig. 5 as the area in which to detect objects.

[0047] Similarly, when the current time is 9:40, according to the operation plan information, vehicle V is at position F in Fig. 17 and is traveling toward position G, so there is an intersection in the traveling direction. In this case, object detection device 100b determines the shaded area in Fig. 9 as the area in which to detect objects.

[0048] As described above, according to this embodiment, it is possible to determine an area in which an object is to be detected appropriately without using road information or a road detection function.

[0049] As can be understood from the above explanation, the object detection device 100b of this embodiment can be suitably applied to detecting objects in the direction of travel of buses and trains, which require strict punctuality and operate on schedule.

[0050] Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments, and further modifications, substitutions, and adjustments can be made without departing from the basic technical concept of the present disclosure. For example, the network configurations, element configurations, and data representation formats shown in the drawings are examples intended to aid in understanding the present disclosure, and are not limited to the configurations shown in these drawings.

[0051] For example, in the first to third embodiments described above, the moving body is a vehicle V. However, instead of the vehicle V, the object detection device can be used to detect objects in the traveling direction of other moving bodies. Examples of such moving bodies include railroad cars and UAVs (Unmanned Aerial Vehicles, so-called drones). When the moving body is a railroad car, the object detection device sets a region along the direction in which the rails curve at the moving body's destination. If there is a structure such as a station at the moving body's destination, the object detection device can set a region that protrudes toward the platform. Similarly, when the moving body is a UAV, the object detection device sets a region along its flight path (such as on a road), and if there is a structure or the like at the moving body's destination that requires attention, the object detection device can set a region that protrudes according to the shape of the structure.

[0052] In addition, in the first to third embodiments described above, examples have been given in which the detection object is a pedestrian, but the detection object is not limited to a pedestrian and may be another vehicle, a fallen object, an abnormality in the road, or the like.

[0053] (Hardware Configuration) In each embodiment of the present disclosure, each component of each device represents a functional unit block. Some or all of the components of each device are realized by an arbitrary combination of an information processing device 900 and a program, for example, as shown in FIG. 18 . FIG. 18 is a block diagram showing an example of the hardware configuration of the information processing device 900 that realizes each component of each device. The information processing device 900 includes, as an example, the following configuration: - CPU (Central Processing Unit) 901 - ROM (Read Only Memory) 902 - RAM (Random Access Memory) 903 - Program 904 loaded into RAM 903 - Storage device 905 that stores the program 904 - Drive device 907 that reads and writes to a recording medium 906 - Communication interface 908 that connects to a communication network 909 - Input / output interface 910 that inputs and outputs data - Bus 911 that connects each component

[0054] Each component of each device in each embodiment is realized by the CPU 901 acquiring and executing a program 904 that realizes the function. That is, the CPU 901 in FIG. 18 executes a data acquisition program and an area determination program, and performs an update process for each calculation parameter stored in the RAM 903, the storage device 905, etc. The program 904 that realizes the function of each component of each device is stored in the storage device 905 or the ROM 902 in advance, for example, and is read by the CPU 901 as needed. The program 904 may be supplied to the CPU 901 via the communication network 909, or may be stored in advance on the recording medium 906, and the drive device 907 may read the program and supply it to the CPU 901.

[0055] There are various variations in the method of realizing each device. For example, each device may be realized by any combination of a separate information processing device 900 and a program for each component. Furthermore, multiple components included in each device may be realized by any combination of a single information processing device 900 and a program. That is, each unit (processing means, function) of the object detection device shown in the first to third embodiments can be realized by a computer program that causes a processor installed in the device to execute each of the above-mentioned processes using its hardware.

[0056] In addition, some or all of the components of each device may be realized by other general-purpose or dedicated circuits, processors, etc., or a combination of these. These may be configured by a single chip, or by multiple chips connected via a bus.

[0057] Some or all of the components of each device may be realized by a combination of the above-mentioned circuits and programs.

[0058] When some or all of the components of each device are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or decentralized. For example, the information processing devices, circuits, etc. may be realized as a client-server system, a cloud computing system, or the like, in a form in which each device is connected via a communication network.

[0059] It should be noted that the above-described embodiments are preferred embodiments of the present disclosure, and the scope of the present disclosure is not limited to only the above-described embodiments. In other words, those skilled in the art can modify or substitute the above-described embodiments to construct various modified forms without departing from the gist of the present disclosure.

[0060] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0061] [Supplementary Note 1] An object detection device comprising: a first acquisition unit that acquires an image; a second acquisition unit that acquires road information or sensor information for a position corresponding to the image; a region determination unit that determines a region in the image that is a detection range for an object based on the road information or the sensor information; and an object detection unit that detects an object within the region. [Supplementary Note 2] The first acquisition unit of the object detection device may be configured to acquire an image captured in the direction of travel of the moving object from a camera mounted on the moving object. [Supplementary Note 3] The second acquisition unit of the object detection device may be configured to acquire road information or sensor information for a position corresponding to the image based on position information and the direction of travel of the moving object. [Supplementary Note 4] The region determination unit of the object detection device may be configured to set the region along a road on the image based on the road information or sensor information. [Supplementary Note 5] In the object detection device, the road information may be map information including the shape of the road. [Supplementary Note 6] In the object detection device, the sensor information may be a detection result of the road shape. [Supplementary Note 7] In the above-mentioned object detection device, instead of the second acquisition unit, the current time and operation plan information can be acquired, and the area determination unit can be configured to determine the area based on the operation plan information and the current time. [Supplementary Note 8] The area determination unit of the above-mentioned object detection device can be configured to set the area that protrudes in a direction intersecting with the intersection when an intersection is present in the traveling direction of the moving body. [Supplementary Note 9] The area determination unit of the above-mentioned object detection device can be configured to set the area that protrudes in accordance with the shape of a structure when a structure is present in the traveling direction of the moving body. [Supplementary Note 10] An object detection method comprising: acquiring an image and road information or sensor information for a position corresponding to the image; determining an area in the image that is a detection range for an object based on the road information or the sensor information; and detecting an object within the area.[Supplementary Note 11] A recording medium storing a program that causes a computer to execute the following processes: acquiring an image and road information or sensor information for a position corresponding to the image; determining an area in the image that is an object detection range based on the road information or the sensor information; and detecting an object within the area. The embodiments described in each of the above Supplements can be combined with each other after making necessary modifications. For example, a configuration that combines the contents of Supplementary Note 2 and the contents of Supplementary Note 3 is also included in the scope of disclosure of this specification. The embodiments of Supplements 10 to 11 can be expanded into the embodiments of Supplements 2 to 9, similar to Supplementary Note 1.

[0062] The disclosures of the above-cited patent documents are incorporated herein by reference and may be used as the basis or part of this disclosure, as necessary. Modifications and adjustments of the embodiments and examples are possible within the scope of this disclosure (including the claims), and further based on its basic technical concept. Furthermore, various combinations and selections (including partial deletions) of various disclosed elements (including elements of each claim, each element of each embodiment or example, each element of each drawing, etc.) are possible within the scope of this disclosure. In other words, this disclosure naturally includes various modifications and alterations that would be possible by a person skilled in the art in accordance with the entire disclosure, including the claims, and the technical concept. In particular, with regard to the numerical ranges described herein, any numerical value or subrange within that range should be construed as specifically described, even if not otherwise specified. Furthermore, the disclosures of the above-cited documents, when used in part or in whole in combination with the disclosures herein as part of this disclosure, in accordance with the spirit of this disclosure, are also deemed to be included in the disclosures of this application.

[0063] REFERENCE SIGNS LIST 10, 100, 100a, 100b Object detection device 11 First acquisition unit 12 Second acquisition unit 13, 103 Area determination unit 14, 104 Object detection unit 102 Road information storage unit 105 Display unit 106 Road detection unit 107 Operation plan information storage unit 900 Information processing device 901 CPU (Central Processing Unit) 902 ROM (Read Only Memory) 903 RAM (Random Access Memory) 904 Program 905 Storage device 906 Recording medium 907 Drive device 908 Communication interface 909 Communication network 910 Input / output interface 911 Bus C Camera P Pedestrian T Clock V Vehicle

Claims

1. An object detection device comprising: a first acquisition unit that acquires an image; a second acquisition unit that acquires road information or sensor information for a position corresponding to the image; a region determination unit that determines a region in the image that is a detection range for an object based on the road information or the sensor information; and an object detection unit that detects an object within the region.

2. The object detection device according to claim 1, wherein the first acquisition unit acquires an image taken in the traveling direction of a moving object from a camera mounted on the moving object.

3. The object detection device according to claim 2, wherein the second acquisition unit acquires road information or sensor information for a position corresponding to the image based on position information and a traveling direction of the moving object.

4. An object detection device according to any one of claims 1 to 3, wherein the area determination unit sets the area along a road on the image based on the road information or sensor information.

5. An object detection device according to any one of claims 1 to 4, wherein the road information is map information including the shape of the road.

6. An object detection device according to any one of claims 1 to 5, wherein the sensor information is a result of detection of a road shape.

7. An object detection device according to claim 1 or 2, wherein instead of the second acquisition unit, a current time and operation plan information for a moving object can be acquired, and the area determination unit determines the area based on the operation plan information and the current time.

8. An object detection device according to claim 2, 3 or 7, wherein, when an intersection is present in the traveling direction of the moving body, the area determination section sets the area extending in a direction intersecting with the intersection.

9. An object detection device according to claim 2, 3 or 7, wherein, when a structure is present in the traveling direction of the moving body, the region determination unit sets the protruding region in accordance with the shape of the structure.

10. An object detection method comprising: acquiring an image and road information or sensor information for a position corresponding to the image; determining an area in the image that is an object detection range based on the road information or the sensor information; and detecting an object within the area.

11. A recording medium having recorded thereon a program that causes a computer to execute the following processes: a process of acquiring an image and road information or sensor information for a position corresponding to the image; a process of determining an area in the image that is an object detection range based on the road information or the sensor information; and a process of detecting an object within the area.

Images