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CN114332654A - Building type identification method, system and device based on unmanned aerial vehicle aerial photography - Google Patents

Building type identification method, system and device based on unmanned aerial vehicle aerial photography Download PDF

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Publication number
CN114332654A
CN114332654A CN202111648861.7A CN202111648861A CN114332654A CN 114332654 A CN114332654 A CN 114332654A CN 202111648861 A CN202111648861 A CN 202111648861A CN 114332654 A CN114332654 A CN 114332654A
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China
Prior art keywords
building
roof
buildings
building type
image data
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CN202111648861.7A
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Chinese (zh)
Inventor
吴恒天
孔维政
王广军
汤芳
吴潇雨
陈睿
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State Grid Energy Research Institute Co Ltd
China University of Geosciences Beijing
Original Assignee
State Grid Energy Research Institute Co Ltd
China University of Geosciences Beijing
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Priority to CN202111648861.7A priority Critical patent/CN114332654A/en
Publication of CN114332654A publication Critical patent/CN114332654A/en
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Abstract

The invention discloses a building type identification method, a building type identification system and a building type identification device based on unmanned aerial vehicle aerial photography, wherein the building type identification method, the building type identification system and the building type identification device comprise the steps of obtaining image data of a building target area aerial photographed by an unmanned aerial vehicle; and identifying the roof information in the image data according to the roof attribute to obtain the building type. The invention can realize the rapid identification of the building aerial photographed by the unmanned aerial vehicle.

Description

Building type identification method, system and device based on unmanned aerial vehicle aerial photography
Technical Field
The invention relates to the field of building identification of unmanned aerial vehicle aerial photography, in particular to a building type identification method, system and device based on unmanned aerial vehicle aerial photography.
Background
Unmanned aerial vehicle aerial photography, artificial intelligence, degree of depth study have developed to a certain extent, can't effectively discern rural roof among the prior art, can't effectively discern city building type.
Disclosure of Invention
The invention aims to provide a building type identification method, a building type identification system and a building type identification device based on unmanned aerial vehicle aerial photography, and aims to solve the problem of building type identification of unmanned aerial vehicle aerial photography.
The invention provides a building type identification method based on unmanned aerial vehicle aerial photography, which comprises the following steps:
s1, acquiring image data of the unmanned aerial vehicle aerial photography building target area;
and S2, identifying the roof information in the image data according to the roof attribute to obtain the building type.
The invention also provides a building type identification system for unmanned aerial vehicle aerial photography, which comprises:
an acquisition module: the unmanned aerial vehicle aerial photography building target area image data acquisition device is used for acquiring image data of an unmanned aerial vehicle aerial photography building target area;
an identification module: and the image data is used for identifying the roof information in the image data according to the roof attribute to obtain the building type.
The embodiment of the invention also provides a building type recognition device for unmanned aerial vehicle aerial photography, which comprises: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program implementing the steps of the above method when executed by the processor.
The embodiment of the invention also provides a computer readable storage medium, wherein an implementation program for information transmission is stored on the computer readable storage medium, and the implementation program realizes the steps of the method when being executed by a processor.
By adopting the embodiment of the invention, the rapid identification of the type of the building aerial-photo by the unmanned aerial vehicle can be realized.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a building type identification method based on unmanned aerial vehicle aerial photography according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a building type identification system based on unmanned aerial vehicle aerial photography in accordance with an embodiment of the present invention;
fig. 3 is a schematic diagram of a building type identification device based on unmanned aerial vehicle aerial photography according to an embodiment of the invention.
Description of reference numerals:
210: an acquisition module; 220: and identifying the module.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Method embodiment
According to an embodiment of the present invention, a building type identification method based on unmanned aerial vehicle aerial photography is provided, fig. 1 is a flowchart of the building type identification method based on unmanned aerial vehicle aerial photography according to the embodiment of the present invention, and as shown in fig. 1, the method specifically includes:
s1, acquiring image data of the unmanned aerial vehicle aerial photography building target area;
and S2, identifying the roof information in the image data according to the roof attribute to obtain the building type.
S2 specifically includes:
and identifying the roof information in the image data to obtain the building type according to the roof attribute based on a building type identification model obtained by machine learning of the roof attribute.
S2 specifically includes: and identifying the roof information in the image data according to the roof attribute to obtain the building type, wherein the building type is an industrial factory building, a commercial building, a public building, a residential building and a farmer building.
S2 further includes: identifying and marking the roof shape, the number of buildings and the geographical position of the industrial factory building, the commercial building, the public building, the residential building and the farmer building, calculating the roof area of the industrial factory building, the commercial building, the public building, the residential building and the farmer building, storing the building house type, number, geographical position and roof area in a database, and judging the urban and rural areas according to the building house type, number, geographical position and roof area.
The specific implementation method comprises the following steps:
provided is building top surface identification based on unmanned aerial vehicle aerial photography technology. The method can download and receive aerial photography image data according to a selected urban target area, judge urban and rural areas by utilizing artificial intelligence and deep learning technology, and mark an industrial factory building, a commercial building, a public building, a residential building and a farmer roof on the aerial photography image. The number, type, geographical location, and roof area of the buildings are counted, and the roof information of each building is stored in a database.
The following modules are used:
module 1:
1. receiving boundary data of a selected area;
2. receiving aerial image data of the unmanned aerial vehicle;
3. outputting aerial image data based on the selected area;
and (3) module 2:
1. receiving aerial image data based on a target area;
2. identifying the roof information according to the roof attribute;
3. marking the roof information in the aerial image;
4. after the roof information is corrected;
5. machine learning of roof attributes;
6. marking all roofs in the aerial images;
and a module 3:
1. inputting labels of industrial factory buildings, commercial buildings, public buildings, residential buildings and farmer roofs;
2. inputting aerial image roof data;
3. marking industrial plants, commercial buildings, public buildings, residential buildings and farmer roofs;
4. identifying the shapes and the outlines of industrial factory buildings, commercial buildings, public buildings, residential buildings and farmer roofs;
5. and calculating the roof areas of industrial plants, commercial buildings, public buildings, residential buildings and farmers.
The invention has the following beneficial effects:
1. the building types in the region can be identified, and the accuracy rate of roof area calculation reaches more than 99 percent;
2. the recognition result can be visually displayed;
3. can judge urban and rural areas.
System embodiment
According to an embodiment of the present invention, a building type identification system based on unmanned aerial vehicle aerial photography is provided, fig. 2 is a schematic diagram of the building type identification system based on unmanned aerial vehicle aerial photography according to the embodiment of the present invention, as shown in fig. 2, specifically including:
the obtaining module 210: the unmanned aerial vehicle aerial photography building target area image data acquisition device is used for acquiring image data of an unmanned aerial vehicle aerial photography building target area;
the recognition module 220: and the method is used for identifying the roof information in the image data according to the roof attribute to obtain the building type.
The identification module 220 is specifically configured to:
and identifying the roof information in the image data to obtain the building type according to the roof attribute based on a building type identification model obtained by machine learning of the roof attribute.
The identification module 220 is specifically configured to: and identifying the roof information in the image data according to the roof attribute to obtain the building type, wherein the building type is an industrial factory building, a commercial building, a public building, a residential building and a farmer building.
The identification module 220 is further configured to: identifying and marking the roof shape, the number of buildings and the geographical position of the industrial factory building, the commercial building, the public building, the residential building and the farmer building, calculating the roof area of the industrial factory building, the commercial building, the public building, the residential building and the farmer building, storing the building house type, number, geographical position and roof area in a database, and judging the urban and rural areas according to the building house type, number, geographical position and roof area.
The embodiment of the present invention is a system embodiment corresponding to the above method embodiment, and specific operations of each module may be understood with reference to the description of the method embodiment, which is not described herein again.
Apparatus embodiment one
The embodiment of the invention provides a building type identification device based on unmanned aerial vehicle aerial photography, as shown in fig. 3, comprising: a memory 30, a processor 32 and a computer program stored on the memory 30 and executable on the processor 32, the computer program, when executed by the processor, implementing the steps of the above-described method embodiments.
Device embodiment II
The embodiment of the present invention provides a computer-readable storage medium, on which an implementation program for information transmission is stored, and when the program is executed by the processor 32, the steps in the above method embodiments are implemented.
The computer-readable storage medium of this embodiment includes, but is not limited to: ROM, RAM, magnetic or optical disks, and the like.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; however, these modifications or alternative technical solutions of the embodiments of the present invention do not depart from the scope of the present invention.

Claims (10)

1.一种基于无人机航拍的建筑物类型识别方法，其特征在于，包括，1. a kind of building type identification method based on drone aerial photography, is characterized in that, comprises, S1、获取无人机航拍建筑物目标区域的影像数据；S1. Obtain the image data of the target area of the building from the aerial photography of the drone; S2、根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型。S2. According to the roof attribute, identify the roof information in the image data to obtain the building type. 2.根据权利要求1所述的方法，其特征在于，所述S2具体包括：2. The method according to claim 1, wherein the S2 specifically comprises: 基于机器学习屋顶属性得到的建筑物类型识别模型，根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型。Based on the building type identification model obtained by the machine learning roof attribute, the building type is obtained by identifying the roof information in the image data according to the roof attribute. 3.根据权利要求1所述的方法，其特征在于，所述S2具体包括：根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型，其中建筑物类型为工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑。3. The method according to claim 1, wherein the S2 specifically comprises: identifying the roof information in the image data to obtain a building type according to the roof attribute, wherein the building type is an industrial plant, a commercial building, Public buildings, residential buildings and farm buildings. 4.根据权利要求3所述的方法，其特征在于，所述S2进一步包括：识别并标记工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑的屋顶形状、建筑物数量和地理位置，计算工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑的屋顶面积，将建筑屋类型、数量、地理位置和屋顶面积存储在数据库中，根据建筑屋类型、数量、地理位置和屋顶面积判断城市和农村地区。4. The method according to claim 3, characterized in that, said S2 further comprises: identifying and marking the roof shape, number of buildings and geographical location of industrial plants, commercial buildings, public buildings, residential buildings and farm buildings, calculating Roof area of industrial plants, commercial buildings, public buildings, residential buildings and farm buildings, store the type, quantity, geographic location and roof area of building houses in the database, and judge the urban and Countryside. 5.一种基于无人机航拍的建筑物类型识别系统，其特征在于，包括，5. a kind of building type identification system based on drone aerial photography, is characterized in that, comprises, 获取模块：用于获取无人机航拍建筑物目标区域的影像数据；Acquisition module: used to acquire the image data of the target area of the building in the aerial photography of the drone; 识别模块：用于根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型。Identification module: used to identify the roof information in the image data to obtain the building type according to the roof attribute. 6.根据权利要求5所述的系统，其特征在于，所述识别模块具体用于：6. The system according to claim 5, wherein the identification module is specifically used for: 基于机器学习屋顶属性得到的建筑物类型识别模型，根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型。Based on the building type identification model obtained by the machine learning roof attribute, the building type is obtained by identifying the roof information in the image data according to the roof attribute. 7.根据权利要求5所述的系统，其特征在于，所述识别模块具体用于：根据屋顶属性，识别所述影像数据中的屋顶信息得到建筑物类型，其中建筑物类型为工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑。7 . The system according to claim 5 , wherein the identification module is specifically configured to: identify the roof information in the image data to obtain a building type according to the roof attribute, wherein the building type is an industrial plant, a commercial Buildings, public buildings, residential buildings and farm buildings. 8.根据权利要求7所述的系统，其特征在于，所述识别模块还用于：识别并标记工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑的屋顶形状、建筑物数量和地理位置，计算工业厂房、商业楼宇、公共建筑、居民建筑和农户建筑的屋顶面积，将建筑屋类型、数量、地理位置和屋顶面积存储在数据库中，根据建筑屋类型、数量、地理位置和屋顶面积判断城市和农村地区。8. The system according to claim 7, wherein the identification module is further used for: identifying and marking the roof shape, building quantity and geographical location of industrial plants, commercial buildings, public buildings, residential buildings and farm buildings , Calculate the roof area of industrial plants, commercial buildings, public buildings, residential buildings and farm buildings, store the type, quantity, geographic location and roof area of the building in the database, and judge according to the type, quantity, geographic location and roof area of the building urban and rural areas. 9.一种基于无人机航拍的建筑物类型识别装置，其特征在于，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现如权利要求1至4中任一项所述的基于无人机航拍的建筑物类型识别方法的步骤。9. A device for identifying a building type based on aerial photography of an unmanned aerial vehicle, comprising: a memory, a processor and a computer program stored on the memory and running on the processor, the computer program When executed by the processor, the steps of implementing the method for identifying a building type based on aerial photography of an unmanned aerial vehicle as claimed in any one of claims 1 to 4. 10.一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储有信息传递的实现程序，所述程序被处理器执行时实现如权利要求1至4中任一项所述的基于无人机航拍的建筑物类型识别方法的步骤。10. A computer-readable storage medium, characterized in that, an implementation program for information transmission is stored on the computer-readable storage medium, and when the program is executed by a processor, the implementation of any one of claims 1 to 4 is realized. The steps of the above-mentioned building type recognition method based on UAV aerial photography.
CN202111648861.7A 2021-12-30 2021-12-30 Building type identification method, system and device based on unmanned aerial vehicle aerial photography Pending CN114332654A (en)

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