CN111862137A

CN111862137A - Method and device for determining graph boundary according to point set

Info

Publication number: CN111862137A
Application number: CN202010678536.4A
Authority: CN
Inventors: 杨磊; 韦亚雄
Original assignee: Shanghai Junzheng Network Technology Co Ltd
Current assignee: Shanghai Junzheng Network Technology Co Ltd
Priority date: 2020-07-15
Filing date: 2020-07-15
Publication date: 2020-10-30

Abstract

The present specification provides a method and apparatus for determining a graph boundary from a set of points. In one embodiment of the method, a point set of business object distribution can be obtained, point set data is converted into a geometric figure surface network, and then a geometric figure space needing to be reserved can be found out based on density parameters, so that a preliminary figure boundary is determined. Through the embodiment of the specification, the boundary of the operation area can be determined based on the bottom data such as the shared bicycle distribution, and the operation planning processing efficiency is improved. Meanwhile, the method and the device can uniformly output the reliable boundary graph which is consistent with the actual service condition based on the real bottom data distribution condition of the service, and effectively guarantee the planning quality and reliability of the operation area.

Description

Method and device for determining graph boundary according to point set

Technical Field

The embodiment of the specification belongs to the field of geographic information data processing, and particularly relates to a method and a device for determining a graph boundary according to a point set.

Background

With the development of the sharing economic technology, great convenience is brought to people for traveling by sharing bicycles, sharing electric vehicles, sharing automobiles and the like. The service party providing vehicle sharing can plan the operation area according to the development condition of the local city, and the service party can meet the requirements of users and obtain the best benefit.

Currently, the planning of the service provider operation area is usually based on urban basic data, such as population distribution, administrative/economic area, traffic conditions, etc., and is performed according to manual experience. Meanwhile, the economic levels of different cities or the planning abilities of planners are different, which causes the planning quality of the operation areas to be uneven.

Disclosure of Invention

The present disclosure is directed to a method and an apparatus for determining a graph boundary according to a point set, which can efficiently determine the graph boundary by using a point set distribution condition of a service object, so that the graph boundary is more consistent with an actual condition, and further, a more reasonable operation boundary planning is implemented.

The method and the device for determining the graph boundary according to the point set are realized by the following steps:

a method of determining a graph boundary from a set of points, comprising:

connecting nodes in the point set to form a non-intersected geometric figure set;

cutting out a space area contained in the sparse geometric figure in the geometric figure set to obtain a residual figure, wherein the sparse geometric figure comprises a geometric figure with side length larger than a density parameter in the geometric figure set;

determining a boundary line segment according to the occurrence frequency of the line segment in the residual graph in the geometric graph;

And determining a preliminary graph boundary according to the boundary line segment.

An apparatus for determining a boundary of a graph from a set of points, comprising:

the node connecting module is used for connecting the nodes in the point set to form a non-intersected geometric figure set;

the cutting module is used for cutting out a space area contained in the sparse geometric figure in the geometric figure set to obtain a residual figure, wherein the sparse geometric figure comprises a geometric figure with the side length larger than the density parameter in the geometric figure set;

the boundary searching module is used for determining a boundary line segment according to the occurrence frequency of the line segment in the residual graph in the geometric graph;

and the preliminary boundary determining module is used for determining a preliminary graph boundary according to the boundary line segment.

A processing device, comprising: at least one processor and a memory for storing processor-executable instructions, which when executed by the processor perform the steps of any one of the method embodiments described herein.

A storage medium having stored thereon computer-executable instructions that, when executed, perform the steps of any one of the method embodiments of the present description.

The method and the device for determining the graph boundary according to the point set provided by the embodiment of the specification can acquire the point set of the service object distribution, convert the point set data into the geometric figure surface net, and then find out the geometric figure space needing to be reserved based on the density parameter, thereby determining the preliminary graph boundary. Through the embodiment of the specification, the boundary of the operation area can be determined based on the bottom data such as the shared bicycle distribution, and the operation planning processing efficiency is improved. Meanwhile, the method and the device can uniformly output the reliable boundary graph which is consistent with the actual service condition based on the real bottom data distribution condition of the service, and effectively guarantee the planning quality and reliability of the operation area.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

FIG. 1 is a schematic flow chart diagram illustrating one embodiment of a method for determining a boundary of a graph from a set of points provided herein;

FIG. 2 is a schematic diagram of a distribution of point sets of business objects in one embodiment provided by the present specification;

FIG. 3 is a schematic diagram of converting a set of points to a set of triangles in one embodiment provided by the present specification;

FIG. 4 is a schematic illustration of a differentiation provided in one embodiment of the present description to determine whether a geometry is within a boundary based on a density parameter;

FIG. 5 is a schematic illustration of determining retained geometry in one embodiment provided by the present description;

FIG. 6 is a schematic illustration of determining a boundary line segment in one embodiment provided by the present description;

FIG. 7 is a schematic illustration of a preliminary graphical boundary determined in one embodiment provided by the present description;

FIG. 8 is a schematic flow chart diagram illustrating another embodiment of a method for determining a boundary of a graph from a set of points provided herein;

FIG. 9 is a schematic diagram illustrating a boundary effect after an offset process in one embodiment provided in the present specification;

FIG. 10 is a schematic diagram illustrating the boundary effect after the nesting process in one embodiment provided in the present specification;

FIG. 11 is a block diagram of a hardware architecture for a method for determining a graph boundary from a set of points using an embodiment of the present invention;

FIG. 12 is a block diagram illustrating an exemplary embodiment of an apparatus for determining a boundary of a graph according to a set of points provided in the present specification;

FIG. 13 is a block diagram of another embodiment of the apparatus provided herein;

fig. 14 is a schematic block diagram of another embodiment of the apparatus provided in the present specification.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

One of the main contents of the operation area planning is to determine the boundary of the operation area for the service party to perform market layout, product placement, advertisement investment, friend cooperation, event response, etc. As mentioned above, the planning of an operating area by a current vehicle service provider is usually determined based on manual analysis of some city data. When the operation areas are divided manually, the subjectivity is strong, and experiences of different planners are different, so that the planning results of the operation areas are often greatly different, and the planning quality is difficult to guarantee.

The applicant provides, in one or more embodiments of the present specification, a method for determining a graph boundary according to a data point set where a business object is actually distributed, which can more efficiently and reliably draw the graph boundary based on the distribution density of nodes in the point set and the graph processing.

The following describes an embodiment of the present specification with a specific implementation scenario drawn by a boundary of a shared single-vehicle operation area. FIG. 1 is a flow chart illustrating an embodiment of a method for determining a boundary of a graph according to a point set provided in the present specification. Although the present specification provides method operational steps or devices, system configurations, etc., as illustrated in the following examples or figures, more or less operational steps or modular units may be included in the methods or devices, as may be conventional or may be part of the inventive subject matter, based on conventional or non-inventive considerations. In the case of steps or structures which do not logically have the necessary cause and effect relationship, the execution sequence of the steps or the module structure of the apparatus is not limited to the execution sequence or structure shown in the embodiment or the drawings in this specification. When the apparatus, server, system or end product of the method or system architecture is applied in an actual device, server, system or end product, the method or module architecture according to the embodiment or the drawings may be executed sequentially or executed in parallel (for example, in an environment of parallel processors or multi-thread processing, or even in an environment of distributed processing, server clustering, or implementation in combination with cloud computing or block chain technology).

Of course, the following description of the embodiments is not limited to the implementation scenario of determining the boundary of the shared bicycle operating area, and the solution of the embodiments of the present specification is also applicable to other implementation scenarios of determining the boundary based on point set data of the distribution of business objects, for example, a business object may be a shared automobile, or may be an article such as a shared charger, a shared umbrella, or may be an event, such as renting or returning a shared bicycle, starting a certain service, or taking a case. Specifically, an embodiment of the method provided in this specification is shown in fig. 1, and may include:

s0: and connecting the nodes in the point set to form a disjoint geometric figure set.

In the embodiments of the present description, the location information of the business object, such as longitude and latitude data for storing the sharing bicycle or triggering the use of the sharing bicycle service event, may be obtained, and the location information of each business object is collected and used as a point set. Correspondingly, the nodes in the point set correspond to the position information of the business object. In this embodiment, each node in the point set may be plotted on a corresponding coordinate, for example, as shown in fig. 2, where an abscissa denotes longitude and an ordinate denotes latitude. Of course, in other applications, the location information of the business object is not limited to longitude and latitude data, but may also be other location information, such as two-dimensional coordinate information, three-dimensional coordinates, polar coordinates, or the like, or a data form similar to that in excel that represents a cell subscript, and the like.

The distribution of the point sets of the business objects is shown in fig. 2. Further in this embodiment, it may be converted into a pattern of a surface structure. Specifically, the nodes in the point set may be connected in a certain manner to form a plurality of geometric figures without intersecting edges. The specific connection mode may be that adjacent nodes are connected, or that every two nodes are connected, all nodes in the finally formed surface mesh graph are connected with at least one other node, and the connected geometric graphs are not intersected (there are no intersecting edges, there may be a common edge).

The geometric figures formed by connecting the nodes can comprise triangles, quadrangles and the like, and can be regular geometric figures or irregular geometric figures. As used herein, geometric figures are generally referred to as closed geometric figures. In one embodiment of the method provided herein, the geometric figure may include a triangle. Specifically, Delaunay triangulation may be adopted to convert the point set in fig. 2 into triangles that are connected with each other but do not intersect with each other, so as to form a triangle set, as shown in fig. 3.

S2: and cutting out a space area contained in the sparse geometric figure in the geometric figure set to obtain a residual figure, wherein the sparse geometric figure comprises a geometric figure with the side length larger than the density parameter in the geometric figure set.

The graphics region in fig. 3 is formed by a plurality of disjoint triangular tiles. The size of the area of the triangles can reflect the density of the node distribution to a certain extent. For example, in urban areas, compared with suburban areas, the number of delivery points of shared bicycles is large or the number of use times is large, the node distribution is relatively concentrated, the area of connected geometric figures is small, and the distribution is more concentrated. In this embodiment, the density parameter slength may be set in advance. The density parameter slength may represent the maximum distance of the allowed geometry edges (maximum edge length), from which it is possible to control whether certain geometries are contained within the final boundary. If the side length of the geometry is greater than the density parameter, it may be referred to as a sparse geometry in this embodiment. The line segments connected by the nodes form the edges of the geometric figure, if the distance (also called length) of a certain line segment exceeds the density parameter, the point where the nodes associated with the line segment belong to scattered distribution can be represented, and the determination of the boundary of the whole figure has no influence or negligible influence, and the influence can not be calculated in the boundary.

In a specific example of processing, as shown in fig. 4, if the distance of a line segment is greater than the density parameter slength, such as the line segments AB, BC, CD, AC, the triangles L1, L2, L3, L4, and L5 associated with the line segment AB, BC, CD, AC are not within the final boundary. A line segment less than or equal to the density parameter slength, such as AE, represents a triangle associated with the line segment AE within the final polygon boundary. Of course, in another case, if there is a geometric figure with both the side length greater than the density parameter and the side length less than the density parameter, the decision scheme may be preset. For example, for geometries with both a side length greater than the density parameter and a side length less than the density parameter, the associated geometry is not calculated within the final boundary during processing.

According to one embodiment, the geometric figure can be marked according to whether the side length of each geometric figure in the geometric figure set is greater than slength, if the segment of the geometric figure is greater than slength, the node contained in the geometric figure is rare, and the nodes can not be contained in the boundary. Therefore, the space of the geometric figure can be cut off, such as a triangle formed by line segments of areas where Z3 and Z4 are located in FIG. 5; if the side lengths of three sides of the geometric figure are less than or equal to slength, it can be indicated that the set of points near the geometric figure is dense and should be included in the final boundary. The geometric space needs to be reserved, such as a triangle formed by line segments in the dotted line frame areas of Z1 and Z2 in FIG. 5.

The density parameter slength may be preset, for example, may be set according to historical processing experience or adopt a default value. In another embodiment of the method described in this specification, the density parameter slength may be dynamically adjusted. For example, when a value of a density parameter slength is initially set to be v1, a preliminary graph boundary is obtained. If the graph boundary is not expected or is trimmed or is taken as one of the candidate boundary graphs, the value of the density parameter slength can be adjusted and set as v 2. At this time, a new preliminary pattern boundary can be obtained by the aforementioned pattern clipping. Of course, the density parameter slength may be adjusted one or more times, and the preliminary graph boundary may be obtained. The planner can select a proper output result according to expectation or requirements, thereby greatly increasing the flexibility and convenience of drawing the graph boundary, better selecting the graph boundary with better effect and improving the output quality. Thus, in another embodiment, the method described herein may further comprise:

Adjusting the density parameter based on an adjustment instruction;

and obtaining a new residual graph according to the adjusted density parameter, and determining a new preliminary graph boundary based on the new residual graph.

The embodiment of the specification can cut out the space area of the sparse geometric figure from the geometric figure set, and the figure formed by the line segments of the residual geometric figures can be called as the residual figure.

S4: and determining the boundary line segment according to the times of the line segments in the residual graph appearing in the geometric graph.

As shown in fig. 5, the dashed-line box areas of Z1 and Z2 are segments of the geometric figure within the boundary that needs to be preserved. The polygon boundaries may be drawn based on the line segments of these geometries in the remaining figures in this embodiment. Specifically, whether a line segment is at the boundary position may be determined according to the number of times the line segment appears in the geometric figure. For example, in one example, if a line segment appears in only one triangle and no other triangles are common, the line segment may be used as a boundary line segment. Thus, the above-described processing can be performed for all the line segments in the remaining graphics, respectively, to determine all the boundary line segments, as indicated by the broken lines in fig. 6.

S6: and determining a preliminary graph boundary according to the boundary line segment.

After the boundary line segments are determined, the boundary line segments may be connected to draw a graph boundary (for convenience of distinguishing, the determined graph boundary may be referred to as a preliminary graph boundary). Such as the preliminary graphical boundary represented in fig. 7.

By the method for determining the graph boundary according to the point set, the boundary of the operation area can be determined based on the density degree of the point set data distributed by the service objects such as the shared bicycle distribution, and the operation planning processing efficiency is improved. Meanwhile, the method and the device can uniformly output the reliable boundary graph which is consistent with the actual service condition based on the real bottom data distribution condition of the service, and effectively guarantee the planning quality and reliability of the operation area.

The above embodiments may obtain the preliminary graph boundary by the point set and the density of the point set. The graph boundary is composed of a plurality of unordered line segments, and the formed area can have the conditions of nesting, graph connection and the like. As shown in fig. 7, there are a plurality of independent polygons in the output graph, and there may be a case where some polygons are connected. In this regard, this specification also provides other embodiments of the method, which may further optimize to perform a shift process on the connected polygons, and split or combine adjacent polygons into a polygon with a larger area. Therefore, as shown in fig. 8, in another embodiment of the method described in this specification, the method may further include:

S80: searching a common node connected with polygons in the preliminary graph boundary;

s82: performing position offset on the common node, splitting connected polygons into independent polygons or connecting the polygons into a polygon, and determining an offset-processed graph;

s84: determining an overall graph boundary based on the offset-processed graph.

Connected polygons typically have common nodes. In this embodiment, the common node may be shifted in position and moved in a certain direction or spatial position. In one embodiment, the line segments may be traversed in a clockwise order, common nodes connected by polygons may be found, and longitude and latitude or dimension shift may be performed on the common nodes. For example, uniformly offsetting the longitude of the common node by 0.0005 ° to the left. Of course, the present specification does not limit that other position shift methods may be adopted, for example, shifting the common node to the left by 5 pixels or 1 distance unit. The pattern obtained after the position shift process may be referred to as a shifted pattern. A graph boundary may then be determined based on the shifted graph (the graph boundary at this time may be referred to as the overall graph boundary)

An effect schematic diagram of an embodiment is shown in fig. 9, if a processing manner of shifting one pixel to the right is adopted, the polygons No. 4 and 5 are originally connected with the polygon No. 3, and an independent polygon is formed after the position shift. In FIG. 9, the lower left corner A of the polygon No. 2 is connected to the polygon No. 2. After the offset, the polygon No. 2 is connected into a whole.

It can be seen from the boundary graph shown in fig. 7 or fig. 9 that there are a plurality of polygons and the distribution of each polygon. The representation of the graph at this time is still a collection of line segments. Based on this, in another preferred embodiment of the present specification, the node data may be stored by using a linked list, and structured data respectively representing each polygon may be obtained by performing corresponding linking and judgment processing, so that data representation of the polygon is clearer, and different polygons may also be clearly distinguished, which is convenient for subsequent reading or processing of polygon data. Specifically, in another embodiment of the method described in this specification, the method may further include:

storing position information of nodes of the polygon by using a linked list;

sequentially traversing the line segments in the preliminary graph boundary, and judging whether the line segments can be linked with an existing linked list according to the position information of the nodes;

if the connection is available, connecting the line segment to the tail part of the corresponding linked list, determining that the linked list forms a polygon when the first node and the last node of the linked list are the same, and taking the linked list as the structured data of the polygon;

if the link cannot be connected, the line segment is stored as a new linked list.

Of course, in other embodiments, the line segments may not be traversed sequentially. The unprocessed segments may also be traversed in other predetermined traversal orders or randomly.

In this embodiment, the sets of the line segments in fig. 7 or fig. 9 may be identified, and different polygons may be respectively expressed by ordered sets of points. The present embodiment may store the location information of the nodes of the polygon using a linked list.

In a specific example, a polygon pool (PoylineSeoup) may be constructed for storing polygons (Pline). PoylineSeop can be an array with an initial state of null, represented here using a linked list. Each element of the linked list stores position information, such as longitude and latitude values, of a node. A linked list may be judged to constitute a polygon when the first element (first node) and the last element (last node) of the linked list are equal. The data stored in the linked list may be used as the structured data of the corresponding polygon.

In the above processing, the line segments shown in fig. 7 may be traversed from left to right, the line segments are compared with the existing linked list, and whether the line segments can be linked with the head or the tail of the existing linked list is determined. And it can be judged after each linking operation whether the linked list constitutes a polygon.

For example, at this time, three Pline linked lists are arranged in the polygon pool PoylineSeop, as shown in the following table 1:

TABLE 1 Linked list information one stored in the polygon pool

Linked list	Node point	Connection point
			Pline1	(A，B，C，F)	A，F
Pline2	(E，H，Z，J，G)	E，G
			Pline3	(K，L，P，S，M，K)	/

Each letter in the table above may represent a latitude and longitude. In this embodiment, simplified expression processing may be performed, the same letter may indicate the same longitude and latitude, and a "/" may indicate that the linked list is connected end to end, a polygon has been formed, and no junction point exists.

From the PoylinSoup above, it can be seen that Pline3 has the same longitude and latitude from head to tail, and has formed a polygon without junction points. Pline1 and Pline2 are also sets of points that do not form polygons, and have junctions (a, F), (E, G), respectively, and there is a line segment joining the junctions of Pline1 and Pline 2.

And continuously traversing the line segment. If the next line segment traversed at this time is GD, it can be determined whether this line segment can be interlinked with all the splice points (A, F, E, G) of unformed Pline. As can be seen from Table 1, GD can be connected to point G of Pline2, and point D can be ligated after Pline 2. And determines whether Pline2 can form a polygon. At this point, PoylineSeop is shown in Table 2 below:

TABLE 2 Linked list information two stored in the Polygon pool

Linked list	Node point	Connection point
			Pline1	(A，B，C，F)	A，F
Pline2	(E，H，Z，J，G，D)	E，D
			Pline3	(K，L，P，S，M，K)	/

Further, in another embodiment, it may also be determined whether existing linked lists are merged into one linked list. Specifically, in another embodiment of the method, it may further be determined whether a plurality of linked lists can be linked as one linked list, or whether a currently processed line segment can link an existing linked list as one linked list; and if so, combining the corresponding linked lists into one linked list. If the judgment result is that Pline1 and Pline2 can be connected into a whole or not. If the traversal continues and a segment DA appears, then Pline2 and Pline1 can be linked to form a linked list, at which point PoylineSeop is shown in Table 3 below:

TABLE 3 Linked list information III stored in the Polygon pool

Of course, if a line segment is present, it is not possible to join any splice points. Such as NT, then poiylinesehop is shown in table 4 below:

TABLE 4 Linked list information four stored in the Polygon pool

Through continuous traversal of line segments, finally all plines can form a polygon, or a polygon is synthesized between every two plines.

Through the above steps, each polygon in fig. 9 can be clearly distinguished. Further, small areas in the polygon may be filtered, filtering nested areas. Such as

polygons

4, 6, 7, 8, 9, etc. are all nested within polygon 3 in fig. 9,

polygons

4, 6, 7, 8, 9, etc. may be merged into polygon 3. The merging may also include the process of connecting adjacent and/or large-area polygons, such as connecting multiple polygons (e.g.,

polygons

1, 2, and 3 in fig. 7), and finally obtaining a large polygon (in this case, the polygon may be referred to as a complete polygon), as shown in fig. 10. In this way, the vast majority of the nodes in the set of points are contained within the full polygon, and thus the full graph boundary can be determined based on the full polygon. For example, the boundary data of the point set of the complete polygon is taken as the complete graph boundary.

Thus, through one or more of the embodiments described above, a graphical boundary can be obtained that matches the actual distribution of the business objects. The graph boundary can be used as a recommended region of an operation region, and reliable data basis is provided for operation management and division such as offline operation or online planning.

In the present specification, each embodiment of the method is described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. Reference is made to the description of the method embodiments.

The method embodiments provided in the embodiments of the present specification may be executed in a PC terminal, a vehicle terminal, a computer terminal, a server cluster, a mobile terminal, a block chain system, a distributed network, or a similar computing device. The apparatus may include a system (including a distributed system), software (applications), modules, components, servers, clients, etc. that employ embodiments of the present description in conjunction with any necessary hardware for implementation. Taking a processing device running on a server as an example, fig. 11 is a hardware block diagram of a method for determining a graph boundary according to a point set, to which an embodiment of the present invention is applied. As shown in fig. 11, the server 10 may include one or more (only one shown) processors 100 (the processors 100 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 200 for storing data, and a transmission module 300 for communication functions. It will be understood by those skilled in the art that the structure shown in fig. 11 is merely illustrative and is not intended to limit the structure of the electronic device. For example, the server 10 may also include more or fewer components than shown in FIG. 11, and may also include other processing hardware, such as an internal bus, memory, database or multi-level cache, a display, or have other configurations than shown in FIG. 11, for example.

The memory 200 may be used to store software programs and modules of application software, and the processor 100 executes various functional applications and data processing by operating the software programs and modules stored in the memory 200. Memory 200 may include high speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 200 may further include memory located remotely from processor 100, which may be connected to a computer terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission module 300 is used for receiving or transmitting data via a network. Examples of such networks may include a blockchain private network of the server 10 or a network provided by the world wide web or a communications provider. In one example, the transmission module 300 includes a Network adapter (NIC) that can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission module 300 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

Based on the above description of the embodiments of the method for determining a graph boundary according to a point set, the present specification further provides an apparatus for determining a graph boundary according to a point set. The apparatus may include systems (including distributed systems), software (applications), modules, components, servers, clients, etc. that use the methods described in the embodiments of the present specification in conjunction with any necessary apparatus to implement the hardware. Based on the same innovative conception, embodiments of the present specification provide an apparatus as described in the following embodiments. Since the implementation scheme of the apparatus for solving the problem is similar to that of the method, the specific implementation of the apparatus in the embodiment of the present specification may refer to the implementation of the foregoing method, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Specifically, fig. 12 is a schematic block diagram of an embodiment of an apparatus for determining a graph boundary according to a point set, where as shown in fig. 12, the apparatus may include:

A node connection module 90, configured to connect nodes in the point set to form a disjoint geometric figure set;

the cutting module 91 may be configured to cut out a spatial region included in a sparse geometric figure in the geometric figure set to obtain a remaining figure, where the sparse geometric figure includes a geometric figure with a side length greater than a density parameter in the geometric figure set;

a boundary finding module 92, configured to determine a boundary line segment according to the number of times that the line segment in the remaining graph appears in the geometric graph;

a preliminary boundary determining module 93 may be configured to determine a preliminary graphical boundary from the boundary line segments.

As mentioned above, in other embodiments of the apparatus, the density parameter may be dynamically adjusted to obtain different preliminary pattern boundaries. Therefore, in another embodiment of the apparatus, as shown in fig. 13, the apparatus may further include:

the density adjusting module 100 may be configured to adjust the density parameter in the cropping module 91 based on the adjusting instruction, and obtain a new remaining graph according to the adjusted density parameter, and the preliminary boundary determining module 93 may determine a new preliminary graph boundary based on the new remaining graph. Of course, the specific in-process boundary finding module 92 may determine a new boundary line segment according to the new remaining graph, and then the preliminary boundary determining module 93 determines a new preliminary graph boundary according to the new boundary line segment.

Based on the foregoing description of the method embodiments, the present specification provides that in another embodiment of the apparatus, the geometric figure comprises a triangle. Of course, this description does not exclude other embodiments in which the geometric figure may be a regular or irregular quadrilateral, or other geometric figure that may represent a spatial region.

Based on the foregoing description of the method embodiments, this specification provides another embodiment of the apparatus, which may further include:

the offset processing module 110 may be configured to search a common node connected to polygons in a preliminary graph boundary, perform position offset on the common node, split the connected polygons into independent polygons or connect the polygons into one polygon, and determine an offset processed graph;

the whole boundary determining module 111 may determine a whole graph boundary based on the shifted graph.

the nested processing module 112 may be configured to merge polygons that have been nested in the graph after the offset processing, and connect the merged polygons to obtain a complete polygon;

A complete boundary determination module 113 may be configured to determine a complete graphics boundary based on the complete polygon.

Of course, in an actual device or system, all or a part of the combination of the preliminary boundary determining module 93, the overall boundary determining module 111, and the overall boundary determining module 113 may be implemented by one functional module. Fig. 14 is a schematic block diagram of another embodiment of the apparatus provided in the present specification.

Based on the foregoing description of the method embodiment, in another embodiment of the apparatus provided in this specification, the apparatus may further be configured to store the structured data of the polygon in the linked list, perform data judgment processing, and determine that the data in the linked list already forms the polygon. Specifically, the apparatus may further include:

a polygon storage module, which may be configured to store position information of nodes of a polygon with a linked list;

the linked list processing module can be used for sequentially traversing the line segments in the preliminary graph boundary and judging whether the line segments can be linked with the existing linked list according to the position information of the nodes; if the connection is available, the line segment is linked to the head or the tail of the corresponding linked list, the linked list is determined to form a polygon when the first node and the last node of the linked list are the same, and the linked list is used as the structured data of the polygon; if the link cannot be connected, the line segment is stored as a new linked list.

Based on the foregoing description of the method embodiments, the present specification provides another embodiment of the apparatus, which may further include:

the linked list merging module can be used for judging whether a plurality of linked lists stored by the polygon storage module can be linked into one linked list or not, or whether the current processed line segment can link the existing linked list into one linked list or not; and if so, combining the corresponding linked lists into one linked list.

It should be noted that the above-mentioned description of the apparatus according to the method embodiment may also include other implementation manners, and the specific implementation manner may refer to the description of the related method embodiment, which is not described in detail herein.

In the present specification, each embodiment of the apparatus is described in a progressive manner, and the same and similar parts among the embodiments are mutually referred to or described with reference to the corresponding method embodiment, and each embodiment focuses on the differences from the other embodiments. Reference is made to the description of the method embodiments. The specific details can be obtained according to the descriptions of the foregoing method embodiments, and all of them should fall within the scope of the implementation protected by this application, and no further description is given to implementation schemes of the embodiments one by one.

The apparatus for determining a graph boundary according to a point set in the foregoing embodiment may obtain a graph boundary that matches an actual distribution situation of a business object. The graph boundary can be used as a recommended region of an operation region, and reliable data basis is provided for operation management and division such as offline operation or online planning.

The method or the apparatus for determining a graph boundary according to a point set provided in the embodiment of the present disclosure may be implemented in a computer by executing a corresponding program instruction by a processor, for example, by using a C + + language of a Windows operating system at a PC end, based on a Linux system, or by using Android and iOS system programming languages, for example, at an intelligent terminal, or by using a server cluster, cloud processing/cloud computing, a block chain, and processing logic based on quantum computing, and the like. An embodiment of the present specification further provides a processing device for implementing the method or apparatus, including: at least one processor and a memory for storing processor-executable instructions, the processor implementing the implementation steps described in any one of the method embodiments of the present specification when executing the memory-stored executable instructions.

The present specification also provides a system for determining a graphical boundary from a set of points, which may be a device employing any one of the method embodiments of the specification or comprising any one of the apparatus embodiments of the specification in combination with necessary implementation hardware. The system may include: at least one processor and a memory for storing processor-executable instructions, which when executed by the processor perform the steps of implementing any one of the method embodiments of the present description.

As mentioned above, the specific implementation manner of the vehicle anti-theft system embodiment described above can be referred to the description of the foregoing method embodiment. The description according to the method related embodiment may further include other embodiments, and the specific implementation may refer to the description of the corresponding method embodiment, which is not described in detail herein.

The method or the apparatus or the vehicle system provided by the foregoing embodiments of this specification may implement the service logic through a computer program and record the service logic on a storage medium, where the storage medium may be read and executed by a computer, so as to implement the effect of the solution described in the embodiments of this specification. Accordingly, the present specification also provides a storage medium having stored thereon computer-executable instructions that, when executed, implement the implementation steps of any one of the method embodiments of the specification.

The storage medium may include a physical device for storing information, and generally, the information is digitized and then stored in a medium using an electric, magnetic, or optical method. The storage medium may include: devices that store information using electrical energy, such as various types of memory, e.g., RAM, ROM, etc.; devices that store information using magnetic energy, such as hard disks, floppy disks, tapes, core memories, bubble memories, and usb disks; devices that store information optically, such as CDs or DVDs. Of course, there are other ways of storing media that can be read, such as quantum memory, graphene memory, and so forth.

The foregoing description has been directed to specific embodiments of this disclosure. The embodiments described based on the above embodiments are extensible and still fall within the scope of implementations provided in the present specification. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.

The method and the device for determining the graph boundary according to the point set provided by the embodiment of the specification can acquire the point set data of the service object distribution, convert the point set data into the geometric figure surface net, and then find out the geometric figure space needing to be reserved based on the density parameter, thereby determining the preliminary graph boundary. Through the embodiment of the specification, the boundary of the operation area can be determined based on the bottom data such as the single-vehicle distribution, and the operation planning processing efficiency is improved. Meanwhile, the method and the device can uniformly output the reliable boundary graph which is consistent with the actual service condition based on the real bottom data distribution condition of the service, and effectively guarantee the planning quality and reliability of the operation area.

The embodiments of this specification are not limited to what must be rules handled by Delaunay triangulation, industry communications standards, standard programming languages, data storage rules, or as described in one or more embodiments of this specification. Certain industry standards, or implementations modified slightly from those described using custom modes or examples, may also achieve the same, equivalent, or similar, or other, contemplated implementations of the above-described examples. The embodiments using the modified or transformed data acquisition, storage, judgment, processing and the like can still fall within the scope of the alternative embodiments of the embodiments in this specification.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices and modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a server system. Of course, this application does not exclude that with future developments in computer technology, the computer implementing the functionality of the above described embodiments may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device or a combination of any of these devices.

Although one or more embodiments of the present description provide method operational steps as described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive approaches. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For example, if the terms first, second, etc. are used to denote names, they do not denote any particular order.

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, when implementing one or more of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, etc. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage, graphene storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the present specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is merely exemplary of one or more embodiments of the present disclosure and is not intended to limit the scope of one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present specification should be included in the scope of the claims.

Claims

1. A method of determining a graph boundary from a set of points, comprising:

2. The method of claim 1, further comprising:

adjusting the density parameter based on an adjusting instruction to obtain a new residual graph;

determining a new preliminary graph boundary based on the new residual graph.

3. The method of claim 1, further comprising:

searching a common node connected with polygons in the preliminary graph boundary;

performing position offset on the common node, splitting connected polygons into independent polygons or connecting the polygons into a polygon, and determining an offset-processed graph;

determining an overall graph boundary based on the offset-processed graph.

4. The method of claim 3, further comprising:

merging the polygons with nesting in the graph after the offset processing;

connecting the combined polygons to obtain a complete polygon;

a full graph boundary is determined based on the full polygon.

5. The method of claim 1, further comprising:

storing position information of nodes of the polygon by using a linked list;

traversing the line segments in the preliminary graph boundary, and judging whether the line segments can be linked with an existing linked list according to the position information of the nodes;

if the connection is available, the line segment is linked to the head or the tail of the corresponding linked list, the linked list is determined to form a polygon when the first node and the last node of the linked list are the same, and the linked list is used as the structured data of the polygon;

6. The method of claim 5, further comprising:

judging whether a plurality of linked lists can be linked into one linked list or not, or whether the current processing line segment can link the existing linked list into one linked list or not;

and if so, combining the corresponding linked lists into one linked list.

7. An apparatus for determining a boundary of a graph from a set of points, comprising:

8. The apparatus of claim 7, further comprising:

and the density adjusting module is used for adjusting the density parameters in the cutting module based on the adjusting instruction, obtaining new residual graphics according to the adjusted density parameters, and the preliminary boundary determining module is used for determining a new preliminary graphic boundary based on the new residual graphics.

9. The apparatus of claim 7, further comprising:

the polygon storage module is used for storing the position information of the nodes of the polygon by using a chain table;

the linked list processing module is used for traversing the line segments in the primary graph boundary and judging whether the line segments can be linked with the existing linked list according to the position information of the nodes; if the connection is available, the line segment is linked to the head or the tail of the corresponding linked list, the linked list is determined to form a polygon when the first node and the last node of the linked list are the same, and the linked list is used as the structured data of the polygon; if the link cannot be connected, the line segment is stored as a new linked list.

10. A processing device, comprising: at least one processor and a memory for storing processor-executable instructions, the processor implementing the method of any one of claims 1-6 when executing the instructions.

11. A storage medium having stored thereon computer-executable instructions that, when executed, implement the method of any one of claims 1-6.