阅读说明：本技术 障碍物识别方法、装置、存储介质及巡检机器人 (Obstacle identification method and device, storage medium and inspection robot ) 是由 苗俊 袁齐坤 罗艺 刘立文 杨子力 尤志鹏 钱海 赵英 王璋 李祥贵 尹倩 姜 于 2019-09-09 设计创作，主要内容包括：本发明提供的障碍物识别方法、装置、存储介质及巡检机器人,涉及输电线自动化巡检领域。该障碍物识别方法包括：接收当前图像信息；提取当前图像信息中的输电线区域,其中,输电线区域内的输电线包括非直线部分和直线部分；除去非直线部分,并得到包含障碍物的兴趣区域；利用高斯滤波方法剔除兴趣区域内的背景,并进行二值化处理,以得到包含输电线的直线部分的连通区域；根据连通区域内输电线的分布情况,识别出障碍物的类型。本发明提供的障碍物识别方法、装置、存储介质及巡检机器人能够在分析深度图像信息的基础上,对图像中的障碍物进行准确识别,以使得对障碍物的定位更加精确,有助于巡检机器人的路径规划,从而提高巡检质量。(The invention provides an obstacle identification method, an obstacle identification device, a storage medium and an inspection robot, and relates to the field of automatic inspection of power transmission lines. The obstacle recognition method includes: receiving current image information; extracting a power line area in the current image information, wherein a power line in the power line area comprises a non-linear part and a linear part; removing the non-linear part and obtaining an interest area containing the obstacle; removing the background in the interest area by using a Gaussian filtering method, and performing binarization processing to obtain a connected area containing a linear part of the power transmission line; and identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area. The obstacle identification method, the obstacle identification device, the storage medium and the inspection robot provided by the invention can accurately identify the obstacle in the image on the basis of analyzing the depth image information, so that the obstacle is more accurately positioned, the path planning of the inspection robot is facilitated, and the inspection quality is improved.)

1. An obstacle recognition method for transmission line obstacle recognition, the method comprising:

receiving current image information;

extracting a power line region in the current image information, wherein the power line in the power line region includes a non-linear portion and a linear portion;

removing the non-linear part and obtaining a region of interest containing the obstacle;

removing the background in the interest area by using a Gaussian filtering method, and performing binarization processing to obtain a connected area containing the linear part of the power transmission line;

and identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area.

2. The obstacle identification method according to claim 1, wherein the step of identifying the type of the obstacle based on the distribution of the power transmission lines in the connected area comprises:

projecting pixels perpendicular to the power lines for a plurality of directions of the power lines;

identifying a type of the obstacle from the pixel projection.

3. The obstacle identification method according to claim 2, wherein the step of identifying the type of the obstacle from the pixel projection further comprises:

obtaining a distribution rule in a plurality of directions according to the pixel projection;

calculating pixel statistics of the pixel projections;

and integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

4. The obstacle identifying method according to any one of claims 1 to 3, wherein after the step of identifying the type of the obstacle based on the distribution of the transmission lines in the connected area, the method further comprises:

and calculating the geometric center of the end face of the obstacle.

5. An obstacle recognition device, comprising:

a receiving module: the receiving module is used for receiving current image information;

an extraction module: the extraction module is used for extracting a power line area in the current image information, wherein the power line in the power line area comprises a non-linear part and a linear part;

non-linear portion removing module: the nonlinear part removing module is used for removing the nonlinear part and obtaining an interest area containing the obstacle;

a removing and processing module: the eliminating and processing module is used for eliminating the background in the interest area by using a Gaussian filtering method and carrying out binarization processing to obtain a connected area containing the linear part of the power transmission line;

a type identification module: the type identification module is used for identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area.

6. The obstacle identification device of claim 5, wherein the type identification module is further configured to:

projecting pixels perpendicular to the power lines for a plurality of directions of the power lines;

identifying a type of the obstacle from the pixel projection.

7. The obstacle identification device of claim 6, wherein the type identification module is further configured to:

obtaining a distribution rule in a plurality of directions according to the pixel projection;

calculating pixel statistics of the pixel projections;

and integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

8. Obstacle identifying device according to any of claims 5-7, characterized in that the device further comprises a geometrical center calculating module for calculating a geometrical center of the end face of the obstacle.

9. An inspection robot, comprising:

a memory; and the number of the first and second groups,

a processor;

the memory stores an obstacle identification program executable on the processor, the obstacle identification program being read and executed by the processor to implement the method according to any one of claims 1-4.

10. A storage medium having stored thereon an obstacle recognition program which, when read and executed, is capable of implementing the method of any one of claims 1-4.

Technical Field

The invention relates to the field of automatic inspection of power lines, in particular to a method and a device for identifying obstacles, a storage medium and an inspection robot.

Background

At present, the inspection robot barrier is identified by adopting a method based on simple graphic primitives (such as straight lines, circles, arcs, ellipses, angular points and the like) and combining geometric structure constraint, and the method causes identification failure due to the interference of a complex background on primitive identification.

Disclosure of Invention

The invention aims to provide an obstacle identification method, an obstacle identification device, a storage medium and an inspection robot, which can identify obstacles on the running route of the inspection robot on the basis of analyzing depth image information, thereby being beneficial to realizing the positioning of the obstacles and also being beneficial to the routing planning of the inspection robot.

Embodiments of the invention may be implemented as follows:

in a first aspect, an embodiment of the present invention provides an obstacle identification method for identifying an obstacle of a power transmission line, where the method includes:

receiving current image information;

extracting a power line region in the current image information, wherein the power line in the power line region includes a non-linear portion and a linear portion;

removing the non-linear part and obtaining a region of interest containing the obstacle;

removing the background in the interest area by using a Gaussian filtering method, and performing binarization processing to obtain a connected area containing the linear part of the power transmission line;

and identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area.

Further, in an optional embodiment, the step of identifying the type of the obstacle according to the distribution of the power transmission lines in the connected area includes:

projecting pixels perpendicular to the power lines for a plurality of directions of the power lines;

identifying a type of the obstacle from the pixel projection.

Further, in an optional embodiment, the step of identifying the type of the obstacle according to the pixel projection further comprises:

obtaining a distribution rule in a plurality of directions according to the pixel projection;

calculating pixel statistics of the pixel projections;

and integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

Further, in an optional embodiment, after the step of identifying the type of the obstacle according to the distribution of the power transmission lines in the connected area, the method further comprises:

and calculating the geometric center of the end face of the obstacle.

The obstacle identification method provided by the embodiment of the invention comprises the following steps: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The obstacle identification method provided by the embodiment of the invention accurately identifies the obstacle in the image on the basis of analyzing the depth image information, so that the obstacle is more accurately positioned, the path planning of the inspection robot is facilitated, and the inspection quality is improved.

In a second aspect, an embodiment of the present invention provides an obstacle identification device for identifying an obstacle of a power transmission line, where the device includes:

a receiving module: the receiving module is used for receiving current image information;

an extraction module: the extraction module is used for extracting a power line area in the current image information, wherein the power line in the power line area comprises a non-linear part and a linear part;

non-linear portion removing module: the nonlinear part removing module is used for removing the nonlinear part and obtaining an interest area containing the obstacle;

a removing and processing module: the eliminating and processing module is used for eliminating the background in the interest area by using a Gaussian filtering method and carrying out binarization processing to obtain a connected area containing the linear part of the power transmission line;

a type identification module: the type identification module is used for identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area.

Further, in an optional embodiment, the type identification module is further configured to:

projecting pixels perpendicular to the power lines for a plurality of directions of the power lines;

identifying a type of the obstacle from the pixel projection.

Further, in an optional embodiment, the type identification module is further configured to:

obtaining a distribution rule in a plurality of directions according to the pixel projection;

calculating pixel statistics of the pixel projections;

and integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

Further, in an optional embodiment, the apparatus further comprises a geometric center calculation module, wherein the geometric center calculation module is configured to calculate a geometric center of the end face of the obstacle.

The barrier recognition device provided by the embodiment of the invention comprises: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The obstacle recognition device provided by the embodiment of the invention can accurately recognize the obstacle in the image on the basis of analyzing the depth image information, so that the obstacle can be more accurately positioned, the path planning of the inspection robot is facilitated, and the inspection quality is improved.

In a third aspect, an embodiment of the present invention provides an inspection robot, including:

a memory; and the number of the first and second groups,

a processor;

the memory stores an obstacle identification program operable on the processor, the obstacle identification program being read and executed by the processor to implement the method described above.

The inspection robot provided by the embodiment of the invention comprises: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The storage medium provided by the embodiment of the invention can accurately identify the obstacles in the image on the basis of analyzing the depth image information, so that the obstacles can be more accurately positioned, the path planning of the inspection robot is facilitated, and the inspection quality is improved.

In a fourth aspect, an embodiment of the present invention provides a storage medium, on which an obstacle identification program is stored, and when the obstacle identification program is read and executed, the method described above can be implemented.

The storage medium provided by the embodiment of the invention comprises: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The storage medium provided by the embodiment of the invention can accurately identify the obstacles in the image on the basis of analyzing the depth image information, so that the obstacles can be more accurately positioned, the path planning of the inspection robot is facilitated, and the inspection quality is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments will be briefly described below. It is appreciated that the following drawings depict only certain embodiments of the invention and are therefore not to be considered limiting of its scope. For a person skilled in the art, it is possible to derive other relevant figures from these figures without inventive effort.

Fig. 1 is a block diagram schematically illustrating a structure of an inspection robot according to an embodiment of the present invention.

Fig. 2 is a schematic block diagram of a flow of an obstacle identification method according to an embodiment of the present invention.

Fig. 3 is a schematic block flow diagram of the substeps of step S500 in fig. 2.

FIG. 4 is a schematic block diagram of a flow chart of sub-steps of sub-step S520 in FIG. 3

Fig. 5 is a block diagram illustrating a structure of an obstacle identification device according to an embodiment of the present invention.

Icon: 100-a patrol robot; 110-obstacle identification method; 111-a receiving module; 112-an extraction module; 113-non-linear portion removal module; 114-culling and processing module; 115-type identification module; 120-a memory; 130-a processor.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the 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.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.

The following detailed description of embodiments of the invention refers to the accompanying drawings.

After the overhead high-voltage transmission line is designed and constructed, certain prior information is provided, for example, the span between each tower, the number of the vibration dampers on the two sides of each tower, the type of each tower (strain tower and linear tower), the splicing sleeve in a straight line section and other information are basically determined. But the quantity of the vibration dampers is changed and the installation position is changed due to construction difference, maintenance and the like; due to external factors, phenomena such as foreign matter coverage, hardware deformation and the like often occur on the power transmission line, and heterogeneous obstacles appear. These do not allow the robot to perform autonomous navigation based solely on a priori information. When the power transmission line is designed and erected, vibration dampers are arranged on the power transmission lines on two sides of the tower in order to reduce and eliminate vibration of the power transmission lines in wind according to relevant specifications of overhead power transmission line design. In the present embodiment, the identification of the obstacle may be the identification of a vibration damper. The inspection robot can form a preliminary path plan according to the prior database, and then realize more accurate path plan through identifying and positioning the shockproof hammer. The embodiment of the invention provides accurate identification of the shockproof hammer, so that the shockproof hammer is positioned more accurately, path planning of an inspection robot is facilitated, and inspection quality is improved.

Referring to fig. 1, the present embodiment provides an obstacle identification method and an obstacle identification apparatus 110, which are applied to an inspection robot 100, and are used to identify an obstacle in the operation of the inspection robot 100, so that the operation route of the inspection robot 100 is better, and the inspection effect of the inspection robot 100 is improved. The inspection robot 100 includes a memory 120, a processor 130, and an obstacle recognition device 110.

The memory 120 and the processor 130 are electrically connected to each other, directly or indirectly, to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The obstacle recognition device 110 includes at least one software function module which may be stored in the memory 120 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the server. The processor 130 is used for executing executable modules stored in the memory 120, such as software functional modules included in the obstacle identification device 110 and an obstacle identification program that can run on the processor 130.

The memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction.

The Memory 120 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.

The Processor 130 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. The general purpose processor 130 may be a microprocessor 130. The processor 130 may also be any conventional processor 130 or the like.

Referring to fig. 2, the present embodiment provides an obstacle identification method 110, which includes the following steps.

Step S100: current image information is received.

It should be noted that, in the current image information, power lines and obstacles are included, as well as other noises such as backlights. The current image information may be derived from a camera provided on the inspection robot 100.

Step S200: and extracting the power line area in the current image information.

It should be noted that the power transmission line in the power transmission line region includes a non-linear portion and a linear portion, and the power transmission line region includes an obstacle. In this step S200, the power line region can be extracted by an image recognition method.

Step S300: the non-linear portion is removed and a region of interest containing the obstruction is obtained.

It can be understood that, in step S300, the non-linear portion is eliminated to eliminate the influence of the non-linear portion of the power line on the recognition, thereby ensuring the accuracy of the recognition.

Step S400: and eliminating the background in the interest area by using a Gaussian filtering method, and performing binarization processing to obtain a connected area containing the linear part of the power transmission line.

It should be noted that, because the camera usually includes a background in an image when shooting, the gaussian filtering method can effectively filter the background in the region of interest. After the background in the interest area is provided, binarization processing is performed on the data, so that the gray value of a pixel point of the image is 0 or 255.

Step S500: and identifying the type of the obstacle according to the distribution of the pixel points of the power transmission line in the connected region.

It should be noted that after the binarization processing is performed, there are two kinds of pixel points with gray values on the image, that is, the gray value is 0 or 255. The distribution of the pixel points in which the gray value is 0 can be calculated, the type of the obstacle can be determined, and specifically, the type of the obstacle can be obtained by comparing the distribution with the data in the prior database.

Optionally, step S500: the identification of the type of obstacle according to the distribution of the power lines in the connected region may include substep S510 and substep S520.

Substep S510: pixel projection is carried out on a plurality of directions of the power transmission line, wherein the directions are vertical to the power transmission line;

substep S520: the type of obstacle is identified from the pixel projections.

It should be noted that projecting the transmission line in multiple directions perpendicular to the transmission line can reduce the dimensionality of the calculation, thereby making the calculation simpler.

Further, the sub-step S520: the identification of the type of obstacle from the pixel projection may further include sub-steps S521, S522, and S523.

Substep S521: obtaining a distribution rule in a plurality of directions according to pixel projection;

substep S522: calculating pixel statistics of the pixel projections;

substep S523: and (4) integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

It can be understood that the distribution rules of the pixel points of different types of obstacles are different, and meanwhile, the pixel points of different types of obstacles are also different, so that different obstacle types can be identified according to the distribution rules and the statistics of the pixel points. It should be understood that for the same type of obstacle, the pixel statistics are approximately within a fixed range, and the pixel projection in a certain direction also has a similar distribution rule, so that the type of the obstacle can be identified by combining the distribution rule and the pixel statistics.

In the substep S521, the substep S522, and the substep S523, the obstacle is identified by using a method of combining the fusion multi-directional projection and the structural constraint, thereby improving the accuracy of the identification.

In an alternative embodiment, after the types of the obstacles are obtained after the above steps S100 to S500 are completed, the method may further include step S600: the geometric center of the end face of the obstacle is calculated.

It should be noted that step S600 is mainly to calculate the geometric center of the end face of the obstacle and provide a reference point for positioning the obstacle. The embodiment of the invention realizes the identification of the obstacle, and when the routing inspection robot 100 carries out route planning, the obstacle needs to be positioned based on the identification of the obstacle, so that the better route planning is realized.

The obstacle identification method 110 provided by the embodiment of the invention comprises the following steps: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The obstacle identification method 110 provided by the embodiment of the invention accurately identifies the obstacle in the image on the basis of analyzing the depth image information, so that the obstacle is more accurately positioned, the route planning of the inspection robot 100 is facilitated, and the inspection quality is improved.

Referring to fig. 5, an obstacle identification apparatus according to an embodiment of the present invention includes a receiving module 111, an extracting module 112, a non-linear portion removing module 113, a rejecting and processing module 114, and a type identifying module 115.

In this embodiment of the present invention, the receiving module 111 is configured to: current image information is received.

In the embodiment of the present invention, the step S100 is executed by the receiving module 111.

In an embodiment of the present invention, the extracting module 112 is configured to: a power line region in the current image information is extracted, wherein a power line within the power line region includes a non-linear portion and a linear portion.

In the embodiment of the present invention, the above step S200 is executed by the extracting module 112.

In an embodiment of the present invention, the non-linear portion removing module 113 is configured to: the non-linear portion is removed and a region of interest containing the obstruction is obtained.

In the embodiment of the present invention, the step S300 is performed by the non-linear portion removing module 113.

In an embodiment of the present invention, the culling and processing module 114 is configured to: and eliminating the background in the interest area by using a Gaussian filtering method, and performing binarization processing to obtain a connected area containing the linear part of the power transmission line.

In the embodiment of the present invention, the step S400 is executed by the culling and processing module 114.

In this embodiment of the present invention, the type identification module 115 is configured to: and identifying the type of the obstacle according to the distribution condition of the power transmission lines in the communication area.

In the embodiment of the present invention, the step S500 is executed by the type identification module 115.

Further, in an optional embodiment, the type identifying module 115 is further configured to: pixel projection is carried out on a plurality of directions of the power transmission line, wherein the directions are vertical to the power transmission line; the type of obstacle is identified from the pixel projections.

In an embodiment of the present invention, the above sub-step S510 and the sub-step S520 are performed by the type identifying module 115.

Further, in an optional embodiment, the type identifying module 115 is further configured to: obtaining a distribution rule in a plurality of directions according to pixel projection; calculating pixel statistics of the pixel projections; and (4) integrating the distribution rule and the pixel statistics to identify the type of the obstacle.

In the embodiment of the present invention, the above sub-step S521, sub-step S522, and sub-step S523 are performed by the type identifying module 115.

Further, in an optional embodiment, the apparatus further comprises a geometric center calculation module for calculating a geometric center of the end face of the obstacle.

In the embodiment of the present invention, the step S600 is executed by the geometric center calculating module.

The barrier recognition device provided by the embodiment of the invention comprises: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The obstacle recognition device provided by the embodiment of the invention accurately recognizes the obstacle in the image on the basis of analyzing the depth image information, so that the obstacle is more accurately positioned, the path planning of the inspection robot 100 is facilitated, and the inspection quality is improved.

The embodiment of the invention also provides a storage medium which is readable by a computer. The storage medium stores an obstacle recognition program, and the method can be implemented when the obstacle recognition program is read and executed.

The storage medium provided by the embodiment of the invention comprises: and identifying a power transmission line area according to the current image information, and removing the nonlinear area of the power transmission line in the power transmission line area to obtain an interest area containing the obstacle. During processing, firstly removing the background in the interest area, and then performing binarization processing on the background; and identifying the type of the barrier according to the distribution condition of the pixel points of the power transmission line in the communication area. During identification, the power transmission line pixel points in the current image information can be compared with the prior database to realize identification of the obstacles. The storage medium provided by the embodiment of the invention can accurately identify the obstacles in the image on the basis of analyzing the depth image information, so that the obstacles can be positioned more accurately, the path planning of the inspection robot 100 is facilitated, and the inspection quality is improved.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.