CN106886796B - Icon position identification method and device and terminal equipment - Google Patents
Icon position identification method and device and terminal equipment Download PDFInfo
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Abstract
The invention provides an icon position identification method and device and terminal equipment. The method comprises the following steps: selecting a sample icon; extracting image characteristic points of the picture and the sample icon; matching the image characteristic points of the image and the sample icon to obtain a characteristic point combination matched with each other; calculating the distance value of two image characteristic points in each characteristic point combination to obtain a reference distance value; when the distance value between two image feature points in the feature point combination is smaller than the reference distance value, taking the image feature point combination as the optimal feature point combination; when the number of the optimal feature point combinations exceeds a threshold value, calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations; and taking the average coordinate value corresponding to the coordinate in the picture as the coordinate of the icon in the picture. The method does not need to initialize and train the characteristic points when the icon position is obtained, and has low requirements on the pixel definition of the picture, high recognition speed, high accuracy and strong reusability.
Description
Technical Field
The invention relates to the field of image recognition, in particular to an icon position recognition method and device and terminal equipment.
Background
When online, the online efficiency of the online game is high, and in order to improve the online efficiency of the online game, the current method is to implement the automatic online without audit. However, the disadvantage of this is that some online game icons have logo (trademark) corner marks or watermarks appearing in screenshots, and how to accurately judge and remove the positions of the logo corner marks and watermarks becomes a difficult problem to be solved urgently. The current processing scheme in the industry is to use an OpenCV (open source license based cross-platform computer vision library) component to train a logo and a sample picture for object recognition, but the scheme has high requirements on the pixel definition of the picture, and the algorithm is too complex, a large number of logo sample pictures are required for training, the recognition efficiency is low, and the use is complex.
Disclosure of Invention
In view of the above, the present invention provides an icon position identifying method, an icon position identifying device and a terminal device, so as to improve the above problems.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides an icon position identification method, configured to identify an icon position in a picture, where the method includes the following steps: selecting a sample icon; extracting image characteristic points of the picture and the sample icon respectively; matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination; calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value; when the distance value between two image feature points in the feature point combination is smaller than the reference distance value, taking the image feature point combination as an optimal feature point combination; when the number of the optimal feature point combinations exceeds a threshold value, calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations; and taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
In a second aspect, an embodiment of the present invention provides an icon position identifying apparatus, configured to identify a position of an icon in a picture, where the apparatus includes:
the selection module is used for selecting a sample icon;
the extraction module is used for extracting image characteristic points of the picture and the sample icon;
the matching module is used for matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination;
the calculation module is used for calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value;
the screening module is used for taking the image characteristic point combination of which the distance value between the two image characteristic points in the characteristic point combination is smaller than the reference distance value as an optimal characteristic point combination;
the calculation module is further used for calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations when the number of the optimal feature point combinations exceeds a threshold value;
and the positioning module is used for taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
In a third aspect, an embodiment of the present invention provides a terminal device, including:
a processor;
a memory; and
an icon position identifying device installed in the memory and including one or more software function modules executed by the processor, the icon position identifying device comprising:
the selection module is used for selecting a sample icon;
the extraction module is used for extracting image characteristic points of the picture and the sample icon;
the matching module is used for matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination;
the calculation module is used for calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value;
the screening module is used for taking the image characteristic point combination of which the distance value between the two image characteristic points in the characteristic point combination is smaller than the reference distance value as an optimal characteristic point combination;
the calculation module is further used for calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations when the number of the optimal feature point combinations exceeds a threshold value;
and the positioning module is used for taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
According to the icon position identification method, the icon position identification device and the terminal equipment, the image feature points of the sample icon and the image are extracted, the feature point combinations matched with each other in the sample icon and the image are obtained, the optimal feature point combination is screened out from the feature point combinations, when the optimal feature point combination meets the requirements, the average coordinate value of the image feature points in the image in all the optimal feature point combinations is calculated, and the average coordinate value is used as the position coordinate of the icon in the image. Compared with the prior art, the method does not need to initialize and train the characteristic points when the icon position is obtained, and has the advantages of low requirement on the pixel definition of the picture, high recognition speed, high accuracy and strong reusability.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a block diagram of a terminal device according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a functional module architecture of an icon position identifying apparatus according to an embodiment of the present invention.
Fig. 3 is a flowchart of an icon position identifying method according to an embodiment of the present invention.
Icon: 100-a terminal device; 110-icon position identification means; 111-selecting a module; 112-an extraction module; 113-a matching module; 114-a calculation module; 115-a screening module; 116-a positioning module; 120-a memory; 130-a processor.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 of the present invention 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.
The icon position identification method and device provided by the embodiment of the invention are applied to terminal equipment. The terminal device may be, but is not limited to, a Personal Computer (PC), a smart phone, a tablet PC, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), and the like.
Fig. 1 is a block diagram of the terminal device 100. The terminal device 100 includes an icon position recognition means 110, a memory 120, and a processor 130.
The elements of the memory 120 and the processor 130 are electrically connected to each other directly or indirectly to enable data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The icon position recognition means 110 includes at least one software function module that can be stored in the memory 120 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the terminal device 100. The processor 130 is used for executing executable modules stored in the memory 120, such as software functional modules and computer programs included in the icon position identifying device 110.
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 memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction.
Referring to fig. 2, a functional module architecture of the position recognition device 110 is shown. The icon position identifying device 110 is used for quickly identifying the icon and the position thereof in the picture. The icon position identifying device 110 includes a selecting module 111, an extracting module 112, a matching module 113, a calculating module 114, a filtering module 115 and a positioning module 116.
The selecting module 111 is configured to select a sample icon. A sample icon library is stored in the terminal device 100, and includes a plurality of sample icons, which are various common logos (trademarks) and watermarks. In this embodiment, the selecting module 111 randomly selects one sample icon in the sample icon library.
The extraction module 112 is configured to extract image feature points of the picture and the sample icon. The image feature points refer to points in the image which have vivid characteristics and can effectively reflect the essential features of the image and can identify target objects in the image. The image Feature points may be obtained through a plurality of visual algorithms, such as a Scale-invariant Feature transform (SIFT) algorithm, a Speeded Up Robust Feature (Speeded Up Robust Feature) algorithm, and the like.
The matching module 113 is configured to match the image feature points of the picture with the image feature points of the sample icon, so as to obtain a feature point combination matched with each other. Since both the picture and the sample icon include a plurality of image feature points, some image feature points in the picture and some image feature points in the sample icon match, i.e., have the same image feature points. The matching module 113 obtains a feature point combination by matching image feature points of the picture and the sample icon, for example, if there is an image feature point P1 in the picture and there is an image feature point P2 in the sample icon, and if P1 and P2 match each other, then a feature point combination is obtained (P1, P2). The matching of the feature points can be realized according to various matching algorithms, and in this embodiment, a FLANN-BASED algorithm in OpenCV is adopted for matching.
The number of the feature point combinations is determined according to the actual situation, and after the matching module 113 obtains the feature point combinations, the calculating module 114 is configured to calculate a distance value between two image feature points in each feature point combination to obtain a reference distance value. For example, when the feature point combination is (P1, P2), the distance between P1 and P2 is calculated. After the distance value of each feature combination point is obtained in the above manner, the calculation module 114 sorts each obtained distance value to obtain a minimum distance value, and the sorting and selecting manner of the minimum distance value is faster and more accurate. After obtaining the minimum distance value, the calculating module 114 obtains a reference distance value through the minimum distance value, in this embodiment, the calculating method of the reference distance value is as follows:
L＝α×Dmin
wherein, L is the reference distance value to be obtained, alpha is the preset coefficient, DminIs the minimum distance value. The value of α is set according to the actual application scenario, for example, the value of α can be set to 3 in logo removal.
After the calculation module 114 calculates the reference distance value, the screening module 115 compares the distance value between two image feature points in each feature point combination with the reference distance value, if the distance value between two image feature points is smaller than the reference distance value, the screening module 115 uses the feature point combination as an optimal feature point combination, and the optimal feature point combination is obtained for selecting the feature point combination to obtain a more accurate result. For example, if the minimum distance value is 1 and the preset coefficient is 3, the reference distance value is 1 × 3 — 3, and the set of optimal feature point combinations includes feature point combinations corresponding to distance values 1.5, 1.7, 1.9, 5.5, and 7.8, then the feature point combinations corresponding to distance values 1.5, 1.7, and 1.9 are used as the optimal feature point combinations.
After the optimal feature point combinations are determined, when the number of the optimal feature point combinations exceeds a threshold, the calculating module 114 calculates average coordinate values of image feature points in pictures in all the optimal feature point combinations. The value of the threshold is set according to an actual application scenario, which is not limited in this embodiment. The average coordinate value calculation method of the image feature points may be obtained by averaging the horizontal coordinate values and the vertical coordinate values of the image feature points in the picture in the optimal feature point combination, for example, the number of the optimal feature point combinations is 6, the threshold is 3, 6>3, and the average coordinate values are, assuming that the coordinates of the image feature points in the picture in the 6 optimal feature point combinations are (2, 5), (4, 7), (6, 9), (9, 6), (11, 13), (16, 14), respectively:
finally, the average coordinate value is calculated to be (8, 9).
After the calculating module 114 calculates the average coordinate value, the positioning module 116 is configured to use the coordinate in the picture corresponding to the average coordinate value as the coordinate of the icon in the picture. For example, according to the above example, in the picture, the coordinate with the coordinate value of (8, 9) is the position where the icon exists in the picture.
When the matching module 113 does not match the image feature points matched with each other or the number of the best feature point combinations obtained by screening by the screening module 115 is smaller than the threshold value, it indicates that there is no icon in the picture. The selecting module 111 performs the next round of selection, and selects another sample icon from the icon library for recognition.
The icon position recognition device 110 provided by the embodiment of the invention can be used for quickly recognizing and positioning the icon in the picture, so that the steps of initializing and training the characteristic points in the traditional recognition mode are omitted, and the invention has low requirements on the pixel definition of the picture, high recognition speed, high accuracy and strong reusability.
The embodiment of the present invention further provides an icon position identification method, please refer to fig. 3, which includes the following steps:
step S201, a sample icon is selected.
In the embodiment of the present invention, the step S201 may be performed by the selecting module 111.
Step S202, extracting image characteristic points of the picture and the sample icon.
In the present embodiment, this step S202 may be performed by the extraction module 112.
Step S203, matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination.
In the present embodiment, this step S203 may be performed by the matching module 113.
Step S204, calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value. Preferably, the step S204 includes: and calculating a distance value between two image feature points in each feature point combination to obtain a minimum distance value, and obtaining a reference distance value according to the minimum distance value. And obtaining a minimum distance value by sequencing each distance value, and multiplying the minimum distance value by a preset coefficient to obtain a reference distance value.
In this embodiment, this step S204 may be performed by the calculation module 114.
In step S205, it is determined whether the distance value between two image feature points in the feature point combination is smaller than a reference distance value. If yes, step S206 is executed, and if no, step S201 is executed to select another sample icon for identification.
In step S206, the image feature point combination is used as an optimal feature point combination.
In the present embodiment, step S205 and step S206 may be performed by the filtering module 115.
Step S207, determining whether the number of the optimal feature point combinations exceeds a threshold. If yes, step S208 is executed, and if no, step S201 is executed to select another sample icon for identification.
Step S208, calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations.
In the present embodiment, step S208 may be performed by the calculation module 114.
In step S209, the average coordinate value is set to correspond to the coordinates in the picture as the coordinates of the icon in the picture.
In the present embodiment, step S209 may be performed by the positioning module 116.
Since each step in the icon position identifying method can be executed by each function module in the icon position identifying device 110, the principle thereof has been explained in the foregoing embodiments, and is not described herein again.
In summary, the embodiments of the present invention provide an icon position identification method, an icon position identification device, and a terminal device. The method comprises the steps of extracting image feature points of a sample icon and a picture, obtaining feature point combinations matched with each other in the sample icon and the picture, screening out the optimal feature point combinations in the feature point combinations, calculating average coordinate values of the image feature points in the picture in all the optimal feature point combinations when the optimal feature point combinations meet requirements, and taking the average coordinate values as position coordinates of the icon in the picture. Compared with the prior art, the method does not need to initialize and train the characteristic points when the icon position is obtained, and has the advantages of low requirement on the pixel definition of the picture, high recognition speed, high accuracy and strong reusability.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may 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: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of 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.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in 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.
Claims (11)
1. An icon position identification method is used for identifying the position of an icon in a picture, and is characterized by comprising the following steps:
randomly selecting a sample icon from a sample icon library;
extracting image characteristic points of the picture and the sample icon respectively;
matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination;
calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value;
when the distance value between two image feature points in the feature point combination is smaller than the reference distance value, taking the image feature point combination as an optimal feature point combination;
when the number of the optimal feature point combinations exceeds a threshold value, calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations;
and taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
2. The icon position identifying method according to claim 1, wherein the step of calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value comprises:
calculating a distance value between two image feature points in each feature point combination to obtain a minimum distance value;
the reference distance value is obtained by the minimum distance value.
3. The icon position identifying method according to claim 2, wherein the step of calculating a distance value between two image feature points in each feature point combination to obtain a minimum distance value comprises:
and calculating the distance value between the two image feature points in each feature point combination, and sequencing each distance value to obtain the minimum distance value.
4. The icon position identifying method according to claim 2, wherein the step of obtaining the reference distance value by the minimum distance value comprises:
and multiplying the minimum distance value by a preset coefficient to obtain the reference distance value.
5. The icon position identifying method as claimed in claim 1, wherein when the number of the optimal feature point combinations is lower than a threshold value, another sample icon is selected from the sample icon library for identification.
6. An icon position recognition apparatus for recognizing the position of an icon in a picture, the apparatus comprising:
the selection module is used for randomly selecting a sample icon from a sample icon library;
the extraction module is used for extracting image characteristic points of the picture and the sample icon;
the matching module is used for matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination;
the calculation module is used for calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value;
the screening module is used for taking the image characteristic point combination of which the distance value between the two image characteristic points in the characteristic point combination is smaller than the reference distance value as an optimal characteristic point combination;
the calculation module is further used for calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations when the number of the optimal feature point combinations exceeds a threshold value;
and the positioning module is used for taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
7. The icon position identifying device according to claim 6, wherein the calculating module calculates a distance value between two image feature points in each feature point combination, and obtaining the reference distance value comprises:
calculating a distance value between two image feature points in each feature point combination to obtain a minimum distance value;
the reference distance value is obtained by the minimum distance value.
8. The icon position identifying device according to claim 7, wherein the calculating module calculates a distance value between two image feature points in each feature point combination, and the obtaining of the minimum distance value comprises:
and calculating the distance value between the two image feature points in each feature point combination, and sequencing each distance value to obtain the minimum distance value.
9. The icon position identifying apparatus of claim 7, wherein the calculating module obtains the reference distance value through the minimum distance value comprises:
and multiplying the minimum distance value by a preset coefficient to obtain the reference distance value.
10. The icon position identifying device as claimed in claim 6, wherein when the number of the optimal feature point combinations is lower than a threshold, the selecting module is configured to randomly select another sample icon from the sample icon library for identification.
11. A terminal device, comprising:
a processor;
a memory; and
an icon position identifying device installed in the memory and including one or more software function modules executed by the processor, the icon position identifying device comprising:
the selection module is used for randomly selecting a sample icon from a sample icon library;
the extraction module is used for extracting image characteristic points of the picture and the sample icon;
the matching module is used for matching the image characteristic points of the picture with the image characteristic points of the sample icon to obtain a mutually matched characteristic point combination;
the calculation module is used for calculating a distance value between two image feature points in each feature point combination to obtain a reference distance value;
the screening module is used for taking the image characteristic point combination of which the distance value between the two image characteristic points in the characteristic point combination is smaller than the reference distance value as an optimal characteristic point combination;
the calculation module is further used for calculating the average coordinate value of the image feature points in the pictures in all the optimal feature point combinations when the number of the optimal feature point combinations exceeds a threshold value;
and the positioning module is used for taking the coordinate of the average coordinate value corresponding to the picture as the coordinate of the icon in the picture.
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