CN111563181A - Digital image file query method and device and readable storage medium - Google Patents
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Abstract
The application discloses a digital image file query method, a digital image file query device and a computer readable storage medium. Adding the acquired target digital image and the digital image set to be retrieved to a pre-constructed display container, and assigning values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped and are displayed in a display container according to a preset row-column format; extracting image features, numerical features and position relation features of the target digital image as identification features, wherein the numerical features and the position relation features are determined based on the value assignment of each digital image and the position coordinates of a display container where the digital image is located; the position relation characteristic is used for determining a required position relation condition; digital images to be retrieved which meet the position relation condition and are the same as the image content of the target digital image are inquired from the digital image set to be retrieved based on the identification characteristics, so that the digital image is inquired efficiently and quickly.
Description
Technical Field
The present application relates to the field of information retrieval technologies, and in particular, to a method and an apparatus for querying a digital image file, and a computer-readable storage medium.
Background
With the rapid development of data detection technology, retrieval based on text information does not meet the information retrieval requirements of users, and image retrieval technology comes up. The traditional digital image is matched and inquired by extracting the characteristics of color, texture, shape, gray level and the like of the image as retrieval characteristics in the retrieval process. Commonly used are color-based search methods, image search methods based on texture features such as statistical methods, spectral methods, and model methods, and shape search methods based on edges and regions. However, these classical methods are based on artificial design features, and the quality of the design method directly affects the image retrieval effect. It can be appreciated that deep learning, as a perplexing in machine learning, has the advantage of automatically learning data features with big data to account for uncertainty due to artifacts. Based on this, in order to solve technical drawbacks of the conventional digital image, the related art applies deep learning to the field of image data retrieval.
However, the related art directly inputs the original image into a deep learning model such as a convolutional neural network, and does not consider the situation that the object or region of interest may appear in different regions of the image, the size and the application field of the image may also be different. Meanwhile, the dimension of the depth feature is high, and the method for searching the big data image by directly utilizing the depth feature is not feasible in practical application. Especially in the actual multi-image input process, the inconvenient agility in the aspect of similarity measurement between features is generally calculated by adopting the distance between vectors, and for batch digital images, the simple distance between vectors cannot truly reflect the similarity and the degree of association between the digital images. In addition, in the process of searching a plurality of digital picture files, the position relation between picture elements such as pixels and colors and the random hash needs to be calculated when the relation is determined, the calculation is complex, and the method is not suitable for efficient query of similar array combinations with numerical relations. Particularly, when the method is used for the comparison relation query of big data, for example, in the data analysis process of different types of commodity sales data of enterprises or personnel identity characteristic data and the like, numerical values are required to be flexibly and dynamically given to represent the relation meaning.
In view of this, how to efficiently and quickly perform digital image query is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The application provides a digital image file query method, a digital image file query device and a computer readable storage medium, which can efficiently and quickly realize digital image query.
In order to solve the above technical problems, embodiments of the present invention provide the following technical solutions:
an embodiment of the present invention provides a digital image file query method, including:
adding the acquired target digital image and the digital image set to be retrieved to a pre-constructed display container, and assigning values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped with each other and are displayed in the display container according to a preset row-column format;
extracting the identification features of the target digital image; the identification features comprise image features, numerical features and positional relationship features, the numerical features and the positional relationship features being determined based on the assigned value of each digital image and the positional coordinates of the display container in which it is located; the position relation characteristic is used for determining a position relation condition required by the target digital image;
and inquiring the digital image to be retrieved which meets the position relation condition and is the same as the image content of the target digital image from the digital image set to be retrieved based on the identification feature.
Optionally, the number of the target digital images is multiple, and the extracting the identification features of the target digital images includes:
extracting the image characteristics of each target digital image to obtain the total number of the target digital images;
if the number of the target digital images is not more than 2, calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image; taking the linear distance, the magnitude relationship, the sum relationship, and image features of the first and second target digital images as the recognition features;
if the number of the target digital images is more than 2 but not more than 3, calculating the linear distance between any two and the angle value formed by the linear distance and the position coordinates of the first target digital image, the second target digital image and the third target digital image, and calculating the magnitude relation and the sum value relation among the assigned natural numerical values of the first target digital image, the second target digital image and the third target digital image; taking the image features of the plurality of sets of linear distances, the angle values, the magnitude relationship, the sum relationship, the first target digital image, the second target digital image, and the third target digital image as the recognition features;
if the number of the target digital images is more than 3, calculating a linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three target digital images according to the position coordinates of the target digital images, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the target digital images; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of each target digital image as the identification characteristics.
Optionally, the number of the target digital images is 1, and the extracting the identification features of the target digital images includes:
if the assignment rule indicates that the assignment of all the digital images in the same column of the display container is the same;
the assigned value and image features of the target digital image are taken as identifying features.
Optionally, the assignment rule is to assign a natural number to each digital image in the display container in a manner of sequentially increasing by 1 from the first column to the last column.
Optionally, after the digital image to be retrieved, which satisfies the position relationship condition and has the same image content as the target digital image, is queried from the digital image set to be retrieved based on the identification feature, the method further includes:
and outputting the position information of the digital image to be retrieved, which meets the position relation condition and has the same image content with the target digital image, and simultaneously displaying the digital image obtained by query to a user.
Optionally, before adding the acquired target digital image and the digital image set to be retrieved to the pre-constructed display container, the method further includes:
and determining the target digital image and the digital image set to be retrieved according to the received touch instruction.
Another aspect of the embodiments of the present invention provides a digital image file query apparatus, including:
the image acquisition module is used for acquiring a target digital image and a digital image to be retrieved;
the image storage module is used for adding the target digital image and the digital image set to be retrieved to a pre-constructed display container;
the image assignment module is used for assigning values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped with each other and are displayed in the display container according to a preset row-column format;
the characteristic extraction module is used for extracting the identification characteristics of the target digital image; the identification features comprise image features, numerical features and positional relationship features, the numerical features and the positional relationship features being determined based on the assigned value of each digital image and the positional coordinates of the display container in which it is located; the position relation characteristic is used for determining a position relation condition required by the target digital image;
and the image retrieval module is used for inquiring the digital image to be retrieved which meets the position relation condition and is the same as the image content of the target digital image from the digital image set to be retrieved based on the identification characteristic.
Optionally, the feature extraction module includes:
the image characteristic extraction submodule is used for extracting the image characteristics of each target digital image;
the first-class identification feature generation sub-module is used for taking the assigned value and the image feature of the target digital image as identification features if the assignment rule is that the assigned values of the digital images in the same column of the display container are the same;
the second type recognition feature generation submodule is used for calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image if the number of the target digital images is not larger than 2; taking the linear distance, the magnitude relationship, the sum relationship, and image features of the first and second target digital images as the recognition features;
a third-class recognition feature generation submodule, configured to calculate, if the number of the target digital images is greater than 2 but not greater than 3, a linear distance between any two and an angle value formed by the linear distance and the position coordinates of the first target digital image, the second target digital image, and the third target digital image, and calculate a magnitude relationship and a sum relationship between assigned natural numerical values of the first target digital image, the second target digital image, and the third target digital image; taking the image features of the plurality of sets of linear distances, the angle values, the magnitude relationship, the sum relationship, the first target digital image, the second target digital image, and the third target digital image as the recognition features;
the fourth type recognition feature generation submodule is used for calculating a linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three according to the position coordinates of the target digital images and calculating the magnitude relation and the sum value relation between assigned natural numerical values of the target digital images if the number of the target digital images is larger than 3; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of each target digital image as the identification characteristics.
The embodiment of the present invention further provides a digital image file query device, which includes a processor, and the processor is configured to implement the steps of the digital image file query method according to any one of the preceding items when executing the computer program stored in the memory.
Finally, an embodiment of the present invention provides a computer-readable storage medium, where a digital image file query program is stored on the computer-readable storage medium, and when executed by a processor, the digital image file query program implements the steps of the digital image file query method according to any one of the foregoing items.
The technical scheme provided by the application has the advantages that the image of the same type relation with the target digital image in all the digital image sets to be retrieved is inquired in a mode of combining the numerical relation of the image and the relation of the area where the image is located, deep learning of image characteristics is not needed, the position relation of picture elements such as pixels and colors between the target digital image and the image to be retrieved and random hashing is not needed to be calculated, the calculating process is simple, operation is convenient, the digital images meeting the position relation and the image content at the same time can be inquired efficiently and quickly, and the method can be used for forming an efficient inquiring method for big data analysis in an image searching mode.
In addition, the embodiment of the invention also provides a corresponding implementation device and a computer readable storage medium for the digital image file query method, so that the method has higher practicability, and the device and the computer readable storage medium have corresponding advantages.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the related art, the drawings required to be used in the description of the embodiments or the related art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a digital image file query method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating an arrangement of digital images in a display container according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a feature extraction process provided in an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a relationship between two target digital images according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the relationship between three target digital images according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of the relationship between four target digital images according to an embodiment of the present invention;
FIG. 7 is a flowchart illustrating another digital image file query method according to an embodiment of the present invention;
fig. 8 is a structural diagram of an embodiment of a digital image file query device according to an embodiment of the present invention;
fig. 9 is a block diagram of another embodiment of a digital image file query device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope 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.
The terms "first," "second," "third," "fourth," and the like in the description and claims of this application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements but may include other steps or elements not expressly listed.
Having described the technical solutions of the embodiments of the present invention, various non-limiting embodiments of the present application are described in detail below.
Referring to fig. 1, fig. 1 is a schematic flow chart of a digital image file query method according to an embodiment of the present invention, where the embodiment of the present invention includes the following:
s101: and acquiring a target digital image and a digital image set to be retrieved.
In this application, a digital image refers to an image whose image content is a natural number, that is, a digital image is an image generated by taking a natural number without any background. The image content on the digital image is 10 natural numbers 0-9, and each digital image has only one number. The target digital image is an image of a target type that the user wants to retrieve from the database, for example, the user wants to retrieve all images with the number 2 from the database, the target digital image is an image with the number 2, the digital image set to be retrieved is used as an image retrieval database, that is, a retrieval range, and the digital image set to be retrieved includes a plurality of digital images to be retrieved.
The target digital image and the digital image set to be retrieved can be imported from the outside through a USB interface and the like, and can also be selected from an image database stored in the system, which does not influence the implementation of the application. In the process of selecting images from the database, in order to improve the operation flexibility and convenience, the system can be provided with a touch display screen, a user selects a target digital image and a digital image set to be retrieved through the touch display screen, and the system determines the target digital image and the digital image set to be retrieved after receiving a touch instruction of the user.
S102: and adding the target digital image and the digital image set to be retrieved to a pre-constructed display container, and assigning values to the digital images in the display container according to a preset assignment rule.
The display container of the embodiment of the invention is a storage queue and is used for storing the target digital image and the digital image set to be retrieved. The target digital image and each digital image to be retrieved in the set of digital images to be retrieved do not overlap each other and are arranged in a display container according to a predetermined line and column format, such as shown in fig. 2. The target digital image and each digital image to be retrieved in the digital image set to be retrieved may be randomly placed in a display container, and after both are placed in the display container, position information, such as the row and column, or coordinate information, of the target digital image in the container in which the target digital image is located is determined in the display container.
After the target digital image and the digital image set to be retrieved are added to the display container, values can be assigned to the digital images in the container according to preset assignment rules. The assignment rule may assign a natural number to each digital image in the display container in a manner of sequentially increasing 1 from the first column to the last column, and the assignment of each digital image in the same column is the same, as shown in fig. 2.
S103: and extracting the identification features of the target digital image.
It is understood that the target digital image may be one or more. For one, there is no internal relationship between the target digital images; for a plurality of target digital images, each target digital image is arranged in the display container, each target digital image forms a combination, and each target digital image in the combination has a certain internal association relationship, such as a size relationship, an angle relationship and a position relationship. Correspondingly, the retrieval result of the target digital image set formed by the plurality of target digital images is necessarily a plurality of sets, and the digital image content in each set is not only the same as that of each digital image in the target digital image set, but also meets the corresponding position relation. For example, the target digital image set includes a first target digital image and a second target digital image, the first target digital image is 2 and is located in the first row and the third column, the second target digital image is 5 and is located in the third row and the second column, then the search results are two groups, one group is the first row and the sixth column of images with the number of 2 and the third row and the fifth column of images with the number of 5, the other group is the fourth row and the third column of images with the number of 2 and the sixth row and the second column of images with the number of 5, although the image contents are the same, the positional relationship is not satisfied for the first row and the sixth column of images with the number of 2 and the sixth row and the second column of images with the number of 5, and therefore the search results are not output as a group.
In the present application, the identifying features may include image features, numerical features, and positional relationship features, the numerical features and the positional relationship features being determined based on the assigned values of the respective digital images and the positional coordinates of the display container in which they are located; the position relation characteristic is used for determining the position relation condition required by the target digital image. The image features are used for identifying the features of the image content, any existing related image feature extraction and identification method can be adopted for digital content identification, numerical features are assigned sizes of the target digital images, and if the target digital images are multiple, the numerical features can also be assigned size relations, assigned sums and the like of the multiple target digital images. Two-dimensional coordinate axes can be established in the display container, each image can be abstracted into one point, each image has a position coordinate value in the same coordinate system, and the distance between the images and the angle formed by the plurality of images can be calculated based on the position coordinate values.
S104: and inquiring the digital images to be retrieved which meet the position relation condition and are the same as the image content of the target digital image from the digital image set to be retrieved based on the identification characteristics.
In the image query process, the image which has the same image content with the target digital image needs to be queried, and a certain position relation needs to be met. For example, if the target digital image is an image with an image content of 2 in the third column of the first row, the results of the query in S104 are all digital images with an image content of 2 in the third column, and for other columns, the results of the query with an image content of 2 are not the same as the results of the query for the target digital image. The target digital image set comprises a first target digital image with a digital image content of 2 and located in the third row and the third column, and a second target digital image with an image content of 5 and located in the third row and the second column, then the retrieval result may be a result set composed of the sixth row and the sixth column with a digital number of 2 and the fifth row and the fifth column with a digital number of 5, and the images with the sixth row and the sixth column with a digital number of 2 and the sixth row with a digital number of 5, although the image contents are the same, do not satisfy the position relationship, and therefore are not output as a group of retrieval results.
It should be further noted that, since the retrieval of two factors, namely the image content and the position relationship, is involved in the image retrieval process, a candidate digital image set which is the same as the image content of the target digital image can be determined first, and then the digital image which meets the position relationship condition is selected from the candidate digital image set; of course, it may be determined to select a candidate digital image set satisfying the position relationship condition, and then select a digital image having the same image content as the target digital image from the candidate digital image set, or perform both, which does not affect the implementation of the present application.
In the technical scheme provided by the embodiment of the invention, the image of the same type relation with the target digital image in all the digital image sets to be retrieved is inquired in a mode of combining the numerical relation of the image and the relation of the area where the image is located, deep learning of image characteristics is not needed, the position relation of pixel, color and other image elements and random hash between the target digital image and the image to be retrieved is not needed to be calculated, the calculation process is simple, the operation is convenient, the digital image which simultaneously meets the position relation and the image content can be inquired efficiently and quickly, and the inquiry efficient method for big data analysis can be formed in an image searching mode.
In the foregoing embodiment, how to perform extracting the image recognition features is not limited, and an implementation manner of S103 is provided in this embodiment, please refer to fig. 3, which may include the following contents:
a: all target digital images are acquired.
B: and extracting the image characteristics of each target digital image.
In this step, the image feature is a feature that reflects which digit the image is, and any number recognition algorithm may be used to perform image feature extraction and image recognition, which is not limited in this application.
C: calculating the position relation characteristic and the digital characteristic of each target digital image, wherein as an optional implementation mode, the step C may include:
c1: judging the total number of the target digital images;
c11: and if the number of the target digital images is 1, the position relation characteristics and the digital characteristics are position information and assignment information in a display container where the images are located.
In this step, if the target digital image is 1, the positional relationship feature is a feature having no distance and no angle. And if the assignment rule is that the assignment of all the digital images in the same column of the display container is the same, taking the assignment of the target digital image as the identification feature.
C12: if the number of the target digital images is not more than 2, calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image; and taking the linear distance, the size relation and the sum value relation as identification features, and taking the image features of the first target digital image and the second target digital image. That is, in this step, the position relation feature is a feature having a distance between the target digital images, as shown in fig. 4.
C13: if the number of the target digital images is more than 2 but not more than 3, calculating the linear distance between the first target digital image and the second target digital image and the angle value formed by the first target digital image and the second target digital image according to the position coordinates of the first target digital image, the second target digital image and the third target digital image, and calculating the magnitude relation and the sum value relation among natural numerical values assigned to the first target digital image, the second target digital image and the third target digital image; and taking the image characteristics of the plurality of groups of linear distances, the angle values, the size relations, the sum value relations, the first target digital image, the second target digital image and the third target digital image as the identification characteristics. That is, in this step, the position relation feature is a distance and angle feature between the target digital images, as shown in fig. 5.
C14: if the number of the target digital images is more than 3, calculating a linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three target digital images according to the position coordinates of the target digital images, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the target digital images; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of the target digital images as identification characteristics. That is, in this step, the position relationship features are features that there are multiple groups of distances and multiple groups of angles between the target digital images, and an angle is determined for every three adjacent images, as shown in fig. 6.
D: and taking the image features of the step B and the position relation features and the digital features of the step C as identification features in the image query process of the step S104. And D, according to the result of the step D, quickly outputting the digital images which meet the condition positions and are found out according to the relation of the target digital image group in the fixed display container by the up-down and left-right translation graphics.
As another alternative implementation, please refer to fig. 7, which further includes:
s105: and outputting the position information of the digital image to be retrieved, which meets the position relation condition and has the same image content as the target digital image, and simultaneously displaying the digital image obtained by query to a user.
In the embodiment of the invention, in order to further ensure the image query accuracy, the position information such as coordinate values of the digital image to be retrieved can be output, and if the output result is incorrect, maintenance personnel can perform fault positioning based on the output coordinate values, thereby further improving the image query efficiency.
It should be noted that, in the present application, there is no strict sequential execution order among the steps, and as long as a logical order is met, the steps may be executed simultaneously or according to a certain preset order, and fig. 1 and fig. 7 are only schematic manners, and do not represent only such an execution order.
The embodiment of the invention also provides a corresponding device for the digital image file query method, so that the method has higher practicability. Wherein the means can be described separately from the functional module point of view and the hardware point of view. In the following, the digital image file query device provided by the embodiment of the present invention is introduced, and the digital image file query device described below and the digital image file query method described above may be referred to in a corresponding manner.
Based on the angle of the functional module, referring to fig. 8, fig. 8 is a structural diagram of a digital image file query device according to an embodiment of the present invention, in a specific implementation manner, where the device may include:
an image acquisition module 801, configured to acquire a target digital image and a digital image to be retrieved.
An image storage module 802 for adding the target digital image and the set of digital images to be retrieved to a pre-constructed display container.
An image assignment module 803, configured to assign values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped with each other and are displayed in the display container according to a preset row-column format.
A feature extraction module 804, configured to extract recognition features of the target digital image; the identification features comprise image features, numerical features and position relation features, and the numerical features and the position relation features are determined based on assigned values of the digital images and position coordinates of a display container in which the digital images are located; the position relation characteristic is used for determining the position relation condition required by the target digital image.
And the image retrieval module 805 is configured to query the digital image set to be retrieved for digital images to be retrieved, which satisfy the position relationship condition and have the same image content as the target digital image, based on the identification feature.
Optionally, in some implementations of this embodiment, the feature extraction module 804 may further include, for example:
the image characteristic extraction submodule is used for extracting the image characteristics of each target digital image;
the first-class identification feature generation submodule is used for taking the assigned value and the image feature of the target digital image as identification features if the assignment rule is that the assigned values of all the digital images in the same row of the display container are the same;
the second type recognition feature generation submodule is used for calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image if the number of the target digital images is not larger than 2; taking the linear distance, the size relation and the sum value relation as well as the image characteristics of the first target digital image and the second target digital image as identification characteristics;
the third-class recognition feature generation sub-module is used for calculating the linear distance between any two and the angle value formed by the linear distance and the three according to the position coordinates of the first target digital image, the second target digital image and the third target digital image and calculating the size relationship and the sum value relationship among assigned natural numerical values of the first target digital image, the second target digital image and the third target digital image if the number of the target digital images is more than 2 but not more than 3; taking the image characteristics of the plurality of groups of linear distances, the angle values, the size relations, the sum value relations, the first target digital image, the second target digital image and the third target digital image as identification characteristics;
the fourth type recognition feature generation submodule is used for calculating the linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three according to the position coordinates of the target digital images and calculating the magnitude relation and the sum value relation between the assigned natural numerical values of the target digital images if the number of the target digital images is larger than 3; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of the target digital images as identification characteristics.
In other embodiments of this embodiment, the apparatus may further include a result output module, for example, where the result output module is configured to output the position information of the digital image to be retrieved, which meets the position relationship condition and has the same image content as the target digital image, and simultaneously display the digital image obtained by the query to the user.
Alternatively, the image acquisition module 801 may also be a module for determining the target digital image and the digital image set to be retrieved according to the received touch instruction.
The functions of the functional modules of the digital image file query device according to the embodiments of the present invention can be specifically implemented according to the method in the embodiments of the method, and the specific implementation process thereof can refer to the related description of the embodiments of the method, which is not described herein again.
Therefore, the digital image query method and the digital image query device can efficiently and quickly realize digital image query.
The digital image file query device mentioned above is described from the perspective of functional modules, and further, the present application also provides a digital image file query device, which is described from the perspective of hardware. Fig. 9 is a block diagram of another digital image file querying device according to an embodiment of the present application. As shown in fig. 9, the apparatus includes a memory 90 for storing a computer program;
a processor 91, for implementing the steps of the digital image file query method as mentioned in the above embodiments when executing the computer program.
Among other things, the processor 91 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 91 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 91 may also include a main processor and a coprocessor, the main processor is a processor for processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 91 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 91 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.
The memory 90 may include one or more computer-readable storage media, which may be non-transitory. Memory 90 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 90 is at least used for storing a computer program 901, wherein the computer program can realize the relevant steps of the digital image file query method disclosed in any one of the foregoing embodiments after being loaded and executed by the processor 91. In addition, the resources stored by the memory 90 may also include an operating system 902, data 903, and the like, and the storage may be transient storage or permanent storage. The operating system 902 may include Windows, Unix, Linux, etc. Data 903 may include, but is not limited to, data corresponding to digital image file query results, and the like.
In some embodiments, the digital image file querying device may further comprise a display screen 99, an input/output interface 93, a communication interface 94, a power source 95, and a communication bus 96.
Those skilled in the art will appreciate that the configuration shown in FIG. 9 does not constitute a limitation of the digital image file querying device and may include more or less components than those shown, such as the sensor 97.
The functions of the functional modules of the digital image file query device according to the embodiments of the present invention can be specifically implemented according to the method in the embodiments of the method, and the specific implementation process thereof can refer to the related description of the embodiments of the method, which is not described herein again.
Therefore, the digital image query method and the digital image query device can efficiently and quickly realize digital image query.
It is to be understood that, if the digital image file query method in the above embodiments is implemented in the form of a software functional unit and sold or used as a stand-alone product, it may be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present application may be substantially or partially implemented in the form of a software product, which is stored in a storage medium and executes all or part of the steps of the methods of the embodiments of the present application, or all or part of the technical solutions. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an electrically erasable programmable ROM, a register, a hard disk, a removable magnetic disk, a CD-ROM, a magnetic or optical disk, and other various media capable of storing program codes.
Based on this, the embodiment of the present invention further provides a computer-readable storage medium, in which a digital image file query program is stored, and the steps of the digital image file query method according to any one of the above embodiments are performed when the digital image file query program is executed by a processor.
The functions of the functional modules of the computer-readable storage medium according to the embodiment of the present invention may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Therefore, the digital image query method and the digital image query device can efficiently and quickly realize digital image query.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The digital image file query method, device and computer readable storage medium provided by the present application are introduced in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present application.
Claims (10)
1. A digital image file query method is characterized by comprising the following steps:
adding the acquired target digital image and the digital image set to be retrieved to a pre-constructed display container, and assigning values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped with each other and are displayed in the display container according to a preset row-column format;
extracting the identification features of the target digital image; the identification features comprise image features, numerical features and positional relationship features, the numerical features and the positional relationship features being determined based on the assigned value of each digital image and the positional coordinates of the display container in which it is located; the position relation characteristic is used for determining a position relation condition required by the target digital image;
and inquiring the digital image to be retrieved which meets the position relation condition and is the same as the image content of the target digital image from the digital image set to be retrieved based on the identification feature.
2. The method as claimed in claim 1, wherein the target digital image is a plurality of target digital images, and the extracting the identification features of the target digital images comprises:
extracting the image characteristics of each target digital image to obtain the total number of the target digital images;
if the number of the target digital images is not more than 2, calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image; taking the linear distance, the magnitude relationship, the sum relationship, and image features of the first and second target digital images as the recognition features;
if the number of the target digital images is more than 2 but not more than 3, calculating the linear distance between any two and the angle value formed by the linear distance and the position coordinates of the first target digital image, the second target digital image and the third target digital image, and calculating the magnitude relation and the sum value relation among the assigned natural numerical values of the first target digital image, the second target digital image and the third target digital image; taking the image features of the plurality of sets of linear distances, the angle values, the magnitude relationship, the sum relationship, the first target digital image, the second target digital image, and the third target digital image as the recognition features;
if the number of the target digital images is more than 3, calculating a linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three target digital images according to the position coordinates of the target digital images, and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the target digital images; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of each target digital image as the identification characteristics.
3. The method for querying digital image files according to claim 1, wherein the target digital image is 1, and the extracting the identification features of the target digital image comprises:
if the assignment rule indicates that the assignment of all the digital images in the same column of the display container is the same;
the assigned value and image features of the target digital image are taken as identifying features.
4. The digital image file query method of claim 3, wherein the assignment rule is that a natural number is assigned to each line of digital images in the display container in a form of increasing 1 in sequence from the first column to the last column.
5. The method according to claim 4, wherein after the digital image file is queried from the digital image set to be retrieved based on the identification feature, the method further comprises:
and outputting the position information of the digital image to be retrieved, which meets the position relation condition and has the same image content with the target digital image, and simultaneously displaying the digital image obtained by query to a user.
6. The digital image file query method according to any one of claims 1 to 5, wherein before adding the acquired target digital image and the digital image set to be retrieved to the pre-constructed display container, further comprising:
and determining the target digital image and the digital image set to be retrieved according to the received touch instruction.
7. A digital image file query apparatus, comprising:
the image acquisition module is used for acquiring a target digital image and a digital image to be retrieved;
the image storage module is used for adding the target digital image and the digital image set to be retrieved to a pre-constructed display container;
the image assignment module is used for assigning values to the digital images in the display container according to a preset assignment rule; the target digital image and each digital image to be retrieved in the digital image set to be retrieved are not overlapped with each other and are displayed in the display container according to a preset row-column format;
the characteristic extraction module is used for extracting the identification characteristics of the target digital image; the identification features comprise image features, numerical features and positional relationship features, the numerical features and the positional relationship features being determined based on the assigned value of each digital image and the positional coordinates of the display container in which it is located; the position relation characteristic is used for determining a position relation condition required by the target digital image;
and the image retrieval module is used for inquiring the digital image to be retrieved which meets the position relation condition and is the same as the image content of the target digital image from the digital image set to be retrieved based on the identification characteristic.
8. The digital image file query device of claim 7, wherein the feature extraction module comprises:
the image characteristic extraction submodule is used for extracting the image characteristics of each target digital image;
the first-class identification feature generation sub-module is used for taking the assigned value and the image feature of the target digital image as identification features if the assignment rule is that the assigned values of the digital images in the same column of the display container are the same;
the second type recognition feature generation submodule is used for calculating the linear distance between the first target digital image and the second target digital image according to the position coordinates of the first target digital image and the second target digital image and calculating the magnitude relation and the sum relation between the assigned natural numerical values of the first target digital image and the second target digital image if the number of the target digital images is not larger than 2; taking the linear distance, the magnitude relationship, the sum relationship, and image features of the first and second target digital images as the recognition features;
a third-class recognition feature generation submodule, configured to calculate, if the number of the target digital images is greater than 2 but not greater than 3, a linear distance between any two and an angle value formed by the linear distance and the position coordinates of the first target digital image, the second target digital image, and the third target digital image, and calculate a magnitude relationship and a sum relationship between assigned natural numerical values of the first target digital image, the second target digital image, and the third target digital image; taking the image features of the plurality of sets of linear distances, the angle values, the magnitude relationship, the sum relationship, the first target digital image, the second target digital image, and the third target digital image as the recognition features;
the fourth type recognition feature generation submodule is used for calculating a linear distance between any two target digital images and a plurality of groups of angle values formed by the adjacent three according to the position coordinates of the target digital images and calculating the magnitude relation and the sum value relation between assigned natural numerical values of the target digital images if the number of the target digital images is larger than 3; and taking the multiple groups of linear distances, the multiple groups of angle values, the magnitude relation, the sum value relation and the image characteristics of each target digital image as the identification characteristics.
9. A digital image file query device, comprising a processor for implementing the steps of the digital image file query method according to any one of claims 1 to 6 when executing a computer program stored in a memory.
10. A computer-readable storage medium, on which a digital image file query program is stored, which when executed by a processor implements the steps of the digital image file query method according to any one of claims 1 to 6.
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