CN113744150A - Image watermarking removing method and device - Google Patents
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Abstract
The application discloses a method and a device for removing watermarks from images, relates to the technical field of computers, and aims to solve the problem that in the prior art, watermarks of different styles are poor in processing effect. The method comprises the following steps: acquiring a first target picture with a watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for removing a watermark from an image.
Background
With the rapid development of network technology, in order to protect the copyright of various pictures spread on the internet, the picture copyright owner often superimposes a visible watermark on the picture. However, many users of pictures need to use pictures without watermarks, and at this time, the pictures need to be subjected to watermarking removal.
At present, in the prior art, the image is subjected to watermark removal processing mainly based on a deep learning model, however, the image watermark removal technology based on the deep learning model cannot well process watermark patterns never seen by many models, and therefore the watermark removal effect is poor.
Disclosure of Invention
The embodiment of the application provides a method and a device for removing watermarks from images, and aims to solve the problem that in the prior art, watermarks of different styles are poor in processing effect.
In order to solve the technical problem, the embodiment of the application adopts the following technical scheme:
in a first aspect, the present application provides a method for image watermarking, the method comprising:
acquiring a first target picture with a watermark;
performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark;
carrying out covering processing on the first target area to obtain a second target area;
and performing image restoration on the second target area to obtain a second target picture without the watermark.
In a second aspect, the present application provides an apparatus for image watermarking, the apparatus comprising:
the acquisition module is used for acquiring a first target picture with a watermark;
a determining module, configured to perform watermark detection on the first target picture, and determine a first target area corresponding to the watermark, where the first target area includes the watermark;
the processing module is used for masking the first target area to obtain a second target area;
and the image restoration module is used for restoring the image of the second target area to obtain a second target picture without the watermark.
In a third aspect, the present application provides an electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method of the first aspect.
After the technical scheme is adopted, the image watermarking removing method provided by the embodiment of the application obtains the first target picture with the watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark. Therefore, the watermark detected by the target picture is covered firstly, and then the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are removed better, and the processing capacity of watermarks of different patterns is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a flowchart of an image watermarking removing method according to an embodiment of the present application;
FIG. 2 is a flowchart of an image watermarking removing method according to an embodiment of the present application;
FIG. 3 is a flowchart of an image watermarking removing method according to an embodiment of the present application;
fig. 4 is a block diagram illustrating an image watermarking removing apparatus according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. 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 application.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a flowchart of an image watermarking removing method according to an embodiment of the present application. Referring to fig. 1, an image de-watermarking method provided by an embodiment of the present application may include:
the model for performing watermark detection on the first target picture may be a deep learning model. Typical Deep learning models can be Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Belief Networks (DBN), and Stacked Auto-encoder Networks (SAEN) models, among others. The Deep Learning (DL) is a new research direction in the field of Machine Learning (ML), which is introduced into Machine Learning to make it closer to the original target, Artificial Intelligence (AI). Deep learning is the intrinsic law and expression level of the learning sample data, and the information obtained in the learning process is very helpful for the interpretation of data such as characters, images and sounds. The final aim of the method is to enable the machine to have the analysis and learning capability like a human, and to recognize data such as characters, images and sounds. Deep learning is a complex machine learning algorithm, and achieves the effect in speech and image recognition far exceeding the prior related art.
In the embodiment of the present application, the first target region may be irregular, that is, the original shape of the watermark; it may also be regular, for example a quadrilateral area containing the watermark.
it should be understood that the manner of performing the masking process on the first target region may be selected according to practical application, and is not limited herein. For example, the first target area may be painted with a color that is distinguished from the original image of the target picture, or may be completely masked with a pure color image.
The second target region may be a defective region in the first target picture, that is, a region of the first target picture that needs to be subjected to image restoration.
And 140, performing image restoration on the second target area to obtain a second target picture without the watermark.
In this embodiment, the second target picture without the watermark may be obtained after the first target picture with the watermark is processed, that is, the second target picture may be a complete, natural, and image without the watermark that is substantially identical to the original image of the first target picture.
The method for removing the watermark of the image, provided by the embodiment of the application, comprises the steps of obtaining a first target picture with the watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark. Therefore, the watermark detected by the target picture is covered firstly, and then the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are removed better, and the processing capacity of watermarks of different patterns is improved.
In the present embodiment, step 120 can be implemented in various different ways.
A specific implementation example is given below. It is to be understood that the following are merely examples, and are not intended to be limiting.
Referring to fig. 2, the specific process of determining the first target area corresponding to the watermark in step 120 may include: step 210 and step 220. These two steps are explained below.
in the embodiment of the present application, in order to perform subsequent masking on the minimum area including the watermark and perform better image restoration, a quadrilateral may be selected to determine the minimum area of the watermark in the first target picture. The quadrilateral area can be a diamond, a parallelogram, a rectangle, and the like.
In this way, the position of the watermark can be clearly divided from other areas of the first target picture, so that the steps of the subsequent image de-watermarking method can be better performed.
According to the image watermark removing method provided by the embodiment of the application, the minimum quadrilateral area containing the watermark is determined for the watermark detected by the target picture, then the quadrilateral area is covered, and finally the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are better removed, and the processing capacity of watermarks of different patterns is improved.
Optionally, in an embodiment of the present application, the determining the minimum quadrilateral area corresponding to the watermark in step 210 may include: determining a plurality of position coordinates of the watermark in a coordinate system based on the pre-established coordinate system; determining at least four target position coordinates from the plurality of position coordinates, wherein the four target position coordinates comprise at least two position coordinates located on a first straight line and at least two position coordinates located on a second straight line, and the first straight line and the second straight line are not coincident; and determining the minimum quadrilateral area corresponding to the watermark based on the four target position coordinates. Therefore, the minimum quadrilateral area corresponding to the watermark can be better determined in a coordinate mode.
The pre-established coordinate system may be a two-dimensional coordinate system, for example, the image area of the first target picture may be a four-quadrant two-dimensional coordinate system, and the two-dimensional coordinate system is established by taking the upper left corner of the first target picture as a coordinate origin (0, 0), the horizontal right side as a positive half axis of a horizontal coordinate, and the vertical downward side as a negative half axis of a vertical coordinate. The four target positions may be four vertices of the quadrangular region, so that the position of the quadrangular region is better described by coordinates of the four target positions.
In this embodiment of the present application, in the process of performing watermark detection, the first target picture with a watermark may be input into a pre-trained deep learning model, and the position of the watermark is determined according to an output result of the pre-trained deep learning model.
In order to more conveniently represent the coordinates of the quadrilateral region, in an embodiment of the present application, the RGB color values of each pixel in the first target picture may be determined according to the principle of three primary colors, and the one pixel may be a unit cell of the two-dimensional coordinate system, that is, the side length of the one pixel may be a unit length of the two-dimensional coordinate system. That is, the first target picture may be divided into a grid form by pixels, so that the coordinates of each position in the first target picture can be determined more conveniently.
The RGB color scheme is a color standard in the industry, and various colors are obtained by changing three color channels of red (R), green (G), and blue (B) and superimposing the three color channels on each other, where RGB represents colors of the three channels of red, green, and blue, and the color standard almost includes all colors that can be perceived by human vision, and is one of the most widely used color systems. In a computer, the "number" of RGB means brightness, and is expressed by an integer. Typically, RGB each has 256 levels of brightness, numerically represented as from 0, 1, 2. Note that although the number is 255 at the highest, 0 is also one of the numbers, and thus there are 256 levels. By calculation, 256 levels of RGB colors can combine to form about 1678 thousands of colors, i.e., 256 × 256 × 16777216. Also commonly referred to simply as 1600 or million. Also known as 24-bit color (24 th power of 2).
Therefore, the coordinates of the four vertexes of the quadrilateral area are determined by introducing the RGB color values, so that the position of the watermark is more conveniently determined, and the subsequent step of removing the watermark is better carried out.
In this embodiment of the application, the masking the first target region in step 130 to obtain a second target region may include: and filling the first target area with pure color to obtain a second target area with pure color.
It should be understood that a pure color picture may be used to mask the first target region to obtain a pure color second target region. Wherein the solid color may be black.
It is understood that the solid color may be a color having a large difference from a color included in an original image of the first target picture. That is, the selection of the solid color in the embodiment of the present application may be selected according to actual situations, and is not limited herein. For example, when the first target picture is a light color series image, the first target area may be filled with black; when the first target picture is a dark color image, the first target area may be filled with white.
In the process of removing watermarks, for example, many watermarks have different characters, icons, sizes, transparencies and the like, which all cause the difficulty of the existing image watermark removing technology to be greatly increased. Therefore, after the region of the target picture with the watermark is covered, the influence of different types of watermarks on the watermark removing effect is eliminated, and various watermarks can be converted into a condition that the covered part is repaired through the surrounding part of the image.
In the embodiment of the present application, step 140 can also be implemented in various different ways. It is to be understood that the following are merely examples, and are not intended to be limiting.
In step 140, the image restoration of the second target area may include the specific process of obtaining a second target picture without a watermark, where: performing image restoration on the second target area based on a deep learning model to obtain a second target picture without a watermark; wherein the deep learning model includes an original picture identical to the second target picture.
It can be understood that, in the process of image restoration, the first target picture with the masked watermark is input into the pre-trained deep learning model, and the second target picture without the watermark is obtained according to the output result of the pre-trained deep learning model.
Wherein the original picture identical to the second target picture may be the first target picture.
In addition, it should be understood that, in the embodiment of the present application, the deep learning model for performing watermark detection and the deep learning model for performing image restoration may be selected according to actual situations, and are not limited herein. For example, the deep learning model for performing watermark detection and the deep learning model for performing image restoration may be the same deep learning model, that is, the deep learning model may perform both watermark detection and image restoration; alternatively, the first deep learning model may be one model for watermark detection, and the second deep learning model may be another model for image restoration.
According to the image watermark removing method provided by the embodiment of the application, the watermark detected by the target image is firstly covered, and then the covered area is subjected to image restoration based on the deep learning model, so that the problem of removing the watermark can be converted into the problem of image restoration, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are better removed, and the processing capacity of watermarks of different patterns is improved.
The following describes the image watermarking removing method provided by the embodiment of the present application in further detail with reference to an actual application scenario. As shown in fig. 3, the image de-watermarking method provided by the embodiment of the present application may include the following steps:
in step 310, a first target picture with a watermark is obtained.
And 340, performing pure color filling on the first target area to obtain a pure color second target area.
According to the image watermark removing method provided by the embodiment of the application, the watermark detected by the target image is firstly covered, and then the covered area is subjected to image restoration, so that the problem of removing the watermark can be converted into the problem of image restoration, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are better removed, and the processing capacity of watermarks of different patterns is improved.
Fig. 4 is a block diagram of an image watermarking removing apparatus according to an embodiment of the present disclosure. Referring to fig. 4, an image de-watermarking apparatus 400 provided in an embodiment of the present application may include: an acquisition module 410, a determination module 420, a processing module 430, and an image inpainting module 440.
The obtaining module 410 is configured to obtain a first target picture with a watermark;
the determining module 420 is configured to perform watermark detection on the first target picture, and determine a first target area corresponding to the watermark, where the first target area includes the watermark;
the processing module 430 is configured to perform a masking process on the first target area to obtain a second target area;
the image restoration module 440 is configured to perform image restoration on the second target area to obtain a second target picture without a watermark.
The method for removing the watermark of the image, provided by the embodiment of the application, comprises the steps of obtaining a first target picture with the watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark. Therefore, the watermark detected by the target picture is covered firstly, and then the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are removed better, and the processing capacity of watermarks of different patterns is improved.
Optionally, in an embodiment, in the process of determining the first target area corresponding to the watermark, the determining module 420 may be specifically configured to: determining a minimum quadrilateral area corresponding to the watermark; determining the minimum quadrilateral area as the first target area.
Optionally, in an embodiment, in the process of performing the masking processing on the first target region to obtain the second target region, the processing module 430 may specifically be configured to: and filling the first target area with pure color to obtain a second target area with pure color.
Optionally, in one embodiment, the solid color is black.
Optionally, in an embodiment, in the process of determining the minimum quadrilateral area corresponding to the watermark, the determining module 420 may be further specifically configured to: determining a plurality of position coordinates of the watermark in a coordinate system based on the pre-established coordinate system; determining at least four target position coordinates from the plurality of position coordinates, wherein the four target position coordinates comprise at least two position coordinates located on a first straight line and at least two position coordinates located on a second straight line, and the first straight line and the second straight line are not coincident; and determining the minimum quadrilateral area corresponding to the watermark based on the four target position coordinates.
Optionally, in an embodiment, in the process of performing image restoration on the second target area to obtain a second target picture without a watermark, the image restoration module 440 may be specifically configured to: performing image restoration on the second target area based on a deep learning model to obtain a second target picture without a watermark; wherein the deep learning model includes an original picture identical to the second target picture.
It should be noted that the image watermarking apparatus provided in the embodiments of the present application corresponds to the above-mentioned image watermarking method. The related content can refer to the above description of the image watermarking method, and is not described herein again.
In addition, an embodiment of the present application further provides an electronic device 500, where the electronic device 500 includes: a memory 510, a processor 520 and a computer program stored on the memory 510 and executable on the processor 520, which computer program, when executed by the processor 520, implements the steps of the method as described in any of the above. For example, the computer program when executed by the processor 520 implements the following processes: acquiring a first target picture with a watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark. Therefore, the watermark detected by the target picture is covered firstly, and then the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are removed better, and the processing capacity of watermarks of different patterns is improved.
Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, which, when executed by the processor, implements the steps of the method as described in any one of the above. For example, the computer program when executed by the processor implements the process of: acquiring a first target picture with a watermark; performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark; carrying out covering processing on the first target area to obtain a second target area; and performing image restoration on the second target area to obtain a second target picture without the watermark. Therefore, the watermark detected by the target picture is covered firstly, and then the covered area is repaired, so that the problem of removing the watermark can be converted into the problem of repairing the image, the interference of watermark patterns on the watermark removing effect is eliminated, the watermarks of various patterns are removed better, and the processing capacity of watermarks of different patterns is improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that 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 like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of image watermarking, the method comprising:
acquiring a first target picture with a watermark;
performing watermark detection on the first target picture, and determining a first target area corresponding to the watermark, wherein the first target area contains the watermark;
carrying out covering processing on the first target area to obtain a second target area;
and performing image restoration on the second target area to obtain a second target picture without the watermark.
2. The method of image watermarking as defined in claim 1, wherein the determining the first target region corresponding to the watermark includes:
determining a minimum quadrilateral area corresponding to the watermark;
determining the minimum quadrilateral area as the first target area.
3. The method for watermarking an image according to claim 1 or 2, wherein the masking the first target region to obtain a second target region comprises:
and filling the first target area with pure color to obtain a second target area with pure color.
4. The method of image watermarking as defined in claim 3, wherein the solid color is black.
5. The method of image watermarking as defined in claim 2, wherein the determining the smallest quadrilateral area corresponding to the watermark comprises:
determining a plurality of position coordinates of the watermark in a coordinate system based on the pre-established coordinate system;
determining at least four target position coordinates from the plurality of position coordinates, wherein the four target position coordinates comprise at least two position coordinates located on a first straight line and at least two position coordinates located on a second straight line, and the first straight line and the second straight line are not coincident;
and determining the minimum quadrilateral area corresponding to the watermark based on the four target position coordinates.
6. The method of claim 1, wherein the image repairing the second target area to obtain the second target picture without the watermark comprises:
performing image restoration on the second target area based on a deep learning model to obtain a second target picture without a watermark;
wherein the deep learning model includes an original picture identical to the second target picture.
7. An apparatus for watermarking an image, the apparatus comprising:
the acquisition module is used for acquiring a first target picture with a watermark;
a determining module, configured to perform watermark detection on the first target picture, and determine a first target area corresponding to the watermark, where the first target area includes the watermark;
the processing module is used for masking the first target area to obtain a second target area;
and the image restoration module is used for restoring the image of the second target area to obtain a second target picture without the watermark.
8. The apparatus for image watermarking as defined in claim 7, wherein the determining module is further configured to:
determining a minimum quadrilateral area corresponding to the watermark;
determining the minimum quadrilateral area as the first target area.
9. The apparatus for image watermarking as defined in claim 7 or 8, wherein the processing module is further configured to:
and filling the first target area with pure color to obtain a second target area with pure color.
10. An electronic device, characterized in that the electronic device comprises: memory, processor and computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, carries out the steps of the method according to any one of claims 1 to 6.
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