WO2017000716A2

WO2017000716A2 - Image management method and device, and terminal device

Info

Publication number: WO2017000716A2
Application number: PCT/CN2016/083634
Authority: WO
Inventors: 郑成建; 刘宇; 王勃飞; 王宁
Original assignee: 中兴通讯股份有限公司
Priority date: 2015-06-30
Filing date: 2016-05-27
Publication date: 2017-01-05
Also published as: WO2017000716A3; CN106326908A

Abstract

An image management method and device, and a terminal device. The method comprises: classifying images in a terminal device, and obtaining classified images, the classified images including type labels of image categories; obtaining degrees of similarity of images having a same type label, grouping images having a same type label according to the degrees of similarity, and obtaining at least one group of images, the degree of similarity of any two images within each group of images being greater than a preset threshold; within each group of images, selecting a local image to be saved in the terminal device, obtaining a difference image of each remaining image of the group and the local image, storing the difference images in a cloud, and simultaneously deleting the remaining images of the group.

Description

Picture management method, device and terminal device

Technical field

The present application relates to the field of image processing technologies, and relates to a method, an apparatus, and a terminal device for managing a picture, for example.

Background technique

As the performance of terminal devices (such as mobile phones, tablets, etc.) becomes more and more powerful, the functions of photographing are getting better and better, and the photos in the terminal devices are more and more. A large number of similar photos exist in most user terminal devices. Some of these similar photos are deliberately taken by the user to obtain a best effect when taking a picture. Some are generated by using the continuous shooting function, and some are using landscaping software. A copy of the reservation. With the upgrade of the hardware configuration, the pixel resolution is getting higher and higher, and the storage capacity of a single photo is getting larger and larger. Over time, these photos will occupy a large amount of mobile phone memory.

Summary of the invention

The embodiments of the present invention provide a method, a device, and a terminal device for managing a picture, which solve the problem that a similar picture in the terminal device occupies a large amount of valuable memory.

An embodiment of the present invention provides a method for managing a picture, including:

Performing classification processing on the picture in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category;

Obtaining similarity between pictures having the same class label, and grouping the pictures with the same class label according to the similarity to obtain at least one set of pictures, wherein any two pictures in each set of pictures The similarity between the two is greater than a preset threshold;

Selecting a local image to be saved in the terminal device in each group of pictures, and obtaining a difference image between each of the remaining pictures of the group and the local picture, storing the difference image in the cloud, and deleting the group The remaining pictures.

The above method for managing pictures further includes:

The difference image is acquired from the cloud, and the difference image is added to the corresponding local picture to restore the deleted picture.

The classifying the pictures in the terminal device to obtain the classified pictures, including:

Detecting whether the face information is included in the picture of the terminal device;

If the face information is included, the picture is divided into a character type picture, and if the face information is not included, the picture is divided into a landscape picture.

The obtaining the similarity between the pictures with the same class label includes:

Extracting feature information of each picture in the terminal device according to the class label of the picture;

Obtaining similarities between pictures having the same class label according to the feature information.

The extracting the feature information of each image according to the class label of the image, including:

If the class label of the picture indicates that the picture is a character class picture, the feature information of the extracted picture includes a color histogram of the picture and a contour feature of the face area;

If the class label of the picture indicates that the picture is a landscape picture, the feature information of the extracted picture includes a color histogram of the picture.

The obtaining the similarity between the pictures having the same class label according to the feature information, including:

Selecting a first picture that is not grouped in the picture of the terminal device, and acquiring a class label of the first picture;

If the class label indicates that the first picture is a character class picture, selecting a second picture of the character class picture in the picture that is not grouped by the terminal device, and according to the color histogram and the face of the picture Calculating a similarity between the first picture and the second picture by using a contour feature of the area;

If the class label indicates that the first picture is a landscape picture, select a third picture whose class label is a landscape picture in a picture that is not grouped by the terminal device, and calculate a location according to a color histogram of the picture. The similarity between the third picture and the first picture is described.

The calculating the similarity between the first picture and the second picture according to the color histogram of the picture and the contour feature of the face area, including:

Determining whether the number of faces in the first picture and the second picture are the same;

If the same, the similarity between the first picture and the second picture is calculated by the formula S=r1*P+r2*H;

Where S represents the similarity, r1 and r2 are preset coefficients, and r1+r2=1, P represents the matching degree of the contour feature of the face region, and H represents the color histogram similarity.

The step of selecting a local picture that needs to be saved in the terminal device in each group of pictures includes:

Get the image quality of each set of images;

In each set of pictures, one picture with the highest picture quality is selected as the local picture.

The embodiment of the invention further provides a picture management device, including:

a classification module, configured to classify a picture in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category;

a grouping module, configured to acquire a similarity between pictures having the same class label, and perform grouping processing on the pictures with the same class label according to the similarity to obtain at least one group of pictures, where each group of pictures The similarity between the two pictures is greater than a preset threshold;

a processing module, configured to select a local picture that needs to be saved in the terminal device in each group of pictures, and obtain a difference image between each picture of the group and the local picture, and store the difference image in the cloud , while deleting the remaining pictures of the group.

The management device of the above picture further includes:

And a recovery module, configured to acquire the difference image from the cloud, and add the difference image to the corresponding local image to recover the deleted picture.

The classification module includes:

a detecting submodule, configured to detect whether the face information is included in the picture of the terminal device;

And dividing the sub-module, the method is configured to divide the picture into a character-like picture if the detection module detects that the picture of the terminal device includes face information, and otherwise divide the picture into a landscape-like picture.

The grouping module includes:

Extracting a sub-module, configured to extract feature information of each picture in the terminal device according to the class label of the picture;

The obtaining submodule is configured to acquire the similarity between the pictures having the same class label according to the feature information.

The extracting submodule includes:

a first acquiring unit, configured to acquire a color histogram of the picture and a contour feature of the face area if the class label of the picture indicates that the picture is a character class picture;

The second obtaining unit is configured to obtain a color histogram of the picture if the class label of the picture indicates that the picture is a landscape picture.

The obtaining submodule includes:

a third acquiring unit, configured to: select a first picture that is not grouped in the picture of the terminal device, and acquire a class label of the first picture;

a first calculating unit, configured to: if the class label indicates that the first picture is a character class picture, select a second picture of the character class picture in the picture that is not grouped by the terminal device, and according to the picture a color histogram and a contour feature of the face region, and calculating a similarity between the first picture and the second picture;

a second calculating unit, configured to: if the class label indicates that the first picture is a landscape picture, select a third picture whose class label is a landscape picture in a picture that is not grouped by the terminal device, and according to the picture a color histogram, calculating a similarity between the third picture and the first picture.

The first computing unit includes:

a determining subunit, configured to determine whether the number of faces in the first picture and the second picture are the same;

Calculating a subunit, configured to calculate the first picture and the second picture by using a formula S=r1*P+r2*H if the number of faces in the first picture and the second picture are the same Similarity

The processing module includes:

The fourth obtaining submodule is configured to obtain a picture quality of each group of pictures;

The sub-module is selected, and in each set of pictures, one picture with the highest picture quality is selected as the local picture.

The embodiment of the invention further provides a terminal device, which comprises the management device of the picture as described above.

Embodiments of the present invention also provide a non-transitory computer readable storage medium storing computer executable instructions for performing the above method.

The method for managing a picture in the embodiment of the present invention classifies a picture in a terminal device, and divides the pictures belonging to the same category and whose similarity is greater than a preset threshold into a group, and selects a local picture in each group of pictures. Saving in the terminal device, and acquiring a difference image between each picture of the group and the local picture, storing the difference image information in the cloud, and deleting the remaining pictures of the group, thereby greatly saving the terminal The storage space of the device. In addition, in the embodiment of the present invention, when the picture is stored in the cloud, only the difference image is encoded and transmitted, and since the similarity of each group of pictures is large, the code stream after the difference image encoding is relatively small, which is more than the original picture. The bandwidth is saved, and since the difference image is stored in the cloud in the embodiment of the present invention, the content of the original image cannot be seen after the difference image stored in the cloud is decoded, thereby effectively preventing image leakage caused by system loopholes or other reasons. .

DRAWINGS

1 is a first working flowchart of a method for managing a picture according to an embodiment of the present invention;

2 is a second working flowchart of a method for managing a picture according to an embodiment of the present invention;

3 is a block diagram showing the structure of a picture management apparatus according to an embodiment of the present invention;

FIG. 4 is a schematic diagram showing the hardware structure of a terminal device according to an embodiment of the present invention.

Implementation

In order to make the technical problems and technical solutions to be solved by the present application clear, the following description will be made in conjunction with the optional embodiments and the accompanying drawings.

The related picture management method can include three aspects. One is to study the compressed storage of continuous shooting photos, and to use the continuous shooting photos to repeat the characteristics of multiple pixels to reduce the storage space of the photos, but still need to occupy the storage space of the terminal device after compression. There is limited savings on the storage space of the terminal device. The second is to use image processing technology to select and choose. Only one of a group of similar photos is kept, and the rest of similar photos are deleted. The disadvantage is that all photos cannot be retained, and cannot be restored after deletion. Later, I want to review the photos taken in the past. Only see the one that was retained. The third is to use cloud storage to back up all photos directly in the cloud. When the capacity of the photo exceeds the predetermined capacity of the cloud, the user needs to use the cloud for a fee, and there is a risk of photo leakage in the way the photo is stored.

Therefore, the embodiment of the present invention provides a method, a device, and a terminal device for managing a picture, which solves the problem that a similar picture in the terminal device occupies a large amount of valuable memory.

A method for managing a picture in the embodiment of the present invention, as shown in FIG. 1, includes:

Step S11: Perform classification processing on the pictures in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category.

When the pictures in the terminal device are classified, the pictures may be divided into a character class, a landscape class, and the like, and different types of pictures have different class tags.

Step S12: Acquire similarity between pictures having the same class label, and perform grouping processing on the pictures with the same class label according to the similarity to obtain at least one set of pictures, wherein two of each set of pictures The similarity between pictures is greater than a preset threshold.

Step S13: selecting a local picture that needs to be saved in the terminal device in each group of pictures, and acquiring a difference image between each picture of the group and the local picture, and storing the difference image in the cloud, Delete the remaining pictures of the group.

The method for managing pictures in the embodiment of the present invention performs classification processing on pictures in the terminal device, and Dividing a picture belonging to the same category and having a similarity greater than a preset threshold into a group, selecting a local picture in each group of pictures to be saved in the terminal device, and acquiring each remaining picture of the group and the local The difference image of the picture stores the difference image information in the cloud, and deletes the remaining pictures of the group, which greatly saves the storage space of the terminal device. In addition, in the embodiment of the present invention, when the picture is stored in the cloud, only the difference image is encoded and transmitted, and since the similarity of each group of pictures is large, the code stream after the difference image encoding is relatively small, which is more than the original picture. The bandwidth is saved, and since the difference image is stored in the cloud in the embodiment of the present invention, the original image content cannot be seen after the difference image stored in the cloud is decoded, thereby effectively preventing image leakage caused by system loopholes or other reasons.

Optionally, the step S11 includes:

Step S111: detecting whether the face information is included in the picture of the terminal device;

Step S112: If the face information is included, the picture is divided into a character type picture, and if the face information is not included, the picture is divided into a landscape picture.

In the embodiment of the present invention, the picture may be divided into a character class picture and a landscape class picture by performing face detection on each picture. Optionally, the face detection method may adopt a skin color based detection method to display the picture. Converted to the color space YCbCr, where Y represents the luminance component of the picture, Cb represents the blue chrominance component of the picture, and Cr represents the red chrominance component of the picture. The skin area in the picture is detected by the clustering of the skin color projection to the CbCr plane, wherein the Cb value interval is [90, 128], and the Cr value interval is [110, 190], and the skin color interval threshold can be repeated multiple times. The test is adjusted.

The morphological operation is performed on the binarized image obtained by the above detection result, and the interference point is first etched and then the void point is expanded and expanded.

Optionally, the face region on the binarized image after the morphological operation is extracted by the region labeling technique, and the length and width information of the circumscribed rectangle of each region is obtained. According to the biological knowledge, the aspect ratio of the face is relatively fixed, generally between 0.8 and 1.25. Through this feature, the false detection area is eliminated, and the number of faces in the current picture is counted.

Optionally, obtaining the similarity between the pictures having the same class label in the step S12, including:

Step S121: Extract feature information of each picture in the terminal device according to the class label of the picture;

Step S122: Acquire similarities between pictures having the same class label according to the feature information.

The step S121 may include:

If the class label of the picture indicates that the picture is a character class picture, extracting the picture feature information includes a color histogram of the picture and a contour feature of the face area;

If the class label of the picture indicates that the picture is a landscape picture, extracting features of the picture The information includes the color histogram of the picture.

In the embodiment of the present invention, extracting the contour feature of the face region in the image may include: uniformly scaling the face region to L*L pixels, where L is a preset value, where L represents the size of the face region, in different images. The size of the face area may be inconsistent. In this embodiment, the face area in different pictures is uniformly scaled to a pixel size of L*L. Edge detection is performed on the scaled face region image by using the sobel operator, and the binarization threshold of the detection result image is obtained by using the "big law method", and the detection result image is binarized, and the result of the binarization is used as the result. The contour feature matrix of the face area is saved. Optionally, the preset value L is 80, and the determination of the value of L can be obtained through multiple tests.

In an embodiment of the invention, the similarity of the color histograms between the two pictures may be determined using a Pap singer distance.

The step S122 may include:

Optionally, calculating the similarity between the first picture and the second picture according to the color histogram of the picture and the contour feature of the face area, including:

Where S represents the similarity, r1 and r2 are preset coefficients, and r1+r2=1, P represents the matching degree of the contour feature of the face region, and H represents the color histogram similarity. Optionally, the preset coefficients r1 and r2 are 0.4 and 0.6, and the determination of the values of the preset coefficients r1 and r2 can be obtained through multiple tests.

In the embodiment of the present invention, calculating the matching degree P of the contour feature of the face region includes: performing an exclusive OR operation on the contour feature matrix of the face region of the picture A and the picture B, and counting the number of the M in the statistical operation result M, M The smaller the value, the more similar the picture A and the picture B are; the normalized value of M can be used to obtain the matching degree P of the contour feature of the face region, P=M/(L*L).

Optionally, calculating the similarity between the third picture and the first picture according to the color histogram of the picture may include:

Using the similarity of the color histogram of the third picture and the first picture as the similarity of the third picture and the first picture.

After obtaining the similarity S between the pictures having the same class label according to the foregoing method, it is determined whether the similarity between the two pictures having the same class label is greater than a preset threshold T1, and is greater than the preset threshold, and is divided into the same The group picture, wherein the preset threshold T1 can be selected as 0.8, and the determination of the value of the preset threshold T1 can be obtained through multiple tests. Meanwhile, in the embodiment of the present invention, each group of pictures is given a group label, and the setting of the group label may include the picture category of the current group, the number of similar pictures in the group, and a unique serial number, for example, “person_6_20150326H000123” The group is a character-like picture, and there are 6 similar pictures in the group, and the last string is the unique serial number of the group of pictures. Optionally, the serial number can cover information such as picture capturing time and shooting position.

Optionally, the selecting, in the step S13, the local pictures that need to be saved in the terminal device in each group of pictures includes:

Get the image quality of each set of images;

Of course, in the embodiment of the present invention, any one or more pictures may be selected as a local picture in each group according to user requirements, and stored in the terminal device.

The step of obtaining the picture quality of each picture in each group of pictures may specifically include:

Step S131: calculating a grayscale image of the current picture;

Step S132: calculating the information entropy F of the grayscale image obtained in step S131;

Step S133: calculating a color coefficient of the current picture Color;

Step S134: If the current picture is a character class picture, calculate a contrast Contrast of the gray image corresponding to the face area;

Step S135: Calculate the picture quality according to the class label of the current picture and the information entropy F, the color coefficient Color, and/or the contrast Contrast.

In step S132, the information entropy of the image

Where: K is the gray value, p _K is the probability that the gray value K appears in the gray image, and N is the gray level of the image.

In step S133, the color coefficient of the image

In the formula:

Where σ represents the standard deviation of the image color coefficient, μ represents the mean value of the image color coefficient, and rg and yb are a simple corresponding color space of the image RGB color space: rg=RG, yb=0.5*(R+G)-B, Where R represents the red component value in the RGB color space; G represents the green component value in the RGB color space; B represents the blue component value in the RGB color space.

In step S134, the contrast contrast of the face region can adopt the variance contrast

Where: L represents the size of the face area, and I represents the brightness of the face at the current position.

It is the average brightness of the entire face area.

After obtaining the picture quality of each group of pictures, the pictures in each group are sorted by quality from high to low, and the highest quality picture in each group is marked, and an ID is assigned.

Optionally, the step of sorting the pictures in each group according to the quality from high to low may include: first ordering the information entropy F of the images in descending order; and then assigning different points to the sorted images. The value, for example, the maximum image entropy F is 100, and the remaining images are proportional [0, 100]. Perform the same operation on the color coefficient Color, sort first, and then assign a score. If the current picture is a landscape picture, the picture quality coefficient of the landscape picture is Q=F _d +Color _d , where F _d and Color _d respectively represent the score corresponding to the information entropy F and the color coefficient Color; if the current picture is The character class picture continues to sort the contrast Contrast of the face region, and the mapping takes the value [0, 100]. At this time, the coefficient of the picture quality of the character class picture is Q=F _d +Color _d +Contrast _d , Contrast _d indicates The score of the Contrast corresponding to the contrast of the face area. According to the calculated picture quality coefficient of the current picture, the picture quality of the current picture may be obtained, where the coefficient Q of the picture quality is larger, indicating that the quality of the current picture is better.

Optionally, the method for managing a picture in the embodiment of the present invention further includes:

The image management method of the embodiment of the present invention stores the difference image of the image in the cloud, and the user does not need to delete the image to save the storage space of the terminal device, and all the images can be backtracked and browsed at any time; and the difference image of the image is stored to In the cloud, only the difference image is encoded and transmitted, and since the similarity of each group of pictures is large, the code stream after the difference image encoding is relatively small, which saves bandwidth more than the original picture. In addition, the original image (stored in the terminal device) and the difference image (stored in the cloud) are stored separately, and only a high protection measure is taken on the original image, and the image content cannot be seen after decoding the difference image stored in the cloud. To effectively prevent image leaks caused by system vulnerabilities or other reasons.

The above explains the steps of the picture management method separately, and the overall flow of the picture management method is explained below.

As shown in Figure 2, it includes:

Step S21: Perform classification processing on the pictures in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category.

Optionally, the picture can be divided into a character class picture and a landscape class picture.

Step S22: Extract feature information of the picture according to the category of the picture.

Step S23: Acquire similarities between pictures having the same label according to the feature information of the picture.

Step S24: Perform grouping processing on the pictures with the same class label according to the similarity, and the similarity between any two pictures in each group of pictures is greater than a preset threshold.

Step S25: Calculate the quality of each group of pictures, and mark the picture with the highest quality, and obtain the difference image of the picture and the remaining pictures of the group.

Step S26: Encoding the difference image and transmitting the code of the difference image to the cloud.

Step S27: Only the highest quality picture is saved in the terminal device, and the remaining pictures of the group are deleted.

Step S28: When it is necessary to view the picture other than the highest quality picture, the corresponding difference image code stream is obtained from the cloud, decoded and added to the picture with the highest quality of the group to restore the deleted picture.

Optionally, the group label of the group in which the local picture currently marked in the terminal device is located is first obtained, where the group label includes a picture category, a number of similar pictures in the group, and a unique serial number, and the parsing group label obtains a similar picture of the current group. And then obtaining all the difference image code streams corresponding to the group of pictures from the cloud according to the unique serial number of the group label; finally, decoding the code stream of the difference image at the terminal device, and adding the decoding result to the current local picture Corresponding deleted picture original picture, if the current local picture cannot be found in the terminal device, only the difference image is returned and an error is indicated.

The image management method provided by the embodiment of the present invention applies image analysis technology to first classify pictures in the terminal device, and then extracts features of the classified pictures, and calculates similar features between the features based on the similarity measurement functions defined by the features. Similarity, mark similar pictures as a group; then select the best picture in each group by designing digital picture quality evaluation scheme; finally, by encoding the difference image, save to cloud storage, delete the similarity of terminal equipment image. When the user needs to browse the picture, only the corresponding reverse process can be used to browse all the pictures. The embodiment of the invention adopts the image analysis technology and combines it with the cloud storage to solve the problem that the terminal device has many similar pictures, the arrangement is troublesome, and the storage space of the terminal device is occupied, and all the pictures can be backtracked and browsed at any time without Select pictures and save memory to select between them, and use the method of storing difference images to improve the density of images and protect user privacy.

The embodiment of the invention further provides a picture management device, as shown in FIG. 3, comprising:

The classification module 31 is configured to classify the pictures in the terminal device to obtain a classified picture. a slice, the classified picture includes a class label indicating the picture category;

The grouping module 32 is configured to acquire the similarity between the pictures having the same class label, and perform grouping processing on the pictures with the same class label according to the similarity to obtain at least one set of pictures, where each group of pictures The similarity between any two pictures is greater than a preset threshold;

The processing module 33 is configured to select a local picture that needs to be saved in the terminal device in each group of pictures, and obtain a difference image between each picture of the group and the local picture, and store the difference image to In the cloud, delete the remaining pictures of the group.

The image management device of the embodiment of the present invention further includes:

In the image management apparatus of the embodiment of the present invention, the classification module 31 includes:

a dividing sub-module, configured to: if the detecting module detects that the picture of the terminal device includes face information, divide the picture into a character-like picture, and if the face information is not included, divide the picture into a landscape Class picture.

In the image management apparatus of the embodiment of the present invention, the grouping module 32 includes:

In the image management apparatus of the embodiment of the present invention, the extracting submodule includes:

In the image management apparatus of the embodiment of the present invention, the acquiring submodule includes:

a first calculating unit, configured to: if the class label indicates that the first picture is a character class picture, select a second picture of the character class picture in the picture that is not grouped by the terminal device, and according to the picture a color histogram and a contour feature of the face region, calculating the first picture and the second Similarity of the picture;

In the image management apparatus of the embodiment of the present invention, the first calculating unit includes:

In the image management apparatus of the embodiment of the present invention, the processing module 33 includes:

It should be noted that the device and the terminal are devices and terminals corresponding to the foregoing method embodiments. All the implementation manners in the foregoing method embodiments are applicable to the device and the terminal embodiment, and the same technical effects can be achieved.

FIG. 4 is a schematic diagram showing the hardware structure of a terminal device according to an embodiment of the present invention. As shown in FIG. 4, the device includes:

One or more processors 41, one processor 41 is taken as an example in FIG. 4;

Memory 42;

The apparatus may also include an input device 43 and an output device 44.

The processor 41, the memory 42, the input device 43, and the output device 44 in the device may be connected by a bus or other means, as exemplified by a bus connection in FIG.

The memory 42 is a non-volatile computer readable storage medium, and can be used for storing a software program, a computer executable program, and a module, such as a program instruction/module corresponding to the method for determining a phase difference in the embodiment of the present invention (for example, attached) The classification module 31, the grouping module 32, and the processing module 33) shown in FIG. The processor 41 executes various functional applications and data processing of the server by running software programs, instructions, and modules stored in the memory 42, that is, the management of the picture of the above method embodiment is implemented. law.

The memory 42 may include a storage program area and an storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to usage of the terminal device, and the like. Moreover, memory 42 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 42 may optionally include memory remotely located relative to processor 41, which may be connected to the terminal device over a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

Input device 43 can be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the terminal. Output device 44 may include a display device such as a display screen.

The one or more modules are stored in the memory 42 and, when executed by the one or more processors 41, perform management methods of the above-described embodiments and pictures in an optional real-time manner.

Embodiments of the present invention also provide a non-transitory computer readable storage medium storing computer-executable instructions executable in any of the above embodiments. The management method of the picture.

The method, device and terminal device for managing the picture in the embodiment of the invention solve the problem that a similar picture in the terminal device occupies a large amount of valuable memory, and can improve the density of the picture, protect the user privacy, and improve the user experience.

Industrial applicability

The method for managing the picture in the embodiment of the present invention solves the problem that the similar picture in the terminal device occupies a large amount of valuable memory, and the embodiment of the present invention only stores the difference image in the cloud, and the difference image stored in the cloud cannot be decoded. See the original image content to effectively prevent image leaks caused by system vulnerabilities or other reasons

Claims

A method of managing pictures, including:

Performing classification processing on the picture in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category;

Obtaining similarity between pictures having the same class label, and grouping the pictures with the same class label according to the similarity to obtain at least one set of pictures, wherein any two pictures in each set of pictures The similarity between the two is greater than the preset threshold;

Selecting a local image to be saved in the terminal device in each group of pictures, and obtaining a difference image between each of the remaining pictures of the group and the local picture, storing the difference image in the cloud, and deleting the image The remaining pictures of the group.
The method for managing a picture according to claim 1, further comprising:

The difference image is acquired from the cloud, and the difference image is added to the corresponding local picture to restore the deleted picture.
The method for managing a picture according to claim 1, wherein the classifying the picture in the terminal device to obtain the classified picture comprises:

Detecting whether the face information is included in the picture of the terminal device;

If the face information is included, the picture is divided into a character type picture, and if the face information is not included, the picture is divided into a landscape picture.
The method for managing a picture according to claim 1 or 3, wherein the obtaining the similarity between the pictures having the same class label comprises:

Extracting feature information of each picture in the terminal device according to the class label of the picture;

Obtaining similarities between pictures having the same class label according to the feature information.
The method for managing a picture according to claim 4, wherein the extracting the feature information of each picture according to the class label of the picture comprises:

If the class tag of the picture indicates that the picture is a character class picture, extracting the picture feature information includes a color histogram of the picture and a contour feature of the face area;

If the class label of the picture indicates that the picture is a landscape picture, extracting the picture feature information includes a color histogram of the picture.
The method for managing a picture according to claim 4, wherein the obtaining the similarity between the pictures having the same class label according to the feature information comprises:

Selecting a first picture that is not grouped in the picture of the terminal device, and acquiring a class label of the first picture;

If the class label indicates that the first picture is a character class picture, selecting a second picture of the character class picture in the picture that is not grouped by the terminal device, and according to the color histogram and the face of the picture a contour feature of the region, calculating a similarity between the first picture and the second picture;

If the class label indicates that the first picture is a landscape picture, select a third picture whose class label is a landscape picture in a picture that is not grouped by the terminal device, and calculate a location according to a color histogram of the picture. The similarity between the third picture and the first picture is described.
The method for managing a picture according to claim 6, wherein the calculating the similarity between the first picture and the second picture according to the color histogram of the picture and the contour feature of the face area comprises:

Determining whether the number of faces in the first picture and the second picture are the same;

If the same, the similarity between the first picture and the second picture is calculated by the formula S=r1*P+r2*H;

Where S represents the similarity, r1 and r2 are preset coefficients, and r1+r2=1, P represents the matching degree of the contour feature of the face region, and H represents the color histogram similarity.
The method for managing a picture according to claim 1, wherein the selecting a local picture to be saved in the terminal device in each group of pictures comprises:

Get the image quality of each set of images; and

In each set of pictures, one picture with the highest picture quality is selected as the local picture.
A picture management device comprising:

a classification module, configured to classify a picture in the terminal device to obtain a classified picture, where the classified picture includes a class label indicating the picture category;

a grouping module, configured to acquire a similarity between pictures having the same class label, and perform grouping processing on the pictures with the same class label according to the similarity to obtain at least one group of pictures, where each group of pictures The similarity between the two images is greater than a preset threshold;

a processing module, configured to select a local picture that needs to be saved in the terminal device in each group of pictures, and obtain a difference image between each picture of the group and the local picture, and store the difference image in the cloud , while deleting the remaining pictures of the group.
The picture management device according to claim 9, further comprising:

And a recovery module, configured to acquire the difference image from the cloud, and add the difference image to the corresponding local image to recover the deleted picture.
The picture management device according to claim 9, wherein the classification module comprises:

a detecting submodule configured to detect whether the face information of the terminal device includes a face information;

a dividing sub-module, configured to: if the detecting module detects that the picture of the terminal device includes face information, divide the picture into a character-like picture, and if the face information is not included, divide the picture into a landscape Class picture.
The method of managing a picture according to claim 11, wherein the grouping module comprises:

Extracting a sub-module, configured to extract feature information of each picture in the terminal device according to the class label of the picture;

The obtaining submodule is configured to acquire the similarity between the pictures having the same class label according to the feature information.
The picture management device according to claim 12, wherein the extraction submodule comprises:

a first acquiring unit, configured to acquire a color histogram of the picture and a contour feature of the face area if the class label of the picture indicates that the picture is a character class picture;

The second obtaining unit is configured to obtain a color histogram of the picture if the class label of the picture indicates that the picture is a landscape picture.
The picture management apparatus according to claim 12, wherein the obtaining submodule comprises:

a third acquiring unit, configured to: select a first picture that is not grouped in the picture of the terminal device, and acquire a class label of the first picture;

a first calculating unit, configured to: if the class label indicates that the first picture is a character class picture, select a second picture of the character class picture in the picture that is not grouped by the terminal device, and according to the picture a color histogram and a contour feature of the face region, and calculating a similarity between the first picture and the second picture;

a second calculating unit, configured to: if the class label indicates that the first picture is a landscape picture, select a third picture whose class label is a landscape picture in a picture that is not grouped by the terminal device, and according to the picture a color histogram, calculating a similarity between the third picture and the first picture.
The picture management device according to claim 14, wherein the first calculation unit comprises:

a determining subunit, configured to determine whether the number of faces in the first picture and the second picture are the same;

Calculating a subunit, configured to calculate the first picture and the second picture by using a formula S=r1*P+r2*H if the number of faces in the first picture and the second picture are the same Similarity

Where S represents the similarity, r1 and r2 are preset coefficients, and r1+r2=1, P represents the face region The degree of matching of the contour features, H represents the color histogram similarity.
The picture management device according to claim 9, wherein the processing module comprises:

a fourth obtaining submodule, configured to obtain a picture quality of each group of pictures;

The sub-module is selected, and in each set of pictures, one picture with the highest picture quality is selected as the local picture.
A terminal device comprising the picture management device according to any one of claims 9-16.
A non-transitory computer readable storage medium storing computer executable instructions for performing the method of managing a picture according to any of claims 1-12.