CN110825897A - Image screening method and device and mobile terminal - Google Patents

Image screening method and device and mobile terminal Download PDF

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Publication number
CN110825897A
CN110825897A CN201911042623.4A CN201911042623A CN110825897A CN 110825897 A CN110825897 A CN 110825897A CN 201911042623 A CN201911042623 A CN 201911042623A CN 110825897 A CN110825897 A CN 110825897A
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image
scoring
feature
grading
screened
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Chinese (zh)
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周明
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Vivo Mobile Communication Co Ltd
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Vivo Mobile Communication Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/53—Querying
    • G06F16/535—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection

Abstract

The invention provides an image screening method, an image screening device and a mobile terminal. The method comprises the following steps: acquiring an image set to be screened, which is obtained by continuously shooting a shooting object; acquiring scoring characteristics corresponding to the image set to be screened; extracting image features corresponding to the grading features from each image of the image set to be screened; scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image; and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values. The invention can improve the accuracy of image screening.

Description

Image screening method and device and mobile terminal
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to an image screening method, an image screening device, and a mobile terminal.
Background
With the rapid development of mobile communication technology, mobile terminals (such as mobile phones) have become an indispensable part of people's life and work. With the continuous development of mobile terminal configuration, the photographing function of the mobile terminal is more and more powerful.
When a user uses the mobile terminal to shoot a large number of pictures, a picture set for recalling videos needs to be created, and usually, several pictures with higher definition are selected according to the definition of the pictures to serve as the picture set for creating the recalling videos.
However, for different people, the subjective evaluation of the same image is different under different requirements, for example, in a dimly lit space, multiple images are taken at the same angle and posture, and the taken images need to be blurred and not clear, but the previous image screening method only retains one clearest image, and the existing criterion of only using sharpness as picture screening is an objective criterion, which may cause the picture screening result to be inaccurate.
Disclosure of Invention
The embodiment of the invention provides an image screening method, an image screening device and a mobile terminal, and aims to solve the problem that in the prior art, the image screening standard is an objective standard, and the image screening result is possibly inaccurate.
In order to solve the above technical problem, the embodiment of the present invention is implemented as follows: :
in a first aspect, an embodiment of the present invention provides an image screening method, including: acquiring an image set to be screened, which is obtained by continuously shooting a shooting object; acquiring configured grading characteristics based on the image set to be screened; extracting image features corresponding to the grading features from each image of the image set to be screened; scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image; and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In a second aspect, an embodiment of the present invention provides an image screening apparatus, including: the image set acquisition module is used for acquiring an image set to be screened, which is obtained by continuously shooting a shooting object; the grading feature acquisition module is used for acquiring configured grading features based on the image set to be screened; the image feature extraction module is used for extracting image features corresponding to the grading features from each image of the image set to be screened; the scoring value acquisition module is used for scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image; and the target image screening module is used for screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In a third aspect, an embodiment of the present invention provides a mobile terminal, including a processor, a memory, and a computer program stored on the memory and operable on the processor, where the computer program, when executed by the processor, implements the steps of the image screening method described in any one of the foregoing.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the image screening method described in any one of the above.
In the embodiment of the invention, the grading characteristics corresponding to the image set to be screened are obtained by obtaining the image set to be screened, which is obtained by continuously shooting the shooting object, the image characteristics corresponding to the grading characteristics are extracted from each image of the image set to be screened, each image is graded according to the grading characteristics and the image characteristics corresponding to each image to obtain the grading value of each image, and the target image with the grading value larger than or equal to the grading threshold value is screened from the image set to be screened according to each grading value. According to the embodiment of the invention, each image is scored by combining the scoring characteristics, rather than simply screening out the image with higher definition, so that the accuracy of image screening can be improved.
Drawings
FIG. 1 is a flowchart illustrating steps of an image screening method according to an embodiment of the present invention;
FIG. 1a is a schematic diagram of an embodiment of the present invention for obtaining a set of images to be filtered;
FIG. 1b is a schematic diagram of the same type of image cleaning function provided by the embodiment of the present invention;
FIG. 1c is a diagram illustrating a customized screening criteria provided by an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of an image screening method according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating steps of an image filtering method according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps of an image screening method according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an image screening apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an image screening apparatus according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an image screening apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an image screening apparatus according to an embodiment of the present invention;
fig. 9 is a block diagram of an image screening apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present 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.
Example one
Referring to fig. 1, a flowchart illustrating steps of an image screening method according to an embodiment of the present invention is shown, which may specifically include the following steps:
step 101: and acquiring an image set to be screened, which is obtained by continuously shooting the shooting object.
The embodiment of the invention can be applied to a scheme that the terminal side screens the images of the same type and reserves the images desired by the user.
The terminal may be a mobile terminal, such as a mobile electronic device like a mobile phone or a tablet computer, or may be a PC (personal computer) terminal, such as a desktop computer or a notebook computer.
The shooting object refers to a corresponding object when an image set to be screened is acquired, the object to be screened can be a person, a pot plant, a landscape and the like, and specifically, the shooting object can be determined according to actual conditions.
The image set to be screened refers to an image set formed by a plurality of images obtained by continuously shooting a shooting object, and the image set to be screened may include 3 images, 5 images, 8 images, or the like, specifically, the image set to be screened may be determined according to an actual situation, for example, referring to fig. 1a, a schematic diagram for obtaining the image set to be screened according to an embodiment of the present invention is shown, as shown in fig. 1a, the shooting object is a potted plant, and the collected shooting object may collect images corresponding to the shooting object respectively at different times and according to different brightnesses and according to different degrees of definition, so as to obtain a plurality of images corresponding to the shooting object, where the plurality of images form the image set to be screened.
The image set to be filtered may also be an image set composed of a plurality of images obtained by performing continuous shooting with a continuous shooting function built in the starting terminal, and specifically, may be determined according to business requirements, and the embodiment of the present invention is not particularly limited thereto.
In the invention, an image set to be screened which needs to be cleaned can be obtained in advance, then the images in the image set to be screened are cleaned, or after a user triggers the function of cleaning the images of the same type, the user selects one image, and then the terminal obtains the images which are the same type as the selected image from the images stored in the album according to the images selected by the user, namely the image set to be screened is formed.
After acquiring the image set to be filtered obtained by continuously shooting the shooting object, step 102 is executed.
Step 102: and acquiring the grading characteristics corresponding to the image set to be screened.
The scoring features refer to image features that are acquired in advance for scoring with each image in the image set to be screened.
The scoring features may be image features extracted from some pre-stored pictures that are most hot in the shooting scene corresponding to the image set to be filtered in the latest period of time, such as features of person posture, background, blurring degree, person angle, and the like.
The scoring features may also be image features customized by the user for each image in the set of images to be filtered, for example, the user customizes the features of the set of images to be filtered according to features that the user wants, such as blur, highlight, and the like.
Of course, the scoring features may also be other forms of image features corresponding to the image set to be filtered, such as features of partial regions of images, and the like. The scoring characteristics will be described in detail in the following embodiments of the method, which are not repeated herein.
For example, referring to fig. 1b, a schematic diagram of a same-type image cleaning function provided in an embodiment of the present invention is shown, and as shown in fig. 1b, after a user opens a terminal album, a button for "same-type image cleaning" is displayed in the interface, and the user may click the button to trigger a cleaning operation on the same-type images stored in the album.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
After the image set to be filtered is obtained, the scoring feature corresponding to the image set to be filtered may be obtained, and how to obtain the scoring feature will be described in detail in the following method embodiments, which are not described herein again.
After the scoring features corresponding to the set of images to be filtered are obtained, step 103 is performed.
Step 103: and extracting image features corresponding to the grading features from each image of the image set to be screened.
The image features refer to features of images extracted from each image of the image set to be screened according to score features which are acquired in advance and correspond to the image set to be screened, for example, when the score features are human gestures, features of task gestures can be extracted from each image of the image set to be screened; (ii) a And when the grading feature is a highlight feature, the highlight image feature can be extracted from each image of the image set to be screened.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
The specific implementation process of extracting the image features corresponding to the score features from each image of the image set to be screened will be described in detail in the following method embodiments, which are not described herein again.
After the image features corresponding to the scored features are extracted from each image of the image set to be filtered, step 104 is performed.
Step 104: and scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image.
After obtaining the image features of each image, scoring the image features corresponding to each image according to the scoring features to obtain a score value corresponding to each image, for example, the scoring features include a and B, the image feature corresponding to the scoring feature a is a feature a of the image 1, and the image feature corresponding to the scoring feature B is a feature B of the image 1, when the image 1 is scored, scoring the feature a according to the scoring feature a and scoring the feature B according to the scoring feature B, and then according to the weights corresponding to the two features, finally obtaining a total score of the image 1, that is, the score value of the image 1.
It should be understood that the above example is only one scheme of how to obtain the score value for better understanding of the technical scheme of the embodiment of the present invention, and in practical applications, a person skilled in the art may also obtain the score value of the image in other ways, which is not limited by the embodiment of the present invention.
After scoring each image according to the scoring features and the image features corresponding to each image to obtain a scoring value of each image, step 105 is performed.
Step 105: and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
The score threshold refers to a score preset by a service person for saving an image, and may be 0.5, 0.6, 0.8, and the like, specifically, the score threshold may be determined according to a service requirement, and the embodiment of the present invention is not limited thereto.
The target image is an image with a score value larger than or equal to a score threshold value in the image set to be screened.
After the score value of each image in the image set to be screened is obtained, the score value of each image in the image set to be screened may be compared with a score threshold, so that a target image with a score value greater than the score threshold may be screened from the image set to be screened, for example, if the image set a to be screened includes an image 1, an image 2, an image 3, and an image 4, the score threshold is 0.5, the score value of the image 1 is 0.4, the score value of the image 2 is 0.8, the score value of the image 3 is 0.9, and the score value of the image 4 is 0.5, the target image in a is the image 2 and the image 3.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
After the target image is screened from the set of images to be screened, the target image may also be saved and other images may be removed, as described in detail below with reference to the preferred embodiments.
In a preferred embodiment of the present invention, after the step 105, the method may further include:
step S: and saving the target image, and deleting other images except the target image in the image set to be screened.
In the embodiment of the invention, after the target image with the score value larger than or equal to the score threshold value is screened out from the image set to be screened, the target image can be saved in a system photo album, and other images except the target image in the image set to be screened are removed from the photo album, for example, the image set to be screened contains an image a, an image b, an image c, an image d and an image e, wherein the image a and the image c are target images, and after the score is carried out, the image a and the image c can be saved in the photo album, and the image b, the image d and the image e can be removed from the photo album.
According to the embodiment of the invention, the user can score similar photos according to the user-defined requirement or cloud big data, screen the photos according to the scores, reserve the most wanted photos, delete other redundant photos, and save the occupation of the memory space of the system.
According to the image screening method provided by the embodiment of the invention, the grading characteristics corresponding to the image set to be screened are obtained by obtaining the image set to be screened, which is obtained by continuously shooting the shooting object, the image characteristics corresponding to the grading characteristics are extracted from each image of the image set to be screened, each image is graded according to the grading characteristics and the image characteristics corresponding to each image, the grading value of each image is obtained, and the target image with the grading value larger than or equal to the grading threshold value is screened from the image set to be screened according to each grading value. According to the embodiment of the invention, each image is scored by combining the scoring characteristics, rather than simply screening out the image with higher definition, so that the accuracy of image screening can be improved.
Example two
Referring to fig. 2, a flowchart illustrating steps of an image screening method according to an embodiment of the present invention is shown, which may specifically include the following steps:
step 201: and acquiring an image set to be screened, which is obtained by continuously shooting the shooting object.
In this embodiment of the present invention, a specific implementation manner of step 201 is similar to that of step 101 in the first embodiment, and the specific implementation process may refer to the description of step 101 above, which is not described herein again in this embodiment of the present invention.
Step 202: and determining a shooting scene corresponding to the shooting object according to the image set to be screened.
The shooting scene refers to a scene in which an image set to be screened is obtained when a shooting object is shot, and the shooting scene may include indoor, outdoor, night, day and the like, and specifically may be determined according to actual conditions.
When the image set to be screened is obtained, the shooting scene of the shooting object during shooting can be determined according to a plurality of images in the image set to be screened, for example, as shown in fig. 1a, it can be known that the shooting scene corresponding to the shooting object (i.e., potted plant) is an indoor scene according to three images in the image set to be screened.
After the shooting scene corresponding to the shooting object is determined, step 203 is executed.
Step 203: and acquiring a matching image of which the heat value is greater than the heat threshold value and which is matched with the shooting scene from a pre-stored image library.
The image library is a database that is provided in advance to store images, and stores a plurality of images of different subjects in a plurality of scenes.
It can be understood that the image library may be a database preset at the terminal side, or may be a database set at the cloud side, and specifically, may be determined according to business requirements.
The heat value refers to a numerical value corresponding to the heat attribute of the image, and the heat value can be used for representing the heat attribute of the image in the latest period of time, namely the degree of the image being favored by the user.
The heat threshold is a threshold preset by a service person and corresponding to a heat value of an image, and when the heat value of the image is greater than the heat threshold, the image is highly popular with a user at the current stage, otherwise, the image is less popular with the user at the current stage.
The matching image is an image which is obtained from an image library, has a heat value larger than a heat threshold value and is matched with the shooting scene.
After the shooting scene corresponding to the shooting object is obtained, a plurality of matched images can be obtained from the image library according to the shooting scene, and then the matched images with the heat values larger than the heat threshold value are screened out according to the heat values corresponding to the images.
After acquiring a matching image with a heat value greater than the heat threshold and matching with the shooting scene from the pre-stored image library, step 204 is executed.
Step 204: extracting a first scoring feature in the matching image.
The first scoring feature refers to a feature for scoring each image in the image set to be filtered, and the first scoring feature may be a feature such as a person's posture, a background, a blurring degree, a person's angle, and the like.
After the matching images corresponding to the image set to be filtered are obtained, the first scoring feature may be extracted from the matching images, for example, as shown in fig. 1a, when a scene of a shooting object is an indoor scene, a plurality of matching images with a heat value greater than a heat threshold value in the indoor scene may be acquired from an image library, and then corresponding image features are extracted from the matching images to serve as the first scoring feature.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
After extracting the first scored feature in the matching image, step 205 is performed.
Step 205: and extracting a first image feature corresponding to the first grading feature from each image.
The first image feature refers to an image feature extracted from each image of the image set to be screened and corresponding to the first score feature, for example, when the first score feature corresponding to the image set to be screened is a human body posture, the first image feature including the human body posture can be extracted from each image of the image set to be screened; when the first scoring feature corresponding to the image set to be filtered is the background, the background feature of each image can be extracted from each image to be used as the first image feature.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
After the first scoring feature corresponding to the image set to be filtered is extracted from the matching images, the first image feature corresponding to the first scoring feature may be extracted from each image of the image set to be filtered, and then step 206 is performed.
Step 206: and comparing the first image characteristic corresponding to each image with the first grading characteristic to obtain a comparison result.
After the first image feature and the first scoring feature are obtained, for each image in the images to be screened, the first image feature and the first scoring feature of each image may be compared, so as to obtain a comparison result, for example, if the first image feature of the image a is a and b, and the corresponding first scoring features are feature 1 and feature 2, respectively, then a and feature 1 may be compared, and b and feature 2 may be compared, so as to obtain two results, which are the comparison result of the image a.
After the comparison result is obtained, step 207 is executed.
Step 207: and determining the scoring value of each image according to the comparison result.
After the comparison result is obtained, the score value of each image can be determined according to the comparison result of the first image characteristic and the first scoring characteristic, and it can be understood that the technology for obtaining the score value by comparing the characteristics is a mature technology in the field, and the detailed description of how to determine the score value of the image according to the comparison result is omitted.
Of course, when the first scoring features are plural, the first image features are also plural, and when the scoring value is obtained, the final scoring value may be calculated according to the weight corresponding to each first image feature, for example, the first scoring features are a and b, the corresponding first image features are feature 1 and feature 2, respectively, the weight of feature 1 is 0.3, the weight of feature 2 is 0.5, the scoring value obtained by comparing a with feature 1 is 0.5, and the scoring value obtained by comparing b with feature 2 is 0.8, and then the final scoring value is 0.5 + 0.3+ 0.5-0.8-0.55.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
In a specific implementation, when there are a plurality of first image features and first scoring features and the scoring value of an image is calculated, the calculation may be performed by referring to other manners, which is not limited in this embodiment of the present invention.
After determining the score value of each image according to the comparison result, step 208 is performed.
Step 208: and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In the present invention, the specific implementation of step 208 is similar to the implementation of step 105 in the first embodiment, and the specific implementation process may refer to the description of step 105 above, which is not repeated herein in the embodiments of the present invention.
According to the embodiment of the invention, the photos are screened based on big data, and the images with higher heat represent the aesthetic viewpoints of people at present, so that the accuracy of image scoring can be improved.
The image screening method provided by the embodiment of the invention has the beneficial effects of the image screening method provided by the first embodiment, and can be used for scoring each image by combining the scoring characteristics of the images with higher pre-stored heat values, so that the real-time performance and the accuracy of image scoring can be improved.
EXAMPLE III
Referring to fig. 3, a flowchart illustrating steps of an image screening method according to an embodiment of the present invention is shown, which may specifically include the following steps:
step 301: and acquiring an image set to be screened, which is obtained by continuously shooting the shooting object.
In this embodiment of the present invention, the specific implementation manner of step 301 is similar to that of step 101 in the first embodiment, and the specific implementation process may refer to the description of step 101 above, which is not described herein again in this embodiment of the present invention.
Step 302: and acquiring a second grading feature set by the user for the image set to be screened and a first grading weight corresponding to the second grading feature.
The second scoring feature refers to a feature which is set by a user for the image set to be screened in a self-defined manner and is used for scoring the image, and the second scoring feature may be a highlight feature, a blur feature, or the like set by the user, and specifically, may be determined according to actual conditions.
The first scoring weight refers to a weight set by the user corresponding to the second scoring feature.
The function of the user-defined feature is preset in the system, when the user executes the function, a required second scoring feature and a first scoring weight corresponding to the second scoring feature may be set, for example, referring to fig. 1c, a schematic diagram of a user-defined screening condition provided by the embodiment of the present invention is shown, as shown in fig. 1c, when the user opens the album, a button of a "screening condition" is displayed in the interface, after the user acquires the image set to be screened, the user may click the button of the "screening condition" to trigger the function of the user-defined screening condition, and then, the user may set a screening condition (i.e., the second scoring feature) for the image set to be screened, such as features of automation, highlight, darkness, fuzziness, and the like.
Of course, after the second scoring characteristics are set, the user may also set corresponding first scoring weights for the second scoring characteristics.
After the second scoring feature set by the user for the image set to be filtered and the first scoring weight corresponding to the second scoring feature are obtained, step 303 is executed.
Step 303: and extracting a second image feature corresponding to the second grading feature from each image.
The second image feature refers to an image feature corresponding to the second scoring feature in each image of the image set to be screened.
After the second scoring feature set by the user for the image set to be filtered is obtained, a second image feature corresponding to the second scoring feature may be extracted from each image of the image set to be filtered.
After the second image features are extracted from each image, step 304 is performed.
Step 304: and according to the second grading characteristics, grading the second image characteristics corresponding to each image to obtain a first initial grading value corresponding to each second image characteristic.
The first initial score value is a score value obtained by scoring the second image feature according to the second scoring feature.
After the second image features are extracted from each image, the second image features can be scored according to the second scoring features, so that a first initial scoring value corresponding to each second image feature is obtained.
After obtaining the first initial score value corresponding to each second image feature, step 305 is performed.
Step 305: and calculating the score value of each image according to each first initial score value and each first score weight.
After obtaining the first initial score value corresponding to the second image feature of each image and the first scoring weight corresponding to each second scoring feature, the score value of each image may be calculated by combining the first initial score value corresponding to each image and the first scoring weight, for example, if the first initial score value corresponding to image a is 0.7, the first scoring weight is 0.8, and then the score value of image a is 0.7 × 0.8 — 0.56.
Of course, for each image, the second scoring feature set by the user for each image may be multiple, and then the extracted second image features should also be multiple, each second scoring feature corresponds to one scoring weight, and when calculating, the calculation is performed according to the first initial scoring value and the first scoring weight of each second image feature, for example, the second scoring feature set by the user for image B is a and B, the corresponding first scoring weight is 0.5 and 0.6, the corresponding second image feature is feature 1 and feature 2, after scoring feature 1 with a, the obtained first initial scoring value is 0.8, and after scoring with B, the obtained first initial scoring value is 0.5, and then the final scoring value of image B is 0.5 + 0.8+0.6 — 0.5 — 0.7.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
After the score value of each image is calculated based on the first initial score values and the first scoring weights, step 306 is performed.
Step 306: and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In the present invention, the specific implementation manner of step 306 is similar to the implementation manner of step 105 in the first embodiment, and the specific implementation process may refer to the description of step 105 above, which is not repeated herein in this embodiment of the present invention.
According to the embodiment of the invention, the subjective intention of the user can be increased by combining the user-defined grading characteristics, not only objective grading of the terminal is realized, and the image which the user wants to store can be reserved as much as possible.
The image screening method provided by the embodiment of the invention has the beneficial effects of the image screening method provided by the first embodiment of the invention, and can also grade the image according to the grading characteristics and the grading weight defined by the user, and screen the image according to the grade, so that the user can keep the desired image.
Example four
Referring to fig. 4, a flowchart illustrating steps of an image screening method according to an embodiment of the present invention is shown, which may specifically include the following steps:
step 401: and acquiring an image set to be screened, which is obtained by continuously shooting the shooting object.
In this embodiment of the present invention, a specific implementation manner of step 401 is similar to that of step 101 in the first embodiment, and the specific implementation process may refer to the description of step 101 above, which is not described herein again in this embodiment of the present invention.
Step 402: and acquiring an image scoring area selected by a user for each image.
The image scoring region refers to a region selected by the user for scoring each image of the image set to be screened, for example, if the user selects the upper half region of the image as the scoring region, the upper half region of the image is the image scoring region; or the left half part area of the image is selected as the grading area by the user, and the left half part area of the image is the grading area of the image; of course, the image scoring area may also be an area in which an object such as a person or a green plant in the image selected by the user is located.
After the image set to be filtered is obtained, the user may select a corresponding image scoring region for each image in the image set to be filtered, and it is understood that the image scoring regions selected by the user for each image in the image set to be filtered may be the same region, for example, the regions where people are located are all selected as image scoring regions, or the upper half regions of the images are all selected as image scoring regions, and so on.
After the image scoring area selected by the user for each image is acquired, step 403 is performed.
Step 403: and acquiring a third scoring feature set by the user for each image scoring area and a second scoring weight corresponding to the third scoring feature.
The third scoring feature refers to a feature set by the user for scoring each image scoring area, and the third scoring feature is a user-defined feature, such as a highlight feature, a blur feature, and the like, and may be determined according to actual conditions.
The second scoring weight refers to a weight set by the user for the third scoring feature.
After the image scoring area selected by the user for each image is obtained, the corresponding third scoring feature can be set for the image scoring area by the user, and the corresponding scoring weight is set for the third scoring feature by the user.
For a specific setting process, reference may be made to the description of step 302 in the third embodiment, which is not described herein again in this embodiment of the present invention.
After acquiring the third scoring feature set by the user for each image scoring area and the second scoring weight corresponding to the third scoring feature, step 404 is executed.
Step 404: and extracting regional image features corresponding to the third grading features from the image grading region corresponding to each image.
The regional image feature refers to an image feature corresponding to the third scoring feature in the image scoring region of each image.
And after the third scoring characteristics set by the user for each image scoring area are obtained, extracting corresponding area image characteristics from the image scoring areas of each image according to the third scoring characteristics.
After extracting the region image feature corresponding to the third score feature from the image score region corresponding to each image, step 405 is performed.
Step 405: and scoring the image characteristics of the region according to the third scoring characteristics aiming at each image scoring region to obtain a second initial scoring value.
The second initial score value is a score value obtained by scoring the regional image feature according to the third scoring feature.
After the regional image feature corresponding to the third scoring feature is extracted from the image scoring region corresponding to each image, for the image scoring region of each image, the regional image feature corresponding to the image scoring region may be scored according to the third scoring feature corresponding to the image scoring region, so as to obtain a second initial scoring value.
After the second initial score value is obtained, step 406 is performed.
Step 406: and calculating a region score value corresponding to the image scoring region according to the second initial score value and the second scoring weight, and taking the region score value as the score value of the image.
The region score value means a score value obtained by scoring the image score region of each image.
After obtaining the second initial score value corresponding to the regional image feature of each image and the second scoring weight corresponding to each third scoring feature, the score value of each image may be calculated by combining the second initial score value corresponding to each image and the second scoring weight, for example, if the second initial score value corresponding to image a is 0.7, the second scoring weight is 0.8, and then the score value of image a is 0.7 × 0.8 — 0.56.
Of course, for each image, the third scoring feature set by the user for the image scoring region of each image may be multiple, and then the extracted region image features should also be multiple, each third scoring feature corresponds to one second scoring weight, and when calculating, the calculation is performed according to the second initial scoring value and the second scoring weight of each region image feature, for example, the third scoring feature set by the user for image B is a and B, the corresponding second scoring weights are 0.5 and 0.6, the corresponding region image features are feature 1 and feature 2, after scoring feature 1 with a, the obtained second initial scoring value is 0.8, and after scoring with B, the obtained second initial scoring value is 0.5, then the final scoring value of image B is 0.5 +0.6, 0.5, 0.7.
It should be understood that the above examples are only examples for better understanding of the technical solutions of the embodiments of the present invention, and are not to be taken as the only limitation of the embodiments of the present invention.
Of course, for an image, two or more image scoring regions may be included, and after obtaining the region scoring value of each image scoring region, the region scoring values may be added to obtain the final scoring value of the image.
After calculating the region score value corresponding to the image scoring region according to the second initial score value and the second scoring weight, and taking the region score value as the score value of the image, step 407 is executed.
Step 407: and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In the present invention, the specific implementation manner of step 407 is similar to that of step 105 in the first embodiment, and the specific implementation process may refer to the description of step 105 above, which is not repeated herein in this embodiment of the present invention.
According to the embodiment of the invention, the subjective intention of the user can be increased by combining the user-defined grading characteristics of the partial region of the image, the objective grading of the terminal is not only realized, and the image characteristics which the user wants to store can be reserved as much as possible.
The image screening method provided by the embodiment of the invention has the advantages that the image screening method provided by the embodiment one can also be used for selecting the area and the feature to be scored in the image by the user, then scoring the image, and selecting the image to be saved according to the subjective intention of the user, so that the image desired by the user can be reserved.
EXAMPLE five
Referring to fig. 5, a schematic structural diagram of an image screening apparatus provided in an embodiment of the present invention is shown, which may specifically include the following modules:
an image set obtaining module 510, configured to obtain an image set to be filtered, where the image set is obtained by continuously shooting a shooting object;
a scoring feature obtaining module 520, configured to obtain a scoring feature corresponding to the image set to be filtered;
an image feature extraction module 530, configured to extract an image feature corresponding to the score feature from each image of the image set to be filtered;
a score value obtaining module 540, configured to score each image according to the scoring features and the image features corresponding to each image, so as to obtain a score value of each image;
and the target image screening module 550 is configured to screen, according to each score value, a target image with a score value greater than or equal to a score threshold value from the image set to be screened.
Preferably, the apparatus further comprises:
and the image processing module is used for storing the target image and deleting other images except the target image in the image set to be screened.
The image screening device provided by the embodiment of the invention obtains the grading characteristics corresponding to the image set to be screened by obtaining the image set to be screened, which is obtained by continuously shooting the shooting object, extracts the image characteristics corresponding to the grading characteristics from each image of the image set to be screened, grades each image according to the grading characteristics and the image characteristics corresponding to each image to obtain the grading value of each image, and screens out the target image with the grading value larger than or equal to the grading threshold value from the image set to be screened according to each grading value. According to the embodiment of the invention, each image is scored through the pre-configured scoring characteristics, rather than simply screening out the image with higher definition, so that the accuracy of image screening can be improved.
EXAMPLE six
Referring to fig. 6, a schematic structural diagram of an image screening apparatus provided in an embodiment of the present invention is shown, which may specifically include the following modules:
an image set obtaining module 610, configured to obtain an image set to be filtered, where the image set is obtained by continuously shooting a shooting object;
a scoring feature obtaining module 620, configured to obtain scoring features corresponding to the image set to be filtered;
an image feature extraction module 630, configured to extract an image feature corresponding to the score feature from each image of the image set to be filtered;
a score value obtaining module 640, configured to score each image according to the scoring features and image features corresponding to each image, so as to obtain a score value of each image;
and the target image screening module 650 is configured to screen, according to each of the score values, a target image with a score value greater than or equal to a score threshold from the image set to be screened.
Preferably, the scoring feature obtaining module 620 includes:
the shooting scene determining submodule 621 is configured to determine, according to the image set to be filtered, a shooting scene corresponding to the shooting object;
a matching image obtaining sub-module 622, configured to obtain, from a pre-stored image library, a matching image that has a heat value greater than a heat threshold and matches the shooting scene;
a first feature extraction sub-module 623, configured to extract a first scored feature in the matching image;
the image feature extraction module 630 includes:
a first image feature extraction sub-module 631, configured to extract a first image feature corresponding to the first scoring feature from each of the images;
the score value obtaining module 640 includes:
the comparison result obtaining sub-module 641 is configured to compare the first image feature corresponding to each image with the first scoring feature to obtain a comparison result;
the first score obtaining sub-module 642 is configured to determine a score value of each image according to the comparison result.
The image screening device provided by the embodiment of the invention has the beneficial effects of the image screening device provided by the fifth embodiment, and can be used for scoring each image by combining the scoring characteristics of the images with higher pre-stored heat values, so that the real-time performance and the accuracy of image scoring can be improved.
EXAMPLE seven
Referring to fig. 7, a schematic structural diagram of an image screening apparatus provided in an embodiment of the present invention is shown, which may specifically include the following modules:
an image set obtaining module 710, configured to obtain an image set to be filtered, where the image set is obtained by continuously shooting a shooting object;
a scoring feature obtaining module 720, configured to obtain a scoring feature corresponding to the image set to be filtered;
an image feature extraction module 730, configured to extract an image feature corresponding to the score feature from each image of the image set to be filtered;
a score value obtaining module 740, configured to score each image according to the scoring features and the image features corresponding to each image, so as to obtain a score value of each image;
and the target image screening module 750 is configured to screen a target image with a score value greater than or equal to a score threshold value from the image set to be screened according to each score value.
Preferably, the scoring feature obtaining module 720 includes:
a second feature setting submodule 721 configured to obtain a second scoring feature set for the image set to be filtered by the user and a first scoring weight corresponding to the second scoring feature;
the image feature extraction module 730 includes:
a second image feature extraction sub-module 731, configured to extract, from each of the images, a second image feature corresponding to the second scored feature;
the score value obtaining module 740 includes:
the first initial score obtaining sub-module 741, configured to score, according to the second score features, second image features corresponding to each of the images to obtain a first initial score value corresponding to each of the second image features;
the second score obtaining sub-module 742 is configured to calculate a score value of each image according to each of the first initial score values and each of the first score weights.
The image screening device provided by the embodiment of the invention has the beneficial effects of the image screening device provided by the fifth embodiment, and can also score the images according to the user-defined scoring characteristics and scoring weights and screen the images according to the scores, so that the user can keep the desired images.
Example eight
Referring to fig. 8, a schematic structural diagram of an image screening apparatus provided in an embodiment of the present invention is shown, which may specifically include the following modules:
an image set obtaining module 810, configured to obtain an image set to be filtered, where the image set is obtained by continuously shooting a shooting object;
a scoring feature obtaining module 820, configured to obtain a scoring feature corresponding to the image set to be filtered;
an image feature extraction module 830, configured to extract an image feature corresponding to the score feature from each image of the image set to be filtered;
a score value obtaining module 840, configured to score each image according to the scoring features and image features corresponding to each image, so as to obtain a score value of each image;
and the target image screening module 850 is used for screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
Preferably, the scoring feature obtaining module 820 includes:
a scoring area setting submodule 821 for acquiring an image scoring area selected by the user for each image;
a third feature extraction submodule 822, configured to obtain a third scoring feature set by the user for each image scoring area, and a second scoring weight corresponding to the third scoring feature;
the image feature extraction module 830 includes:
a region feature extraction submodule 831 configured to extract, from an image scoring region corresponding to each of the images, a region image feature corresponding to the third scoring feature;
the score value obtaining module 840 includes:
the second initial scoring acquisition sub-module 841 is configured to score, for each image scoring region, the region image features according to the third scoring feature to obtain a second initial scoring value;
the third score obtaining sub-module 842 is configured to calculate a region score value corresponding to the image score region according to the second initial score value and the second score weight, and use the region score value as the score value of the image.
The image screening device provided by the embodiment of the invention has the beneficial effects of the image screening device provided by the fifth embodiment, and can also be used for selecting the area and the characteristics to be scored in the image by the user, then scoring the image, and selecting the image to be saved according to the subjective intention of the user, so that the image desired by the user can be reserved.
Example nine
Referring to fig. 9, a hardware structure diagram of a mobile terminal for implementing various embodiments of the present invention is shown.
The mobile terminal 900 includes, but is not limited to: a radio frequency unit 901, a network module 902, an audio output unit 903, an input unit 904, a sensor 905, a display unit 906, a user input unit 907, an interface unit 908, a memory 909, a processor 910, and a power supply 911. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 9 is not intended to be limiting of mobile terminals, and that a mobile terminal may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the mobile terminal includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
A processor 910, configured to obtain an image set to be filtered, where the image set is obtained by continuously shooting a shooting object; acquiring scoring characteristics corresponding to the image set to be screened; extracting image features corresponding to the grading features from each image of the image set to be screened; scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image; and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
In the embodiment of the invention, the grading characteristics corresponding to the image set to be screened are obtained by obtaining the image set to be screened, which is obtained by continuously shooting the shooting object, the image characteristics corresponding to the grading characteristics are extracted from each image of the image set to be screened, each image is graded according to the grading characteristics and the image characteristics corresponding to each image to obtain the grading value of each image, and the target image with the grading value larger than the grading threshold value is screened from the image set to be screened according to each grading value. According to the embodiment of the invention, each image is scored through the pre-configured scoring characteristics, rather than simply screening out the image with higher definition, so that the accuracy of image screening can be improved.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 901 may be used for receiving and sending signals during a message transmission and reception process or a call process, and specifically, after receiving downlink data from a base station, the downlink data is processed by the processor 910; in addition, the uplink data is transmitted to the base station. Generally, the radio frequency unit 901 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 901 can also communicate with a network and other devices through a wireless communication system.
The mobile terminal provides the user with wireless broadband internet access via the network module 902, such as helping the user send and receive e-mails, browse web pages, and access streaming media.
The audio output unit 903 may convert audio data received by the radio frequency unit 901 or the network module 902 or stored in the memory 909 into an audio signal and output as sound. Also, the audio output unit 903 may also provide audio output related to a specific function performed by the mobile terminal 900 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 903 includes a speaker, a buzzer, a receiver, and the like.
The input unit 904 is used to receive audio or video signals. The input Unit 904 may include a Graphics Processing Unit (GPU) 9041 and a microphone 9042, and the Graphics processor 9041 processes image data of a still picture or video obtained by an image capturing device (such as a camera) in a video capture mode or an image capture mode. The processed image frames may be displayed on the display unit 906. The image frames processed by the graphic processor 9041 may be stored in the memory 909 (or other storage medium) or transmitted via the radio frequency unit 901 or the network module 902. The microphone 9042 can receive sounds and can process such sounds into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 901 in case of the phone call mode.
The mobile terminal 900 also includes at least one sensor 905, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 9061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 9061 and/or backlight when the mobile terminal 900 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 905 may also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which are not described in detail herein.
The display unit 906 is used to display information input by the user or information provided to the user. The Display unit 906 may include a Display panel 9061, and the Display panel 9061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 907 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 907 includes a touch panel 9071 and other input devices 9072. The touch panel 9071, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 9071 (e.g., operations by a user on or near the touch panel 9071 using a finger, a stylus, or any other suitable object or accessory). The touch panel 9071 may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 910, receives a command from the processor 910, and executes the command. In addition, the touch panel 9071 may be implemented by using various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. The user input unit 907 may include other input devices 9072 in addition to the touch panel 9071. Specifically, the other input devices 9072 may include, but are not limited to, a physical keyboard, function keys (such as a volume control key, a switch key, and the like), a track ball, a mouse, and a joystick, which are not described herein again.
Further, the touch panel 9071 may be overlaid on the display panel 9061, and when the touch panel 9071 detects a touch operation on or near the touch panel 9071, the touch panel is transmitted to the processor 910 to determine the type of the touch event, and then the processor 910 provides a corresponding visual output on the display panel 9061 according to the type of the touch event. Although in fig. 9, the touch panel 9071 and the display panel 9061 are two independent components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 9071 and the display panel 9061 may be integrated to implement the input and output functions of the mobile terminal, which is not limited herein.
The interface unit 908 is an interface through which an external device is connected to the mobile terminal 900. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 908 may be used to receive input from external devices (e.g., data information, power, etc.) and transmit the received input to one or more elements within the mobile terminal 900 or may be used to transmit data between the mobile terminal 900 and external devices.
The memory 909 may be used to store software programs as well as various data. The memory 909 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 909 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 volatile solid-state storage device.
The processor 910 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by running or executing software programs and/or modules stored in the memory 909 and calling data stored in the memory 909, thereby performing overall monitoring of the mobile terminal. Processor 910 may include one or more processing units; preferably, the processor 910 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It is to be appreciated that the modem processor described above may not be integrated into processor 910.
The mobile terminal 900 may also include a power supply 911 (e.g., a battery) for powering the various components, and preferably, the power supply 911 is logically connected to the processor 910 through a power management system that provides power management functions to manage charging, discharging, and power consumption.
In addition, the mobile terminal 900 includes some functional modules that are not shown, and thus will not be described in detail herein.
Preferably, an embodiment of the present invention further provides a mobile terminal, which includes a processor 910, a memory 909, and a computer program stored in the memory 909 and capable of running on the processor 910, and when the computer program is executed by the processor 910, the processes of the above-mentioned embodiment of the image screening method are implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not described here again.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned image screening method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, 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.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (12)

1. An image screening method, comprising:
acquiring an image set to be screened, which is obtained by continuously shooting a shooting object;
acquiring scoring characteristics corresponding to the image set to be screened;
extracting image features corresponding to the grading features from each image of the image set to be screened;
scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image;
and screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
2. The method of claim 1, wherein the step of obtaining scoring characteristics corresponding to the set of images to be filtered comprises:
determining a shooting scene corresponding to the shooting object according to the image set to be screened;
acquiring a matching image of which the heat value is greater than a heat threshold value and which is matched with the shooting scene from a pre-stored image library;
extracting a first scoring feature in the matching image;
the step of extracting the image features corresponding to the scoring features from each image of the image set to be screened includes:
extracting a first image feature corresponding to the first scoring feature from each image;
the step of scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image comprises the following steps:
comparing the first image characteristic corresponding to each image with the first grading characteristic to obtain a comparison result;
and determining the scoring value of each image according to the comparison result.
3. The method of claim 1, wherein the step of obtaining scoring characteristics corresponding to the set of images to be filtered comprises:
acquiring a second grading feature set by a user for the image set to be screened and a first grading weight corresponding to the second grading feature;
the step of extracting the image features corresponding to the scoring features from each image of the image set to be screened includes:
extracting a second image feature corresponding to the second scoring feature from each image;
the step of scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image comprises the following steps:
according to the second grading characteristics, grading the second image characteristics corresponding to each image to obtain first initial grading values corresponding to the second image characteristics;
and calculating the score value of each image according to each first initial score value and each first score weight.
4. The method of claim 1, wherein the step of obtaining scoring characteristics corresponding to the set of images to be filtered comprises:
acquiring an image scoring area selected by a user for each image;
acquiring a third scoring feature set by the user for each image scoring area and a second scoring weight corresponding to the third scoring feature;
the step of extracting the image features corresponding to the scoring features from each image of the image set to be screened includes:
extracting regional image features corresponding to the third grading features from the image grading region corresponding to each image;
the step of scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image comprises the following steps:
for each image scoring area, scoring the area image features according to the third scoring features to obtain second initial scoring values;
and calculating a region score value corresponding to the image scoring region according to the second initial score value and the second scoring weight, and taking the region score value as the score value of the image.
5. The method according to claim 1, further comprising, after the step of screening the target image with a score value greater than a score threshold value from the set of images to be screened according to each of the score values:
and saving the target image, and deleting other images except the target image in the image set to be screened.
6. An image screening apparatus, characterized by comprising:
the image set acquisition module is used for acquiring an image set to be screened, which is obtained by continuously shooting a shooting object;
the scoring characteristic acquisition module is used for acquiring scoring characteristics corresponding to the image set to be screened;
the image feature extraction module is used for extracting image features corresponding to the grading features from each image of the image set to be screened;
the scoring value acquisition module is used for scoring each image according to the scoring characteristics and the image characteristics corresponding to each image to obtain the scoring value of each image;
and the target image screening module is used for screening the target images with the score values larger than or equal to a score threshold value from the image set to be screened according to the score values.
7. The apparatus of claim 6, wherein the scoring feature obtaining module comprises:
the shooting scene determining submodule is used for determining a shooting scene corresponding to the shooting object according to the image set to be screened;
the matching image acquisition sub-module is used for acquiring a matching image which has a heat value larger than a heat threshold value and is matched with the shooting scene from a pre-stored image library;
the first feature extraction submodule is used for extracting first scoring features in the matched image;
the image feature extraction module includes:
the first image feature extraction submodule is used for extracting first image features corresponding to the first grading features from each image;
the score value acquisition module comprises:
the comparison result acquisition sub-module is used for comparing the first image characteristic corresponding to each image with the first grading characteristic to obtain a comparison result;
and the first grading acquisition submodule is used for determining the grading value of each image according to the comparison result.
8. The apparatus of claim 6, wherein the scoring feature obtaining module comprises:
the second feature setting submodule is used for acquiring a second scoring feature set for the image set to be screened by the user and a first scoring weight corresponding to the second scoring feature;
the image feature extraction module includes:
the second image feature extraction submodule is used for extracting second image features corresponding to the second grading features from each image;
the score value acquisition module comprises:
the first initial score obtaining sub-module is used for scoring the second image characteristics corresponding to each image according to the second scoring characteristics to obtain a first initial score value corresponding to each second image characteristic;
and the second grading acquisition submodule is used for calculating and obtaining the grading value of each image according to each first initial grading value and each first grading weight.
9. The apparatus of claim 6, wherein the scoring feature obtaining module comprises:
the scoring area setting submodule is used for acquiring an image scoring area selected by a user for each image;
the third feature extraction submodule is used for acquiring third scoring features set by the user for each image scoring area and second scoring weights corresponding to the third scoring features;
the image feature extraction module includes:
the regional characteristic extraction submodule is used for extracting regional image characteristics corresponding to the third scoring characteristics from the image scoring region corresponding to each image;
the score value acquisition module comprises:
the second initial scoring acquisition sub-module is used for scoring the regional image characteristics according to the third scoring characteristics aiming at each image scoring region to obtain second initial scoring values;
and the third grading acquisition sub-module is used for calculating a region grading value corresponding to the image grading region according to the second initial grading value and the second grading weight, and taking the region grading value as the grading value of the image.
10. The apparatus of claim 6, further comprising:
and the image processing module is used for storing the target image and deleting other images except the target image in the image set to be screened.
11. A mobile terminal, characterized in that it comprises a processor, a memory and a computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, implements the steps of the image screening method according to any one of claims 1 to 5.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the image screening method according to any one of claims 1 to 5.
CN201911042623.4A 2019-10-29 2019-10-29 Image screening method and device and mobile terminal Pending CN110825897A (en)

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