WO2017020488A1 - 图片处理方法及装置 - Google Patents

图片处理方法及装置 Download PDF

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Publication number
WO2017020488A1
WO2017020488A1 PCT/CN2015/097828 CN2015097828W WO2017020488A1 WO 2017020488 A1 WO2017020488 A1 WO 2017020488A1 CN 2015097828 W CN2015097828 W CN 2015097828W WO 2017020488 A1 WO2017020488 A1 WO 2017020488A1
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WIPO (PCT)
Prior art keywords
picture
pictures
similar
group
similarity
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PCT/CN2015/097828
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English (en)
French (fr)
Inventor
张涛
陈志军
龙飞
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小米科技有限责任公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 小米科技有限责任公司 filed Critical 小米科技有限责任公司
Priority to RU2016116892A priority Critical patent/RU2651240C1/ru
Priority to KR1020167013620A priority patent/KR101821750B1/ko
Priority to JP2016532565A priority patent/JP2017531330A/ja
Priority to MX2016005636A priority patent/MX2016005636A/es
Publication of WO2017020488A1 publication Critical patent/WO2017020488A1/zh

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Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/433Content storage operation, e.g. storage operation in response to a pause request, caching operations
    • H04N21/4335Housekeeping operations, e.g. prioritizing content for deletion because of storage space restrictions
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2458Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2477Temporal data queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/54Browsing; Visualisation therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/231Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
    • H04N21/23113Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion involving housekeeping operations for stored content, e.g. prioritizing content for deletion because of storage space restrictions
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/80Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
    • H04N21/83Generation or processing of protective or descriptive data associated with content; Content structuring
    • H04N21/835Generation of protective data, e.g. certificates
    • H04N21/8352Generation of protective data, e.g. certificates involving content or source identification data, e.g. Unique Material Identifier [UMID]

Definitions

  • the embodiments of the present disclosure relate to the field of information technology, and in particular, to a picture processing method and apparatus.
  • the user in order to obtain a satisfactory picture, the user usually uses the mobile terminal to take multiple shots of the same content to obtain multiple pictures containing the same content. Since these pictures have a certain size, if all the pictures are stored in the terminal, not only will occupy the memory of the terminal, but also affect the performance of the terminal, and it will bring great inconvenience to the user's viewing, and thus need to be stored in the terminal.
  • the picture is processed.
  • Embodiments of the present disclosure provide a picture processing method and apparatus.
  • a picture processing method comprising:
  • the attribute information includes at least a shooting time
  • the pictures in each similar picture group are processed according to the detected operation.
  • the picture feature includes a global feature and a local feature
  • the picture in the picture directory is divided into different picture groups, and each picture group includes at least two pictures;
  • processing according to the detected operation, processing a picture in each similar picture group, including:
  • the picture is saved.
  • the method further includes:
  • the delete instruction is used to indicate that the server is in cloud storage Delete the picture in space.
  • the method further includes:
  • a picture processing apparatus comprising:
  • the scanning module is configured to scan all the pictures in the picture directory during the process of cleaning the storage space
  • a similar picture group generating module configured to generate at least one similar picture group according to the attribute information of each picture and the pre-extracted picture feature, where the attribute information includes at least a shooting time;
  • the first display module is configured to display the pictures in each similar picture group in units of similar picture groups according to the shooting time sequence;
  • the processing module is configured to process the pictures in each similar picture group according to the detected operation.
  • the picture feature includes a global feature and a local feature
  • the similar picture group generating module is configured to divide the picture in the picture directory into different picture groups according to the attribute information of the picture, each picture group includes at least two pictures; for any picture group, calculate any two pictures Similarity of the global feature and the similarity of the local feature; when the similarity of the global feature is greater than the first threshold, and the similarity of the local feature is greater than the second threshold, the similarity to the global feature and the Performing a weighting calculation on the similarity of the local features to obtain a weighted calculation result; when the weighted calculation result is greater than the third threshold, the two pictures are regarded as similar pictures; and the picture group is similar to the same picture All the pictures make up a similar picture group.
  • the processing device is configured to display a save option and a delete option on each picture of each similar picture group; if it is detected that the delete option on any picture is selected, delete The picture; if it is detected that the save option on the picture is selected, the picture is saved.
  • the device further includes:
  • the sending module is configured to send a delete command to the server, where the delete command is used to instruct the server to delete the picture in the cloud storage space.
  • the device further includes:
  • a second display module configured to display a picture cleaning option on the storage space cleaning page
  • the scanning module is configured to execute all the pictures in the scanned picture directory when it is detected that the picture cleaning option is selected.
  • a picture processing apparatus including:
  • a memory configured to store instructions executable by the processor
  • processor is configured to:
  • the pictures in each similar picture group are processed according to the detected operation.
  • the picture is divided into a similar picture group, and then the pictures in the similar picture group are displayed in units of similar picture groups according to the shooting time, which is convenient for the user in the similar picture group.
  • the images are processed to make the process easier and less time consuming.
  • FIG. 1 is a flowchart of a picture processing method according to an exemplary embodiment
  • FIG. 2 is a flowchart of a picture processing method according to an exemplary embodiment
  • FIG. 3 is a schematic diagram of a storage space processing page according to an exemplary embodiment
  • FIG. 4 is a schematic diagram of a similar group of pictures, according to an exemplary embodiment
  • FIG. 5(A) is a schematic diagram of a similar group of pictures, according to an exemplary embodiment
  • FIG. 5(B) is a schematic diagram of a similar group of pictures, according to an exemplary embodiment
  • FIG. 6 is a schematic structural diagram of a similar picture processing apparatus according to an exemplary embodiment
  • FIG. 7 is a block diagram of a picture processing apparatus according to an exemplary embodiment.
  • FIG. 1 is a flowchart of a picture processing method according to an exemplary embodiment. As shown in FIG. 1 , a picture processing method is used in a terminal, and includes the following steps.
  • step 101 all the pictures in the picture directory are scanned during the process of cleaning up the storage space.
  • step 102 at least one similar group of pictures is generated according to attribute information of each picture and pre-extracted picture features, and the attribute information includes at least a shooting time.
  • each of the similar picture groups is displayed in the order of shooting time. Pictures in a similar picture group.
  • step 104 the pictures in each similar picture group are processed according to the detected operation.
  • the method provided by the embodiment of the present disclosure divides the picture into a similar picture group based on the attribute information and the picture feature of the picture, and displays the pictures in the similar picture group in units of similar pictures according to the shooting time.
  • the user processes the pictures in the similar picture group, which makes the process more convenient and time-consuming.
  • the picture features include global features and local features
  • Generating at least one similar group of pictures according to attribute information of each picture and pre-extracted picture features including:
  • the picture in the picture directory is divided into different picture groups, and each picture group includes at least two pictures;
  • the pictures in each similar group of pictures are processed according to the detected operations, including:
  • the method further includes:
  • the method further includes:
  • FIG. 2 is a flowchart of a picture processing method according to an exemplary embodiment. As shown in FIG. 2, a picture processing method is used in a terminal, and includes the following steps.
  • step 201 in the process of cleaning up the storage space, the terminal displays a picture cleaning option on the storage space cleaning page.
  • the terminal can be a smart phone, a tablet computer, a desktop computer, etc.
  • the product type of the terminal is not specifically limited.
  • the camera can be installed in the terminal, and the terminal can take various photos based on the installed camera; the terminal can also A screenshot application for screenshots is installed. Based on the installed screenshot application, the terminal can capture an area or the entire area on the screen and save it as a picture.
  • the terminal usually, during the operation of the terminal, some garbage data is generated.
  • the garbage information data occupies the storage space of the terminal, and the storage space of the terminal is limited. If the garbage data is not processed in time, the normal operation of the terminal will be affected. .
  • the terminal In order to clean up the garbage data generated during the terminal operation in time to ensure the smooth operation of the terminal, the terminal generally installs software.
  • the terminal may display multiple options including image cleaning options, plug-in cleaning options, traffic monitoring options, etc. on the storage space cleaning page to implement the terminal. Different types of garbage data are cleaned up.
  • step 202 the terminal detects whether the picture cleaning option is selected, and if so, performs step 203.
  • the manner in which the terminal detects whether the image cleaning option is selected includes, but is not limited to, detecting whether the pressure on the screen of the terminal changes by using a built-in pressure sensor, and when detecting that the pressure of a position on the screen of the terminal changes, the terminal acquires the position.
  • the position coordinate is compared and the position coordinate of the position is compared with the position area where the picture cleaning option is located. If the position coordinate is located in the position area where the picture cleaning option is located, it is determined that the picture cleaning option is selected.
  • the foregoing method is used to detect whether the image cleaning option is selected by the terminal.
  • the terminal may also use other methods to detect whether the image cleaning option is selected. Make specific limits.
  • step 203 the terminal scans all the pictures in the picture directory.
  • the picture directory is a specific directory for storing pictures in the terminal, and the picture in the picture directory may be a picture taken by the camera, or may be a picture intercepted by a screenshot tool, or may be downloaded through a connection network.
  • the picture or the picture received by other functions such as Bluetooth and infrared is not specifically limited in the image format in the image directory.
  • the terminal can preset the scanning order and scan the pictures in the picture directory one by one according to the scanning order.
  • the preset scanning order may be the shooting time of the picture, the size of the picture, and the like.
  • the terminal can scan according to the shooting time in the order of the first and the last. For example, the terminal can scan the picture with the highest shooting time first, and then scan the last time of the shooting time.
  • the picture can also be scanned in the order of the shooting time. For example, the terminal can scan the last picture of the shooting time first, and then scan the picture with the first shooting time.
  • step 204 the terminal generates at least one similar group of pictures according to the attribute information of each picture and the pre-extracted picture features.
  • the image in the picture directory is scanned by the above step 203, and the terminal can obtain each piece.
  • the attribute information of the picture such as shooting time, shooting location, picture size, brightness, contrast, grayscale, and so on.
  • the feature extraction module built in the terminal can also extract the picture features of each picture in the picture directory, and then form a feature file according to the extracted picture features.
  • the picture features include global features and local features.
  • the local features mainly describe the details of the content of the image, including SIFT (Scale-invariant feature transform), SURF (Speed Up Robust Features), etc.
  • the global feature mainly describes the overall properties of the image content. It includes distribution histograms of colors and LBP (Local Binary Patterns) texture histograms.
  • the terminal divides the picture in the picture directory into different picture groups according to the attribute information of the picture, and each picture group includes at least two pictures.
  • the terminal performs continuous shooting on the same content, or performs multiple shots of the same content in the same segment, or uses a screenshot tool to perform multiple screenshots on the same area on the screen during a certain period of time. Similar pictures, these similar pictures usually have the same attribute information. Based on the attribute information, the terminal may divide the picture in the picture directory into different picture groups, and each picture group includes at least two pictures.
  • the terminal may adopt the following methods when dividing the picture in the picture directory into different picture groups.
  • the terminal may divide the pictures whose shooting times are within the same time range into the same group of pictures according to the shooting time.
  • the shooting time of picture A is 2015/5/110:00:00
  • the shooting time of picture B is 2015/5/110:00:20
  • the shooting time of picture C is 2015/5/110:00:54.
  • the shooting time of picture D is 2015/5/1012:20:10
  • the shooting time of picture E is 2015/5/1012:20:56
  • picture A, picture B and picture C can be divided into one picture group
  • Picture D and picture E are divided into one picture group.
  • the terminal may divide the picture of the same shooting location into the same group of pictures according to the shooting location.
  • picture A is shot at Tiananmen Square
  • picture B is taken at the Forbidden City
  • picture C is taken at the Forbidden City
  • picture D is taken at the Bird's Nest
  • picture E is taken at the Bird's Nest
  • picture F is taken at the Forbidden City.
  • the picture B, the picture C, and the picture F may be divided into one picture group
  • the picture D and the picture E are divided into one picture group.
  • the pictures in the picture directory are divided into different picture groups, and the pictures can be divided into different according to pixel value, brightness, contrast, gray level, and the like. Group of pictures.
  • the foregoing conditions may be arbitrarily combined, that is, the pictures in the picture directory may be divided according to at least two conditions, and the specific combinations are not described in the embodiment of the present invention.
  • the terminal calculates the similarity of the global features of any two pictures and the similarity of the local features.
  • the global feature of each picture is composed of the feature values of the key points at different positions.
  • the Euclidean distance of the feature values at the same position of the two pictures can be calculated.
  • the terminal After calculating the feature point values at all positions, the terminal will count the number of eigenvalues whose Euclidean distance is less than the preset value, and then calculate the number of eigenvalues smaller than the preset value in all the eigenvalues participating in the calculation. The proportion, which is the similarity of the global features.
  • the cosine distance of the global features of the two pictures can be calculated.
  • other methods can also be used, which will not be explained here.
  • the method for calculating the similarity of the global feature may also be used.
  • the specific calculation principle may refer to the process of calculating the similarity of the global feature, and details are not described herein again.
  • the threshold value is weighted according to the weight value set in advance for the similarity of the global feature and the similarity of the local feature, and the weighted calculation result is obtained by weighting the similarity of the global feature and the similarity of the local feature, if the weighting calculation result is greater than the third Threshold, the two pictures are treated as similar pictures.
  • the first threshold may be 60%, 70%, etc.
  • the second threshold may be 50%, 65%, etc.
  • the third threshold may be 40%, 63%, etc., in this embodiment, the first threshold, the second threshold,
  • the size of the third threshold is specifically limited.
  • the values of the first threshold, the second threshold, and the third threshold are examples and are not used to limit them.
  • the terminal combines all the pictures in the picture group and the same picture with each other to form a similar picture group.
  • the relationship between any two pictures in each picture group is basically determined, and the terminal can mutually interact with the same picture in each picture group.
  • step 205 the terminal displays the pictures in each similar picture group in units of similar picture groups in order of shooting time.
  • the terminal will also use the similar picture group as the unit according to the shooting time, for each similar picture group.
  • the picture is displayed.
  • the terminal can display in the order of the first and last according to the shooting time, and can also be displayed in the order of the shooting time and the order of the shooting.
  • FIG. 4 is a similar diagram displayed in the order of the shooting time and the order of the shooting.
  • step 206 the terminal processes the pictures in each similar picture group according to the detected operation.
  • the terminal In order to facilitate processing each picture, the terminal also displays a save option and a delete option on each picture of each similar picture group.
  • the save option or the delete option may be in the form of a menu or a button.
  • the form of the save option or the delete option is not specifically limited.
  • the terminal in order to avoid the loss of pictures stored in the terminal, the user also backs up the pictures in the terminal on the cloud storage of the server. Therefore, after the terminal deletes any picture and cleans up its storage space, the terminal also sends a delete instruction to the server, where the delete instruction can be used to instruct the server to delete the picture in the cloud storage space, thereby implementing the cloud to the server. Cleanup of storage space.
  • the picture in the similar picture group After the pictures in the similar picture group are processed by the above method, if the user only saves one picture in the similar picture group, the picture will not be displayed when the similar picture group is displayed next.
  • the terminal adds some similar pictures, the next time you clean up the pictures in the similar picture group, the picture will be displayed together with the pictures in the original similar picture group.
  • the terminal displays the pictures in the similar picture group in the order of the first and last according to the shooting time, the newly added similar picture group will be displayed after the similar picture group saved by the user, as shown in FIG. 5(A);
  • the pictures in the similar picture group are displayed in the order of the last and the first, and the newly added picture will be displayed before the similar picture group saved by the user, as shown in FIG. 5(B).
  • a method provided by an embodiment of the present disclosure based on attribute information such as a photographing time of a picture, and a picture
  • the feature divides the picture into a similar picture group, and then displays the pictures in the similar picture group in units of similar pictures according to the shooting time, which facilitates the user to process the pictures in the similar picture group, which makes the process more convenient. It takes less time.
  • FIG. 6 is a schematic diagram of a picture processing apparatus according to an exemplary embodiment.
  • the device includes: a scanning module 601, a similar picture group generating module 602, a first display module 603, and a processing module 604.
  • the scanning module 601 is configured to scan all the pictures in the picture directory during the process of cleaning the storage space;
  • the similar picture group generating module 602 is configured to generate at least one similar picture group according to the attribute information of each picture and the pre-extracted picture feature, where the attribute information includes at least a shooting time;
  • the first display module 603 is configured to display pictures in each similar picture group in units of similar picture groups in order of shooting time;
  • the processing module 604 is configured to process pictures in each similar group of pictures based on the detected operations.
  • the picture features include global features and local features
  • the similar picture group generation module 602 is configured to divide the picture in the picture directory into different picture groups, each picture group includes at least two pictures; for any picture group, calculate the similarity of the global features of any two pictures. And the similarity of the local features; when the similarity of the global features is greater than the first threshold, and the similarity of the local features is greater than the second threshold, weighting the similarity of the global features and the similarity of the local features to obtain a weighted calculation result; When the weighting calculation result is greater than the third threshold, the two pictures are regarded as similar pictures; all the pictures in the picture group that are similar to each other in the same picture form a similar picture group.
  • the processing module 604 is configured to display a save option and a delete option on each picture of each similar picture group; if it is detected that the delete option on any picture is selected, delete Image; save if it detects that the save option on the image is selected image.
  • the apparatus further includes: a transmitting module.
  • the sending module is configured to send a delete instruction to the server, where the delete command is used to instruct the server to delete the picture in the cloud storage space.
  • the apparatus further includes: a second display module.
  • the second display module is configured to display a picture cleaning option on the storage space cleaning page
  • the scanning module 601 is configured to execute all the pictures in the scanned picture directory when it is detected that the picture cleaning option is selected.
  • the device provided by the embodiment of the present disclosure divides the picture into a similar picture group based on the attribute information and the picture feature of the picture, and displays the picture in the similar picture group in units of similar pictures according to the shooting time.
  • the user processes the pictures in the similar picture group, which makes the process more convenient and time-consuming.
  • FIG. 7 is a block diagram of an apparatus 700 configured for picture processing, according to an exemplary embodiment.
  • device 700 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a gaming console, a tablet device, a medical device, a fitness device, a personal digital assistant, and the like.
  • apparatus 700 can include one or more of the following components: processing component 702, memory 704, power component 706, multimedia component 708, audio component 710, input/output (I/O) interface 712, sensor component 714, and Communication component 716.
  • Processing component 702 typically controls the overall operation of device 700, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations.
  • Processing component 702 can include one or more processors 720 to execute instructions to perform all or part of the steps described above.
  • processing component 702 can include one or more modules to facilitate interaction between component 702 and other components.
  • the processing component 702 can include a multimedia module to facilitate multimedia The interaction between body component 708 and processing component 702.
  • Memory 704 is configured to store various types of data to support operation at device 700. Examples of such data include instructions for any application or method operating on device 700, contact data, phone book data, messages, pictures, videos, and the like. Memory 704 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Disk or Optical Disk.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read only memory
  • EPROM erasable Programmable Read Only Memory
  • PROM Programmable Read Only Memory
  • ROM Read Only Memory
  • Magnetic Memory Flash Memory
  • Disk Disk or Optical Disk.
  • Power component 706 provides power to various components of device 700.
  • Power component 706 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for device 700.
  • the multimedia component 708 includes a screen between the device 700 and the user that provides an output interface.
  • the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user.
  • the touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor may sense not only the boundary of the touch or sliding action, but also the duration and pressure associated with the touch or slide operation.
  • the multimedia component 708 includes a front camera and/or a rear camera. When the device 700 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera can receive external multimedia data. Each front and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.
  • the audio component 710 is configured to output and/or input an audio signal.
  • audio component 710 includes a microphone (MIC) that is configured to receive an external audio signal when device 700 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode.
  • the received audio signal may be further stored in memory 704 or transmitted via communication component 716.
  • the audio component 710 also includes a speaker configured to output an audio signal.
  • the I/O interface 712 provides an interface between the processing component 702 and the peripheral interface module, which may be a keyboard, a click wheel, a button, or the like. These buttons may include, but are not limited to, a home button, a volume button, a start button, and a lock button.
  • Sensor assembly 714 includes one or more sensors configured to provide a status assessment of various aspects of device 700.
  • sensor assembly 714 can detect an open/closed state of device 700, relative positioning of components, such as the display and keypad of device 700, and sensor component 714 can also detect a change in position of one component of device 700 or device 700. The presence or absence of user contact with device 700, device 700 orientation or acceleration/deceleration, and temperature variation of device 700.
  • Sensor assembly 714 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact.
  • Sensor component 714 can also include a light sensor, such as a CMOS or CCD image sensor, configured for use in imaging applications.
  • the sensor component 714 can also include an acceleration sensor, a gyro sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
  • Communication component 716 is configured to facilitate wired or wireless communication between device 700 and other devices.
  • the device 700 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof.
  • communication component 716 receives broadcast signals or broadcast associated information from an external broadcast management system via a broadcast channel.
  • the communication component 716 also includes a near field communication (NFC) module to facilitate short range communication.
  • NFC near field communication
  • the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • apparatus 700 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable A gate array (FPGA), controller, microcontroller, microprocessor, or other electronic component implementation configured to perform the above methods.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGA field programmable A gate array
  • controller microcontroller, microprocessor, or other electronic component implementation configured to perform the above methods.
  • non-transitory computer readable storage medium comprising instructions, such as a memory 704 comprising instructions executable by processor 720 of apparatus 700 to perform the above method.
  • the non-transitory computer readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device.
  • a non-transitory computer readable storage medium when instructions in the storage medium are executed by a processor of a mobile terminal, enabling the mobile terminal to perform a picture processing method, the method comprising:
  • the pictures in each similar picture group are processed according to the detected operation.
  • the picture features include global features and local features
  • Generating at least one similar group of pictures according to attribute information of each picture and pre-extracted picture features including:
  • the pictures in each similar group of pictures are processed according to the detected operations, including:
  • the method further includes:
  • the method further includes:
  • the non-transitory computer readable storage medium provided by the embodiment of the present disclosure divides the picture into a similar picture group based on attribute information such as the shooting time of the picture and the picture feature, and then displays the similar picture in units of similar pictures according to the shooting time.
  • the pictures in the picture group facilitate the user to process the pictures in the similar picture group, which makes the process more convenient and time-consuming.
  • the picture is divided into a similar picture group, and then the pictures in the similar picture group are displayed in units of similar picture groups according to the shooting time, which is convenient for the user in the similar picture group.
  • the images are processed to make the process easier and less time consuming.

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Abstract

本公开实施例是关于一种图片处理方法及装置,属于终端技术领域。所述方法包括:在清理存储空间的过程中,扫描图片目录下的所有图片;根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;根据检测到的操作对每个相似图片组中的图片进行处理。

Description

图片处理方法及装置
本申请基于申请号为201510465211.7、申请日为2015年7月31日的中国专利申请提出,并要求该中国专利申请的优先权,该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开实施例涉及信息技术领域,尤其涉及一种图片处理方法及装置。
背景技术
在现代生活中,为了获取到一张满意的图片,用户通常会使用移动终端对同一内容进行多次拍摄,以得到多张包含相同内容的图片。由于这些图片具有一定的大小,如果将这些图片全部存储在终端中,不仅会占据终端的内存,影响终端的性能,而且会给用户的查看带来的极大的不便,因而需要对终端中存储的图片进行处理。
目前,相关技术在对图片进行处理时,需要打开相册应用,并借助用户肉眼从图片目录下识别出相似的图片,进而通过检测用户的操作对这些图片进行清理。如果检测到用户选中了图片上的删除选项,则删除该图片;如果检测到用户选中了图片上的保存选项,则保存该图片。
发明内容
本公开实施例提供一种图片处理方法及装置。
根据本公开实施例的第一方面,提供一种图片处理方法,所述方法包括:
在清理存储空间的过程中,扫描图片目录下的所有图片;
根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似 图片组,所述属性信息至少包括拍摄时间;
按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
根据检测到的操作对每个相似图片组中的图片进行处理。
可选地,所述图片特征包括全局特征和局部特征;
所述根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,包括:
根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;
对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;
如果所述全局特征的相似度大于第一阈值,且所述局部特征的相似度大于第二阈值,对所述全局特征的相似度和所述局部特征的相似度进行加权计算,得到加权计算结果;
如果所述加权计算结果大于第三阈值,则将所述两张图片作为相似图片;
将所述图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
可选地,所述根据检测到的操作对每个相似图片组中的图片进行处理,包括:
在每个相似图片组的每张图片上显示保存选项和删除选项;
如果检测到任一张图片上的删除选项被选中,删除所述图片;
如果检测到所述图片上的保存选项被选中,保存所述图片。
可选地,所述删除所述图片之后,还包括:
向服务器发送删除指令,所述删除指令用于指示所述服务器在云存储 空间中删除所述图片。
可选地,所述方法还包括:
在存储空间清理页面上显示图片清理选项;
当检测到所述图片清理选项被选中,执行扫描图片目录下的所有图片。
根据本公开实施例的第二方面,提供一种图片处理装置,所述装置包括:
扫描模块,配置为在清理存储空间的过程中,扫描图片目录下的所有图片;
相似图片组生成模块,配置为根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;
第一显示模块,配置为按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
处理模块,配置为根据检测到的操作对每个相似图片组中的图片进行处理。
可选地,所述图片特征包括全局特征和局部特征;
所述相似图片组生成模块,配置为根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;当所述全局特征的相似度大于第一阈值,且所述局部特征的相似度大于第二阈值,对所述全局特征的相似度和所述局部特征的相似度进行加权计算,得到加权计算结果;当所述加权计算结果大于第三阈值,则将所述两张图片作为相似图片;将所述图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
可选地,所述处理装置,配置为在每个相似图片组的每张图片上显示保存选项和删除选项;如果检测到任一张图片上的删除选项被选中,删除 所述图片;如果检测到所述图片上的保存选项被选中,保存所述图片。
可选地,所述装置还包括:
发送模块,配置为向服务器发送删除指令,所述删除指令用于指示所述服务器在云存储空间中删除所述图片。
可选地,所述装置还包括:
第二显示模块,配置为在存储空间清理页面上显示图片清理选项;
所述扫描模块,配置为当检测到所述图片清理选项被选中,执行扫描图片目录下的所有图片。
根据本公开实施例的第三方面,提供一种图片处理装置,包括:
处理器;
配置为存储处理器可执行的指令的存储器;
其中,所述处理器被配置为:
在清理存储空间的过程中,扫描图片目录下的所有图片;
根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;
按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
根据检测到的操作对每个相似图片组中的图片进行处理。
本公开的实施例提供的技术方案可以包括以下有益效果:
基于图片的拍摄时间等属性信息以及图片特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。
应当理解的是,以上的一般描述和后文的细节描述仅是示例性和解释性的,并不能限制本公开。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分,示出了符合本公开的实施例,并与说明书一起用于解释本公开的原理。
图1是根据一示例性实施例示出的一种图片处理方法的流程图;
图2是根据一示例性实施例示出的一种图片处理方法的流程图;
图3是根据一示例性实施例示出的一种存储空间处理页面的示意图;
图4是根据一示例性实施例示出的一种相似图片组的示意图;
图5(A)是根据一示例性实施例示出的一种相似图片组的示意图;
图5(B)是根据一示例性实施例示出的一种相似图片组的示意图;
图6是根据一示例性实施例示出的一种相似图片处理装置的结构示意图;
图7是根据一示例性实施例示出的一种图片处理装置的框图。
具体实施方式
这里将详细地对示例性实施例进行说明,其示例表示在附图中。下面的描述涉及附图时,除非另有表示,不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本公开相一致的所有实施方式。相反,它们仅是与如所附权利要求书中所详述的、本公开的一些方面相一致的装置和方法的例子。
图1是根据一示例性实施例示出的一种图片处理方法的流程图,如图1所示,图片处理方法用于终端中,包括以下步骤。
在步骤101中,在清理存储空间的过程中,扫描图片目录下的所有图片。
在步骤102中,根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,该属性信息至少包括拍摄时间。
在步骤103中,按照拍摄时间顺序,以相似图片组为单位,显示每个 相似图片组中的图片。
在步骤104中,根据检测到的操作对每个相似图片组中的图片进行处理。
本公开实施例提供的方法,基于图片的拍摄时间等属性信息以及图片特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。
在本公开的另一个实施例中,图片特征包括全局特征和局部特征;
根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,包括:
根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;
对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;
如果全局特征的相似度大于第一阈值,且局部特征的相似度大于第二阈值,对全局特征的相似度和局部特征的相似度进行加权计算,得到加权计算结果;
如果加权计算结果大于第三阈值,则将两张图片作为相似图片;
将图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
在本公开的另一个实施例中,根据检测到的操作对每个相似图片组中的图片进行处理,包括:
在每个相似图片组的每张图片上显示保存选项和删除选项;
如果检测到任一张图片上的删除选项被选中,删除图片;
如果检测到图片上的保存选项被选中,保存图片。
在本公开的另一个实施例中,删除图片之后,还包括:
向服务器发送删除指令,删除指令用于指示服务器在云存储空间中删除图片。
在本公开的另一个实施例中,该方法还包括:
在存储空间清理页面上显示图片清理选项;
当检测到图片清理选项被选中,执行扫描图片目录下的所有图片。
上述所有可选技术方案,可以采用任意结合形成本公开的可选实施例,在此不再一一赘述。
图2是根据一示例性实施例示出的一种图片处理方法的流程图,如图2所示,图片处理方法用于终端中,包括以下步骤。
在步骤201中,在清理存储空间的过程中,终端在存储空间清理页面上显示图片清理选项。
其中,图片的形式有多种,可以为通过摄像头拍摄的照片,还可以为使用截图工具截取到的图片等。终端可以为智能手机、平板电脑、台式电脑等,本实施例不对终端的产品类型作具体的限定,该终端中可以安装有摄像头,基于安装的摄像头,终端可拍摄各种照片;终端中还可以安装有用于截图的截图应用,基于安装的截图应用,终端可截取屏幕上的某一区域或整个区域并保存为图片。
通常终端在运行过程中,会产生一些垃圾数据,这些垃圾信息数据占据着终端的存储空间,而终端的存储空间有限,如果未能及时地对这些垃圾数据进行处理,将影响到终端的正常运行。为及时对终端运行过程中产生的垃圾数据进行清理,以确保终端顺利运行,终端一般会安装软件。
在运行清理软件清理存储空间的过程中,如图3所示,终端可在存储空间清理页面上显示包括图片清理选项、插件清理选项、流量监控选项等在内的多个选项,以实现对终端中不同种类的垃圾数据进行清理。
在步骤202,终端检测到图片清理选项是否被选中,如果是,执行步骤203。
关于终端检测图片清理选项是否被选中的方式,包括但不限于:借助内置的压力传感器检测终端屏幕上的压力是否变化,当检测到终端屏幕上某一位置的压力发生变化,终端将获取该位置的位置坐标,并将该位置的位置坐标与图片清理选项所在的位置区域进行比对,如果该位置坐标位于图片清理选项所在的位置区域内,则确定图片清理选项被选中。
上述通过检测终端屏幕上的压力变化,仅为终端检测图片清理选项是否被选中的一种方式,在实际应用中,终端还可以采用其他方式检测图片清理选项是否被选中,本实施例对此不作进行具体的限定。
在步骤203中,终端扫描图片目录下的所有图片。
在本实施例中,图片目录为终端中用于存储图片的特定目录,图片目录下的图片可以为通过摄像头拍摄的照片,还可以为通过截图工具截取的图片,也可以为通过连接网络下载的图片或开启蓝牙、红外等功能从其他终端上接收到的图片,本实施例不对图片目录下的图片形式作具体的限定。
终端在扫描图片目录下的图片时,可预先设定扫描次序,并按照扫描次序逐一扫描图片目录下的图片。预先设定的扫描次序可以为图片的拍摄时间、图片的大小等等。以扫描次序为拍摄时间为例,终端在扫描图片目录下的图片时,可按照拍摄时间由先及后的顺序进行扫描,比如,终端可先扫描拍摄时间最前的图片,后扫描拍摄时间最后的图片;还可按照拍摄时间由后及先的顺序进行扫描,比如,终端可先扫描拍摄时间最后的图片,后扫描拍摄时间最先的图片。
在步骤204中,终端根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组。
通过上述步骤203对图片目录下的图片进行扫描,终端可获取到每张 图片的属性信息,如,拍摄时间、拍摄地点、图片大小、亮度、对比度、灰度等等。同时终端内置的特征提取模块,还可提取图片目录下每张图片的图片特征,进而根据提取的图片特征组成一个特征文件。其中,图片特征包括全局特征和局部特征等。局部特征主要描述图片内容的细节变化,包括SIFT(Scale-invariant feature transform,尺度不变特征变换)、SURF(Speed Up Robust Features,快速鲁棒特征)等;全局特征主要描述图片内容的整体属性,包括颜色的分布直方图以及LBP(Local Binary Patterns,局部二值模式)纹理直方图等。
终端在根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组时,可采用如下步骤(1)~(3):
(1)、终端根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片。
一般情况下,终端对同一内容进行连拍,或者,在同一间段内对同一内容进行多次拍摄,或者,在某一时间段内使用截图工具对屏幕上同一区域进行多次截图均会产生相似图片,这些相似图片中通常会具有相同的属性信息。基于属性信息的不同,终端可将图片目录下的图片划分为不同的图片组,且每个图片组中至少包含两张图片。
由于属性信息中所包含的不同信息,终端在将图片目录下的图片划分为不同的图片组时,可采用如下几种方式。
在本公开的一个实施例中,终端可依据拍摄时间,将拍摄时间在同一时间范围内的图片划分为同一图片组。例如,图片A的拍摄时间为2015/5/110:00:00,图片B的拍摄时间为2015/5/110:00:20,图片C的拍摄时间为2015/5/110:00:54,图片D的拍摄时间为2015/5/1012:20:10,图片E的拍摄时间为2015/5/1012:20:56,则可将图片A、图片B及图片C划分为一个图片组,将图片D和图片E划分为一个图片组。
在本公开的另一个实施例中,终端可依据拍摄地点,将同一拍摄地点的图片划分为同一图片组。例如,图片A的拍摄地点为天安门,图片B的拍摄时间为故宫,图片C的拍摄时间为故宫,图片D的拍摄时间为鸟巢,图片E的拍摄时间为鸟巢,图片F的拍摄地点为故宫,则可将图片B、图片C及图片F划分为一个图片组,将图片D和图片E划分为一个图片组。
在实际应用中,除了按照每张图片的拍摄时间及拍摄地点,将图片目录下的图片划分到不同的图片组外,还可按照像素值、亮度、对比度、灰度等,将图片划分到不同的图片组。当然,上述条件还可以任意组合,也即是,可按照上述至少两个条件,对图片目录中的图片进行划分,在本发明实施例中不对其具体组合进行赘述。
(2)、对于任一图片组,终端计算任意两张图片的全局特征的相似度以及局部特征的相似度。
通常每张图片的全局特征由不同位置上关键点的特征值组成,在计算任意两张图片的全局特征的相似度时,可计算两张图片相同位置上的特征值的欧氏距离。当对所有位置上的特征点值计算完毕之后,终端将统计欧氏距离小于预设数值的特征值的个数,进而计算小于预设数值的特征值的个数在全部参与计算的特征值中所占的比例,该比例即为全局特征的相似度。
在实际计算中,除了通过计算两张图片全局特征的欧氏距离之外,还可以计算两张图片全局特征的余弦距离,当然,还可以采用其他方法,此处不再一一说明。
对于任意两张图片的局部特征相似度,也可采用上述计算全局特征的相似度的方法,具体的计算原理可参照计算全局特征的相似度的过程,此处不再赘述。
如果全局特征的相似度大于第一阈值,且局部特征的相似度大于第二 阈值,则根据预先为全局特征的相似度以及局部特征的相似度设置的权重值,对全局特征的相似度和局部特征的相似度进行加权计算,得到加权计算结果,如果加权计算结果大于第三阈值,则将两张图片作为相似图片。其中,第一阈值可以为60%、70%等,第二阈值可以为50%、65%等,第三阈值可以为40%、63%等,本实施例不对第一阈值、第二阈值、第三阈值的大小作具体的限定。
上述第一阈值、第二阈值、第三阈值的值为举例,并不用于对其进行限制。
(3)、终端将图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
当将图片组内的所有图片采用上述方式进行比较之后,每个图片组内任意两张图片之间的关系就基本上确定下来,此时终端就可每个将图片组内与同一张图片互为相似图片的所有图片组成一个相似图片组。例如,图片组中有五张图片,分别为图片A、图片B、图片C、图片D和图片E,如果图片A和图片B为相似图片,图片B与图片C为相似图片,图片A与图片C不是相似图片,图片A与图片D不是相似图片,图片B与图片D不是相似图片,图片D与图片E是相似图片,则将图片A、图片B与图片C组成一个相似图片组,将图片D与图片E组成一个相似图片组。
在步骤205中,终端按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片。
为了便于用户对相似图片组中的图片进行处理,当将图片目录下的图片划分为不同的相似图片组之后,终端还将按照拍摄时间,以相似图片组为单位,对每个相似图片组中的图片进行显示。在显示过程中,终端即可按照拍摄时间由先及后的顺序进行显示,还可按照拍摄时间由后及先的顺序进行显示。例如,图4为按照拍摄时间由后及先的顺序所显示的相似图 片组中的图片。
在步骤206中,终端根据检测到的操作对每个相似图片组中的图片进行处理。
为了方便对每张图片进行处理,终端还将在每个相似图片组的每张图片上显示保存选项和删除选项,该保存选项或删除选项可以为菜单形式,也可以为按钮形式,本实施例不对保存选项或删除选项的形式作具体的限定。当将所有图片按照时间顺序,并且按照相似聚集的方式显示出来时,用户就可以快速地对这些图片进行查看,终端通过检测用户的操作,可对每个相似图片组中的图片进行处理。如果检测到任一张图片上的删除选项被选中,则终端将删除该图片;如果检测到图片上的保存选项被选中,则终端将保存该图片。
通常情况下,为了避免终端中所存储的图片丢失,用户还将终端中的图片在服务器的云存储器上进行备份。因而当终端将任一张图片删除之后,对自身的存储空间进行清理后,终端还将向服务器发送删除指令,该删除指令可用于指示服务器在云存储空间中删除图片,从而实现对服务器的云存储空间的清理。
当通过上述方法对相似图片组中的图片进行处理之后,如果用户仅保存了相似图片组中的一张图片,则在下一显示相似图片组时,该图片不会被显示出来。当终端新增了一些相似图片,在下一次清理相似图片组中的图片时,该图片将与原有的相似图片组中的图片一同显示出来。如果终端按照拍摄时间由先及后的顺序显示相似图片组中的图片,则该新增的相似图片组将显示在用户所保存的相似图片组之后,如图5(A)所示;如果终端按照拍摄时间由后及先的顺序显示相似图片组中的图片,则该新增的图片将显示在用户所保存的相似图片组之前,如图5(B)所示。
本公开实施例提供的方法,基于图片的拍摄时间等属性信息以及图片 特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。
图6是根据一示例性实施例示出的一种图片处理装置示意图。参照图6,该装置包括:扫描模块601、相似图片组生成模块602、第一显示模块603及处理模块604。
该扫描模块601被配置为在清理存储空间的过程中,扫描图片目录下的所有图片;
该相似图片组生成模块602被配置为根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,属性信息至少包括拍摄时间;
该第一显示模块603被配置为按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
该处理模块604被配置为根据检测到的操作对每个相似图片组中的图片进行处理。
在本公开的另一个实施例中,图片特征包括全局特征和局部特征;
该相似图片组生成模块602被配置为将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;当全局特征的相似度大于第一阈值,且局部特征的相似度大于第二阈值,对全局特征的相似度和局部特征的相似度进行加权计算,得到加权计算结果;当加权计算结果大于第三阈值,则将两张图片作为相似图片;将图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
在本公开的另一个实施例中,该处理模块604被配置为在每个相似图片组的每张图片上显示保存选项和删除选项;如果检测到任一张图片上的删除选项被选中,删除图片;如果检测到图片上的保存选项被选中,保存 图片。
在本公开的另一个实施例中,该装置还包括:发送模块。
该发送模块被配置为向服务器发送删除指令,删除指令用于指示服务器在云存储空间中删除图片。
在本公开的另一个实施例中,该装置还包括:第二显示模块。
该第二显示模块被配置为在存储空间清理页面上显示图片清理选项;
该扫描模块601被配置为当检测到图片清理选项被选中,执行扫描图片目录下的所有图片。
本公开实施例提供的装置,基于图片的拍摄时间等属性信息以及图片特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。
关于上述实施例中的装置,其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述,此处将不做详细阐述说明。
图7是根据一示例性实施例示出的一种配置为图片处理的装置700的框图。例如,装置700可以是移动电话,计算机,数字广播终端,消息收发设备,游戏控制台,平板设备,医疗设备,健身设备,个人数字助理等。
参照图7,装置700可以包括以下一个或多个组件:处理组件702,存储器704,电源组件706,多媒体组件708,音频组件710,输入/输出(I/O)接口712,传感器组件714,以及通信组件716。
处理组件702通常控制装置700的整体操作,诸如与显示,电话呼叫,数据通信,相机操作和记录操作相关联的操作。处理组件702可以包括一个或多个处理器720来执行指令,以完成上述的方法的全部或部分步骤。此外,处理组件702可以包括一个或多个模块,便于处理组件702和其他组件之间的交互。例如,处理组件702可以包括多媒体模块,以方便多媒 体组件708和处理组件702之间的交互。
存储器704被配置为存储各种类型的数据以支持在装置700的操作。这些数据的示例包括用于在装置700上操作的任何应用程序或方法的指令,联系人数据,电话簿数据,消息,图片,视频等。存储器704可以由任何类型的易失性或非易失性存储设备或者它们的组合实现,如静态随机存取存储器(SRAM),电可擦除可编程只读存储器(EEPROM),可擦除可编程只读存储器(EPROM),可编程只读存储器(PROM),只读存储器(ROM),磁存储器,快闪存储器,磁盘或光盘。
电源组件706为装置700的各种组件提供电力。电源组件706可以包括电源管理系统,一个或多个电源,及其他与为装置700生成、管理和分配电力相关联的组件。
多媒体组件708包括在所述装置700和用户之间的提供一个输出接口的屏幕。在一些实施例中,屏幕可以包括液晶显示器(LCD)和触摸面板(TP)。如果屏幕包括触摸面板,屏幕可以被实现为触摸屏,以接收来自用户的输入信号。触摸面板包括一个或多个触摸传感器以感测触摸、滑动和触摸面板上的手势。所述触摸传感器可以不仅感测触摸或滑动动作的边界,而且还检测与所述触摸或滑动操作相关的持续时间和压力。在一些实施例中,多媒体组件708包括一个前置摄像头和/或后置摄像头。当装置700处于操作模式,如拍摄模式或视频模式时,前置摄像头和/或后置摄像头可以接收外部的多媒体数据。每个前置摄像头和后置摄像头可以是一个固定的光学透镜系统或具有焦距和光学变焦能力。
音频组件710被配置为输出和/或输入音频信号。例如,音频组件710包括一个麦克风(MIC),当装置700处于操作模式,如呼叫模式、记录模式和语音识别模式时,麦克风被配置为接收外部音频信号。所接收的音频信号可以被进一步存储在存储器704或经由通信组件716发送。在一些实 施例中,音频组件710还包括一个扬声器,配置为输出音频信号。
I/O接口712为处理组件702和外围接口模块之间提供接口,上述外围接口模块可以是键盘,点击轮,按钮等。这些按钮可包括但不限于:主页按钮、音量按钮、启动按钮和锁定按钮。
传感器组件714包括一个或多个传感器,配置为为装置700提供各个方面的状态评估。例如,传感器组件714可以检测到装置700的打开/关闭状态,组件的相对定位,例如所述组件为装置700的显示器和小键盘,传感器组件714还可以检测装置700或装置700一个组件的位置改变,用户与装置700接触的存在或不存在,装置700方位或加速/减速和装置700的温度变化。传感器组件714可以包括接近传感器,被配置用来在没有任何的物理接触时检测附近物体的存在。传感器组件714还可以包括光传感器,如CMOS或CCD图像传感器,配置为在成像应用中使用。在一些实施例中,该传感器组件714还可以包括加速度传感器,陀螺仪传感器,磁传感器,压力传感器或温度传感器。
通信组件716被配置为便于装置700和其他设备之间有线或无线方式的通信。装置700可以接入基于通信标准的无线网络,如WiFi,2G或3G,或它们的组合。在一个示例性实施例中,通信组件716经由广播信道接收来自外部广播管理系统的广播信号或广播相关信息。在一个示例性实施例中,所述通信组件716还包括近场通信(NFC)模块,以促进短程通信。例如,在NFC模块可基于射频识别(RFID)技术,红外数据协会(IrDA)技术,超宽带(UWB)技术,蓝牙(BT)技术和其他技术来实现。
在示例性实施例中,装置700可以被一个或多个应用专用集成电路(ASIC)、数字信号处理器(DSP)、数字信号处理设备(DSPD)、可编程逻辑器件(PLD)、现场可编程门阵列(FPGA)、控制器、微控制器、微处理器或其他电子元件实现,配置为执行上述方法。
在示例性实施例中,还提供了一种包括指令的非临时性计算机可读存储介质,例如包括指令的存储器704,上述指令可由装置700的处理器720执行以完成上述方法。例如,所述非临时性计算机可读存储介质可以是ROM、随机存取存储器(RAM)、CD-ROM、磁带、软盘和光数据存储设备等。
一种非临时性计算机可读存储介质,当所述存储介质中的指令由移动终端的处理器执行时,使得移动终端能够执行一种图片处理方法,所述方法包括:
在清理存储空间的过程中,扫描图片目录下的所有图片;
根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,属性信息至少包括拍摄时间;
按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
根据检测到的操作对每个相似图片组中的图片进行处理。
在本公开的另一个实施例中,图片特征包括全局特征和局部特征;
根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,包括:
将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;
对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;
如果全局特征的相似度大于第一阈值,且局部特征的相似度大于第二阈值,对全局特征的相似度和局部特征的相似度进行加权计算,得到加权计算结果;
如果加权计算结果大于第三阈值,则将两张图片作为相似图片;
将图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
在本公开的另一个实施例中,根据检测到的操作对每个相似图片组中的图片进行处理,包括:
在每个相似图片组的每张图片上显示保存选项和删除选项;
如果检测到任一张图片上的删除选项被选中,删除图片;
如果检测到图片上的保存选项被选中,保存图片。
在本公开的另一个实施例中,删除图片之后,还包括:
向服务器发送删除指令,删除指令用于指示服务器在云存储空间中删除图片。
在本公开的另一个实施例中,该方法还包括:
在存储空间清理页面上显示图片清理选项;
当检测到图片清理选项被选中,执行扫描图片目录下的所有图片。
本公开实施例提供的非临时性计算机可读存储介质,基于图片的拍摄时间等属性信息以及图片特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。
本领域技术人员在考虑说明书及实践这里公开的公开后,将容易想到本公开的其它实施方案。本申请旨在涵盖本公开的任何变型、用途或者适应性变化,这些变型、用途或者适应性变化遵循本公开的一般性原理并包括本公开未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的,本公开的真正范围和精神由下面的权利要求指出。
应当理解的是,本公开并不局限于上面已经描述并在附图中示出的精确结构,并且可以在不脱离其范围进行各种修改和改变。本公开的范围仅由所附的权利要求来限制。
工业实用性
基于图片的拍摄时间等属性信息以及图片特征,将图片划分为一个相似图片组,进而按照拍摄时间,以相似图片组为单位,显示相似图片组中的图片,方便了用户对相似图片组中的图片进行处理,使得处理过程更为便捷、耗时更短。

Claims (11)

  1. 一种图片处理方法,所述方法包括:
    在清理存储空间的过程中,扫描图片目录下的所有图片;
    根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;
    按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
    根据检测到的操作对每个相似图片组中的图片进行处理。
  2. 根据权利要求1所述的方法,其中,所述图片特征包括全局特征和局部特征;
    所述根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,包括:
    根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;
    对于任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;
    如果所述全局特征的相似度大于第一阈值,且所述局部特征的相似度大于第二阈值,对所述全局特征的相似度和所述局部特征的相似度进行加权计算,得到加权计算结果;
    如果所述加权计算结果大于第三阈值,则将所述两张图片作为相似图片;
    将所述图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
  3. 根据权利要求1所述的方法,其中,所述根据检测到的操作对每个相似图片组中的图片进行处理,包括:
    在每个相似图片组的每张图片上显示保存选项和删除选项;
    如果检测到任一张图片上的删除选项被选中,删除所述图片;
    如果检测到所述图片上的保存选项被选中,保存所述图片。
  4. 根据权利要求3所述的方法,其中,所述删除所述图片之后,还包括:
    向服务器发送删除指令,所述删除指令用于指示所述服务器在云存储空间中删除所述图片。
  5. 根据权利要求1所述的方法,其中,所述方法还包括:
    在存储空间清理页面上显示图片清理选项;
    当检测到所述图片清理选项被选中,执行扫描图片目录下的所有图片。
  6. 一种图片处理装置,所述装置包括:
    扫描模块,配置为在清理存储空间的过程中,扫描图片目录下的所有图片;
    相似图片组生成模块,配置为根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;
    第一显示模块,配置为按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中的图片;
    处理模块,配置为根据检测到的操作对每个相似图片组中的图片进行处理。
  7. 根据权利要求6所述的装置,其中,所述图片特征包括全局特征和局部特征;
    所述相似图片组生成模块,配置为根据图片的属性信息,将图片目录下的图片划分为不同的图片组,每个图片组至少包含两张图片;对于 任一图片组,计算任意两张图片的全局特征的相似度以及局部特征的相似度;当所述全局特征的相似度大于第一阈值,且所述局部特征的相似度大于第二阈值,对所述全局特征的相似度和所述局部特征的相似度进行加权计算,得到加权计算结果;当所述加权计算结果大于第三阈值,则将所述两张图片作为相似图片;将所述图片组中与同一张图片互为相似图片的所有图片组成一个相似图片组。
  8. 根据权利要求6所述的装置,其中,所述处理装置,配置为在每个相似图片组的每张图片上显示保存选项和删除选项;当检测到任一张图片上的删除选项被选中,删除所述图片;当检测到所述图片上的保存选项被选中,保存所述图片。
  9. 根据权利要求8所述的装置,其中,所述装置还包括:
    发送模块,配置为向服务器发送删除指令,所述删除指令用于指示所述服务器在云存储空间中删除所述图片。
  10. 根据权利要求6所述的装置,其中,所述装置还包括:
    第二显示模块,配置为在存储空间清理页面上显示图片清理选项;
    所述扫描模块,配置为当检测到所述图片清理选项被选中,执行扫描图片目录下的所有图片。
  11. 一种图片处理装置,包括:
    处理器;
    配置为存储处理器可执行的指令的存储器;
    其中,所述处理器被配置为:
    在清理存储空间的过程中,扫描图片目录下的所有图片;
    根据每张图片的属性信息及预先提取的图片特征,生成至少一个相似图片组,所述属性信息至少包括拍摄时间;
    按照拍摄时间顺序,以相似图片组为单位,显示每个相似图片组中 的图片;
    根据检测到的操作对每个相似图片组中的图片进行处理。
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