WO2018191889A1 - 照片处理方法、装置及计算机设备 - Google Patents

照片处理方法、装置及计算机设备 Download PDF

Info

Publication number
WO2018191889A1
WO2018191889A1 PCT/CN2017/081100 CN2017081100W WO2018191889A1 WO 2018191889 A1 WO2018191889 A1 WO 2018191889A1 CN 2017081100 W CN2017081100 W CN 2017081100W WO 2018191889 A1 WO2018191889 A1 WO 2018191889A1
Authority
WO
WIPO (PCT)
Prior art keywords
photo
photos
storage order
album
matching degree
Prior art date
Application number
PCT/CN2017/081100
Other languages
English (en)
French (fr)
Inventor
梁昆
Original Assignee
广东欧珀移动通信有限公司
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 广东欧珀移动通信有限公司 filed Critical 广东欧珀移动通信有限公司
Priority to EP17906536.2A priority Critical patent/EP3611629A4/en
Priority to US16/605,468 priority patent/US11429660B2/en
Priority to PCT/CN2017/081100 priority patent/WO2018191889A1/zh
Priority to CN201780087001.6A priority patent/CN110313001A/zh
Publication of WO2018191889A1 publication Critical patent/WO2018191889A1/zh

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures 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
    • 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
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10File systems; File servers
    • G06F16/13File access structures, e.g. distributed indices
    • G06F16/137Hash-based
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10File systems; File servers
    • G06F16/16File or folder operations, e.g. details of user interfaces specifically adapted to file systems
    • G06F16/162Delete operations
    • 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
    • G06F16/51Indexing; Data structures therefor; Storage structures
    • 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
    • G06F16/5854Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using shape and object relationship
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures

Definitions

  • the invention belongs to the technical field of picture processing, and in particular relates to a photo processing method, device and computer device.
  • the embodiment of the invention provides a photo processing method, device and computer device, which can improve the efficiency of finding photos.
  • An embodiment of the present invention provides a photo processing method, including:
  • the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold
  • at least one aggregate folder is generated, and each of the aggregate folders is used for the aggregation storage order and the matching degree is greater than Or a photo equal to the preset threshold.
  • An embodiment of the present invention provides a photo processing apparatus, including:
  • the obtaining module is configured to obtain feature information of multiple photos in the album
  • a detecting module configured to perform matching degree detection on each adjacent two photos according to the preset photo storage order according to the feature information
  • a generating module configured to generate at least one aggregated folder, if each of the aggregated folders is used to aggregate the storage order, if it is detected that the photo album includes a photo in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold A photo that is continuous and has a matching degree greater than or equal to a preset threshold.
  • Embodiments of the present invention provide a computer device including a memory, a processor, and a computer program stored in the memory and operable in the processor, and the processor implements the following steps when executing the computer program:
  • the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold
  • at least one aggregate folder is generated, and each of the aggregate folders is used for the aggregation storage order and the matching degree is greater than Or a photo equal to the preset threshold.
  • the embodiment of the invention provides a photo processing method, device and computer device, which can improve the efficiency of finding photos.
  • FIG. 1 is a schematic flowchart diagram of a photo processing method according to an embodiment of the present invention.
  • FIG. 2 is a schematic diagram of labeling each photo in an album in a photo processing method according to an embodiment of the present invention.
  • FIG. 3 is another schematic flowchart of a photo processing method according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a scenario of a photo processing method according to an embodiment of the present invention.
  • FIG. 12 is a schematic structural diagram of a photo processing apparatus according to an embodiment of the present invention.
  • FIG. 13 is another schematic structural diagram of a photo processing apparatus according to an embodiment of the present invention.
  • FIG. 14 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention.
  • FIG. 1 is a schematic flowchart of a photo processing method according to an embodiment of the present invention.
  • the process may include:
  • step S101 feature information of a plurality of photos in the album is acquired.
  • the execution subject of the embodiment of the present invention may be a terminal device such as a smart phone or a tablet computer.
  • the terminal may first acquire feature information of each photo in the album including multiple photos.
  • the terminal may calculate a hash value of each photo in the album by using a perceptual hash algorithm, and determine a hash value of each photo as the feature information of the corresponding photo.
  • the perceptual hash algorithm (Perceptual Hash) Algorithm) is a class of hash algorithms, mainly used for searching similar pictures. By performing a computational processing on the image through a perceptual hash algorithm, a hash value can be obtained, which is a 64-bit integer that can be used to represent the feature information of the image.
  • the two hash values can be compared to detect how many bits of the hash values of the two 64-bit integers are the same. For example, if the same data bit of two hash values reaches 55 bits, then the two photos can be considered similar pictures. Otherwise, you can think that these two photos are not similar pictures.
  • step S102 according to the feature information, the matching degree detection is performed on each of the adjacent two photos according to the preset photo storage order.
  • the terminal may follow the preset photo storage order according to the feature information of each photo. Two photos are tested for matching.
  • the terminal may perform matching detection on each of the adjacent two photos in accordance with the storage order based on the shooting time.
  • the photos in the album are stored in a back-to-first order according to the shooting time, that is, the first photo in the album is the photo closest to the current time, and the last photo is taken earlier than the other in the album. photo.
  • the terminal can start from the first and second photos of the album, and sequentially check the matching degree of the adjacent photos. If the matching degree of two photos adjacent in the storage order is greater than or equal to a preset threshold, the corresponding two photos may be considered as similar photos. If the matching degree of two photos adjacent in the storage order is less than a preset threshold, it can be considered that the corresponding two photos are not similar photos.
  • step S103 if it is detected that the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, at least one aggregate folder is generated, and each aggregate folder is used for the aggregation and the storage order is continuous and matched. A photo with a degree greater than or equal to the preset threshold.
  • the terminal detects that the album contains photos that are adjacent in the storage order and whose matching degree is greater than or equal to a preset threshold. That is to say, the terminal detects that the album contains similar photos in the storage order, and the terminal can generate at least one aggregate folder, and each aggregate folder can be used to aggregate similar photos in the storage order. That is, the photos aggregated in each aggregate folder are similar photos that are consecutive in the storage order.
  • the terminal when the terminal detects that the album includes similar photos in the storage order, the terminal may sequentially determine whether to mark each two photos adjacent to the storage order according to a preset photo storage order. Same identification information. Wherein, each photo is allowed to be marked once, and the photos corresponding to the same identification information are consecutive in the storage order. In other words, after each photo has been marked once, it cannot be marked a second time. If the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the terminal may label the corresponding two photos with the same identification information. If the storage order is adjacent and the matching degree is less than a preset threshold, the terminal may label different photos with different identification information.
  • the terminal performs the matching degree detection on each two photos adjacent in the storage order, it is detected that the matching degree of the photo A and the photo B is not less than a preset threshold, and the matching degree of the photo B and the photo C is less than a preset threshold, the photo C
  • the matching degree with the photo D is not less than the preset threshold
  • the matching degree of the photo D and the photo E is not less than the preset threshold
  • the matching degree of the photo E and the photo F is less than the preset threshold
  • the matching degree of the photo F and the photo G is less than the preset.
  • the matching degree of the threshold, the photo G and the photo H is less than a preset threshold
  • the matching degree of the photo H and the photo I is not less than a preset threshold
  • the matching degree of the photo I and the photo J is not less than a preset threshold.
  • the terminal can mark the photos in the album in order from the photo A and the photo B according to the storage order. For example, since the matching degree of the photo A and the photo B is not less than the preset threshold, the terminal may mark the same identification information for the photo A and the photo B, for example, the labeled identification information is the number “1”.
  • the terminal can mark the photo C with the identification information different from the photo B. For example, since the photo B already has the identification information “1”, the photo C can be marked as a number “ 2".
  • the terminal can mark the photo D as the number "2". Similarly, the terminal can also mark the photo E as the number "2".
  • the terminal can mark the photo F with the identification information different from the photo E, for example, the photo F is marked as the number "3". Similarly, the terminal can mark the photo G as the number "4". Similarly, the terminal can mark the photo H as the number "5".
  • the terminal can mark the photo I as the number "5". Similarly, the terminal can mark the photo J as the number "5".
  • the terminal can generate three aggregate folders to aggregate the photos with the same identification information.
  • the terminal may generate a first aggregate folder, a second aggregate folder, and a third aggregate folder.
  • the first aggregation folder aggregates the photo A and the photo B whose identification information is “1”, that is, the first aggregate folder includes the photo A and the photo B.
  • the second aggregate folder aggregates the photo C, the photo D, and the photo E whose identification information is "2".
  • the third aggregate folder aggregates the photo H, the photo I, and the photo J whose identification information is "5".
  • the present embodiment can aggregate similar photos that are adjacent in the storage order and form corresponding aggregate folders. Therefore, the embodiment can improve the simplicity of the album, thereby improving the efficiency of the user in finding photos.
  • FIG. 3 is another schematic flowchart of a photo processing method according to an embodiment of the present disclosure, where the process may include:
  • step S201 the terminal acquires feature information of a plurality of photos in the album.
  • the terminal may first obtain feature information of each photo in an album containing multiple photos.
  • the terminal may calculate a hash value of each photo in the album by using a perceptual hash algorithm, and determine a hash value of each photo as the feature information of the corresponding photo.
  • the perceptual hash algorithm is a class of hash algorithms and is mainly used for searching similar pictures.
  • a hash value can be obtained, which is a 64-bit integer that can be used to represent the feature information of the image.
  • the two hash values can be compared to detect how many bits of the hash values of the two 64-bit integers are the same. For example, if the same data bit of two hash values reaches 55 bits, then the two photos can be considered similar pictures. Otherwise, you can think that these two photos are not similar pictures.
  • step S202 based on the feature information, the terminal performs matching degree detection on each of the adjacent two photos in accordance with the storage order based on the shooting time.
  • the terminal may, according to the feature information of each photo, according to the storage order based on the shooting time, Two photos are tested for matching.
  • the photos in the album are stored in a back-to-first order according to the shooting time, that is, the first photo in the album is the photo closest to the current time, and the last photo is taken earlier than the other in the album. photo.
  • the terminal can start from the first and second photos of the album, and sequentially check the matching degree of each of the adjacent two photos. If the matching degree of two photos adjacent in the storage order is greater than or equal to a preset threshold, the corresponding two photos may be considered as similar photos. If the matching degree of two photos adjacent in the storage order is less than a preset threshold, it can be considered that the corresponding two photos are not similar photos.
  • step S203 if it is detected that the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the terminal sequentially determines, according to the storage order, whether to mark the same identifier for each two photos adjacent to the storage order. Information, in which each photo is allowed to be marked once, and the photos corresponding to the same identification information are consecutive in the storage order.
  • step S204 if the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the terminal labels the corresponding two photos with the same identification information; if the storage order is adjacent and the matching degree is less than the preset threshold, the terminal pairs The corresponding two photos are marked with different identification information.
  • steps S203 and S204 may include:
  • the terminal may sequentially determine whether to mark the same identification information for each two photos adjacent to the storage order according to the storage order based on the shooting time. Wherein, each photo is allowed to be marked once, and the photos corresponding to the same identification information are consecutive in the storage order. In other words, after each photo has been marked once, it cannot be marked a second time. If the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the terminal may label the corresponding two photos with the same identification information. If the storage order is adjacent and the matching degree is less than a preset threshold, the terminal may label different photos with different identification information.
  • the terminal performs the matching degree detection on each two photos adjacent in the storage order, it is detected that the matching degree of the photo A and the photo B is not less than a preset threshold, and the matching degree of the photo B and the photo C is less than a preset threshold, the photo C
  • the matching degree with the photo D is not less than the preset threshold
  • the matching degree of the photo D and the photo E is not less than the preset threshold
  • the matching degree of the photo E and the photo F is less than the preset threshold
  • the matching degree of the photo F and the photo G is less than the preset.
  • the matching degree of the threshold, the photo G and the photo H is less than a preset threshold
  • the matching degree of the photo H and the photo I is not less than a preset threshold
  • the matching degree of the photo I and the photo J is not less than a preset threshold.
  • the terminal can mark the photo in the album in order from the photo A and the photo B according to the storage order. For example, since the matching degree of the photo A and the photo B is not less than the preset threshold, the terminal may mark the same identification information for the photo A and the photo B, for example, the labeled identification information is the number “1”.
  • the terminal can mark the photo C with the identification information different from the photo B. For example, since the photo B already has the identification information “1”, the photo C can be marked as a number “ 2".
  • the terminal can mark the photo D as the number "2". Similarly, the terminal can also mark the photo E as the number "2".
  • the terminal can mark the photo F with the identification information different from the photo E, for example, the photo F is marked as the number "3". Similarly, the terminal can mark the photo G as the number "4". Similarly, the terminal can mark the photo H as the number "5".
  • the terminal can mark the photo I as the number "5". Similarly, the terminal can mark the photo J as the number "5".
  • step S205 the terminal respectively aggregates the photos with the same identification information to generate at least one aggregated folder, and the plurality of photos in the album remain unchanged based on the storage order of the shooting time.
  • the terminal may aggregate the photos with the same identification information and generate at least one aggregate folder.
  • the terminal can generate three aggregate folders to aggregate the photos with the same identification information.
  • the terminal may generate a first aggregate folder, a second aggregate folder, and a third aggregate folder.
  • the first aggregation folder aggregates the photo A and the photo B whose identification information is “1”, that is, the first aggregate folder includes the photo A and the photo B.
  • the second aggregate folder aggregates the photo C, the photo D, and the photo E whose identification information is "2".
  • the third aggregate folder aggregates the photo H, the photo I, and the photo J whose identification information is "5".
  • all the photos in the terminal album may remain unchanged based on the storage order of the shooting time.
  • the photos A to J in the album are stored in the order of shooting time. For example, Photo A is taken later than all other photos, ranking first in the album. Photo B is taken earlier than Photo A, but other photos outside Photo A are ranked second in the album. Photo J was taken earlier than all other photos, ranking the last one in the album.
  • the order of storing the photos A to J based on the shooting time in the album may remain unchanged. That is, in the album, the first aggregated folder is ranked first, and in the first aggregated folder, the photo A is placed before the photo B.
  • the second aggregate folder is ranked second, in the second aggregate folder, the photo C is placed before the photo D, and the photo D is placed before the photo E.
  • Photographs F and G are ranked third and fourth respectively.
  • the third aggregate folder is ranked fifth, in the third aggregate file, the photo H is placed before the photo I, and the photo I is placed before the photo J. That is to say, after the photo aggregation, the photos in the album are still arranged in the order in which the photos A to J are stored.
  • the terminal may label the aggregate folder according to the identification information of the photo included in each aggregate folder. For example, the terminal may label the first aggregate folder according to the number “1”, mark the second aggregate folder according to the number “2”, and mark the third aggregate folder according to the number “5”.
  • the terminal can sort and store the aggregated folders in the album and the photos that are not aggregated with other photos in the order of the numbers from small to large.
  • the terminal may store the first aggregated folder (the identification information is the number "1") in the first place of the album, and the second aggregated folder (the identification information is the number "2") in the second place of the album.
  • the photo F (identification information is the number "3") is stored in the third place
  • the photo G (the identification information is the number "4") is stored in the fourth place
  • the third aggregated folder (the identification information is the number "5") Stored in the fifth place in the album.
  • the terminal can sort and store the photos included in each aggregate folder according to the shooting time.
  • the photo C, the photo D, and the photo E are aggregated, and in this aggregate folder, the terminal can sort and store the photo C, the photo D, and the photo E according to the shooting time.
  • the photo C is stored in the first place in the order of the shooting time from the back to the first
  • the photo D is stored in the second place
  • the photo E is stored in the third place. That is to say, before the aggregation, the photo C is arranged before the photo D, and the photo D is placed before the photo E, then after the three photos are aggregated, the three photos can still be sorted according to the shooting time. Make photo C still ahead of photo D, which is still in front of photo E.
  • step S206 the terminal sets the first photo in each aggregated folder as the cover of the aggregated folder in the order of shooting time.
  • the terminal may set the content of the first photo in each aggregate folder as the cover of the aggregate folder for the user to view. .
  • the terminal may set the content of the photo C ranked in the first place as the cover of the second aggregate folder. In this way, when viewing the album, the user can know that the second aggregate folder contains a plurality of pictures similar to the photo C.
  • the photos in the album when the photos in the album are not aggregated, the photos are sorted according to the storage order based on the shooting time. For example, ten photos in an album are sequentially stored as photos A, B, C, D, E, F, G, H, I, J in order of shooting time from first to last. After the similar photos in the album are aggregated and sorted according to certain rules, the order of storage in the album is the first aggregate folder (including photos A, B) and the second aggregate folder (including photo C). , D, E), photo F, photo G, third aggregate folder (including photos H, I, J). Therefore, the relative position of each photo on the time axis in the album does not change. For example, the order in which the photos B are stored in the album is still ranked before the photo C, and the photo G is still placed before the photo H.
  • the present embodiment can improve the simplicity of the album and improve the photo search by aggregating similar photos in the storage order and all the photos in the album remain unchanged based on the storage order of the shooting time.
  • Efficiency ensures that the position of each photo on the timeline of the album does not change, ie does not destroy the timeline of the album.
  • the photos that are aggregated are similar photos, it is convenient for the user to accurately find an approximate photograph taken in several adjacent shots.
  • the photo processing method provided by the embodiment of the present invention may further include the following steps:
  • the terminal When it is detected that the number of photos in the aggregate folder is zero, the terminal deletes the corresponding aggregate folder.
  • the terminal detects that the number of photos in the second aggregate folder changes from three to zero, then the second aggregate folder is It became an empty folder. In this case, the terminal can delete the second aggregate folder.
  • the simplicity of the album can be further improved by deleting the aggregated folder with zero photos.
  • FIG. 4 to FIG. 11 are schematic diagrams of scenarios of a photo processing method according to an embodiment of the present invention.
  • the terminal album contains ten photos, followed by photo A to photo J.
  • the ten photos are stored in the album in the order of the shooting time, that is, the shooting time of the photo A is later than the other photos, and the shooting time of the photo J is earlier than other photos.
  • the interface of the album is shown in Figure 4.
  • the terminal may first obtain the feature information of the photo A to the photo J, and then according to the feature information of the photos, according to the storage order of the shooting time from the back to the first, starting from the photo A and the photo B, sequentially adjacent to each of the storage order A photo is taken for matching detection.
  • the terminal detects that the matching degree of the photo A and the photo B is not less than a preset threshold, the matching degree of the photo B and the photo C is less than a preset threshold, and the matching degree of the photo C and the photo D is not less than a preset threshold.
  • the matching degree between the photo D and the photo E is not less than the preset threshold
  • the matching degree of the photo E and the photo F is less than the preset threshold
  • the matching degree of the photo F and the photo G is less than the preset threshold
  • the matching degree of the photo G and the photo H is smaller than
  • the preset threshold, the matching degree of the photo H and the photo I is not less than a preset threshold
  • the matching degree of the photo I and the photo J is not less than a preset threshold.
  • the terminal can sequentially determine, from the photo A and the photo B, whether each of the two photos adjacent to the storage order in the album needs to be labeled with the same identification information according to the storage order. Wherein, each photo is allowed to be marked once, and the photos corresponding to the same identification information are consecutive in the storage order. In other words, after each photo has been marked once, it cannot be marked a second time. If the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the terminal may label the corresponding two photos with the same identification information. If the storage order is adjacent and the matching degree is less than a preset threshold, the terminal may label different photos with different identification information.
  • the terminal may mark the same identification information for the photo A and the photo B, for example, the labeled identification information is the number “1”.
  • the terminal can mark the photo C with the identification information different from the photo B. For example, since the photo B already has the identification information “1”, the photo C can be marked as a number “ 2".
  • the terminal can mark the photo D as the number "2". Similarly, the terminal can also mark the photo E as the number "2".
  • the terminal can mark the photo F with the identification information different from the photo E, for example, the photo F is marked as the number "3". Similarly, the terminal can mark the photo G as the number "4". Similarly, the terminal can mark the photo H as the number "5".
  • the terminal can mark the photo I as the number "5". Similarly, the terminal can mark the photo J as the number "5".
  • the terminal can generate three aggregate folders, and respectively aggregate the photos with the same identification information.
  • the terminal may generate a first aggregate folder, a second aggregate folder, and a third aggregate folder.
  • the first aggregation folder aggregates the photo A and the photo B whose identification information is “1”, that is, the first aggregate folder includes the photo A and the photo B.
  • the second aggregate folder aggregates the photo C, the photo D, and the photo E whose identification information is "2".
  • the third aggregate folder aggregates the photo H, the photo I, and the photo J whose identification information is "5".
  • the terminal can sort and store the photos contained in the aggregate folder in a back-to-first order according to the shooting time. For example, in the first aggregated folder, since the photographing time of the photo A is later than the photo B, the photo A is stored before the photo B. Similarly, in the second aggregate folder, the photo C is stored before the photo D, and the photo D is stored before the photo E. In the third aggregate folder, the photo H is stored in front of the photo I, and the photo I is stored in front of the photo J.
  • the terminal can also mark the aggregate folder according to the identification information of the photo included in each aggregate folder. For example, the terminal may label the first aggregate folder according to the number “1”, mark the second aggregate folder according to the number “2”, and mark the third aggregate folder according to the number “5”.
  • the terminal can sort and store the aggregated files in the album and the files that are not aggregated with other photos in the order of the numbers from small to large.
  • the terminal may store the first aggregate folder (the identification information is the number "1") in the first place of the album, and the second aggregate file (the identification information is the number "2") in the second position of the album,
  • the photo F (the identification information is the number "3") is stored in the third place
  • the photo G (the identification information is the number "4") is stored in the fourth place
  • the third aggregated file (the identification information is the number "5") is stored.
  • the album interface can be as shown in FIG. 5. Comparing Fig. 4 with Fig. 5, the album becomes more concise after the aggregation of similar photos.
  • the relative positions of the photos on the time axis do not change, so that the user can still find the pictures in the album in chronological order, that is, the user's habit of finding photos. Can be retained.
  • the photo B is stored before the photo C
  • the photo B is still stored before the photo C.
  • the user deletes the photo I and the photo J in the third aggregated folder, then only the photo H remains in the third aggregated file, as shown in FIG.
  • the terminal can extract the photo H from the third aggregated folder and store it in the terminal album in the order based on the shooting time. For example, since the photographing time of the photograph H is earlier than the photograph G, the photograph H can be stored after the photograph G.
  • the terminal can delete the third aggregate file with the number of photos is zero, and the interface of the terminal album can be as shown in FIG.
  • FIG. 12 is a schematic structural diagram of a photo processing apparatus according to an embodiment of the present invention.
  • the photo processing apparatus 300 may include an acquisition module 301, a detection module 302, and a generation module 303.
  • the obtaining module 301 is configured to acquire feature information of multiple photos in the album.
  • the acquiring module 301 of the terminal may first acquire feature information of each photo in the album including multiple photos.
  • the obtaining module 301 may calculate a hash value of each photo in the album by using a perceptual hash algorithm, and determine a hash value of each photo as the feature information of the corresponding photo.
  • the perceptual hash algorithm is a class of hash algorithms and is mainly used for searching similar pictures.
  • a hash value can be obtained, which is a 64-bit integer that can be used to represent the feature information of the image.
  • the two hash values can be compared to detect how many bits of the hash values of the two 64-bit integers are the same. For example, if the same data bit of two hash values reaches 55 bits, then the two photos can be considered similar pictures. Otherwise, you can think that these two photos are not similar pictures.
  • the detecting module 302 is configured to perform matching degree detection on each adjacent two photos according to the preset photo storage order according to the feature information.
  • the detecting module 302 may follow the feature information of each photo according to the feature information of each photo.
  • the preset photo storage order is used to check the matching degree of each adjacent photo.
  • the detection module 302 can perform the matching degree detection on each of the adjacent two photos according to the storage order based on the shooting time.
  • the photos in the album are stored in a back-to-first order according to the shooting time, that is, the first photo in the album is the photo closest to the current time, and the last photo is taken earlier than the other in the album. photo.
  • the detection module 302 can sequentially detect the matching degree of the adjacent photos starting from the first and second photos of the album. If the matching degree of two photos adjacent in the storage order is greater than or equal to a preset threshold, the corresponding two photos may be considered as similar photos. If the matching degree of two photos adjacent in the storage order is less than a preset threshold, it can be considered that the corresponding two photos are not similar photos.
  • the generating module 303 is configured to generate, if the photo album includes a photo in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold, generating at least one aggregate folder, where each of the aggregate folders is used to aggregate the storage order A photo that is continuous and has a matching degree greater than or equal to a preset threshold.
  • the detecting module 302 detects that the photo album includes photographs that are adjacent in the storage order and whose matching degree is greater than or equal to a preset threshold. That is to say, the detecting module 302 detects that the album contains similar photos in the storage order, and then the generating module 303 can generate at least one aggregate folder, and each of the aggregate folders can be used to aggregate the sequential similarities in the storage order. photo. That is, the photos aggregated in each aggregate folder are similar photos that are consecutive in the storage order.
  • the generation module 303 can be used to:
  • the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold, sequentially determining, according to the storage order, whether to mark the same identification information for each two photos adjacent to the storage order, where each A photo is allowed to be marked once, and the photo corresponding to the same identification information is consecutive in the storage order;
  • the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the corresponding two photos are marked with the same identification information;
  • the storage order is adjacent and the matching degree is less than a preset threshold, the corresponding two photos are marked with different identification information;
  • the photos with the same identification information are respectively aggregated to generate at least one aggregate folder.
  • the generating module 303 may sequentially determine whether each of the storage orders is adjacent according to the preset photo storage order. Two photos are labeled with the same identification information. Wherein, each photo is allowed to be marked once, and the photos corresponding to the same identification information are consecutive in the storage order. In other words, after each photo has been marked once, it cannot be marked a second time. If the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the generating module 303 may label the corresponding two photos with the same identification information. If the storage order is adjacent and the matching degree is less than the preset threshold, the generating module 303 may label the corresponding two photos with different identification information.
  • the detection module 302 performs the matching degree detection on each of the two photos adjacent in the storage order, it is detected that the matching degree of the photo A and the photo B is not less than a preset threshold, and the matching degree of the photo B and the photo C is less than a preset threshold.
  • the matching degree between the photo C and the photo D is not less than the preset threshold
  • the matching degree of the photo D and the photo E is not less than the preset threshold
  • the matching degree of the photo E and the photo F is less than the preset threshold
  • the matching degree of the photo F and the photo G is smaller than
  • the preset threshold, the matching degree of the photo G and the photo H is less than the preset threshold
  • the matching degree of the photo H and the photo I is not less than the preset threshold
  • the matching degree of the photo I and the photo J is not less than the preset threshold.
  • the generating module 303 may sequentially mark the photos in the album from the photo A and the photo B according to the storage order, so that the identification information of the photos whose storage order is adjacent and the matching degree is greater than or equal to the preset threshold is the same. And the identification information of the photos in which the storage order is adjacent and the matching degree is less than the preset threshold is different. At the same time, each photo is only run once, and the same identification information is that the corresponding photos are consecutive in the storage order.
  • the generating module 303 may mark the same identification information for the photo A and the photo B, for example, the labeled identification information is the number “1”.
  • the generating module 303 can mark the photo C with the identification information different from the photo B, for example, since the photo B already has the identification information “1”, the photo C can be marked as The number "2".
  • the generating module 303 can mark the photo D as the number "2". Similarly, the generation module 303 can also mark the photo E as the number "2".
  • the generating module 303 can mark the photo F with the identification information different from the photo E, for example, the photo F as the number "3". Similarly, the generation module 303 can mark the photo G as the number "4". Similarly, the generation module 303 can mark the photo H as the number "5".
  • the generating module 303 can mark the photo I as the number "5". Similarly, the generation module 303 can mark the photo J as the number "5".
  • the generating module 303 can generate three aggregate folders, and respectively aggregate the photos with the same identification information.
  • the generation module 303 can generate a first aggregate folder, a second aggregate folder, and a third aggregate folder.
  • the first aggregation folder aggregates the photo A and the photo B whose identification information is “1”, that is, the first aggregate folder includes the photo A and the photo B.
  • the second aggregate folder aggregates the photo C, the photo D, and the photo E whose identification information is "2".
  • the third aggregate folder aggregates the photo H, the photo I, and the photo J whose identification information is "5".
  • the generating module 303 can be used to:
  • At least one aggregate folder is generated, and the order in which the plurality of photos in the album are stored remains unchanged.
  • the generation module 303 can control the storage order of all the photos in the album based on the shooting time to remain unchanged.
  • the photos A to J in the album are stored in the order of shooting time. For example, Photo A is taken later than all other photos, ranking first in the album. Photo B is taken earlier than Photo A, but other photos outside Photo A are ranked second in the album. Photo J was taken earlier than all other photos, ranking the last one in the album.
  • the order of storing the photos A to J in the album based on the shooting time remains unchanged. That is, in the album, the first aggregated folder is ranked first, and in the first aggregated folder, the photo A is placed before the photo B.
  • the second aggregate folder is ranked second, in the second aggregate folder, the photo C is placed before the photo D, and the photo D is placed before the photo E.
  • Photographs F and G are ranked third and fourth respectively.
  • the third aggregate folder is ranked fifth, in the third aggregate file, the photo H is placed before the photo I, and the photo I is placed before the photo J. That is to say, after the photo aggregation, the photos in the album are still arranged in the order in which the photos A to J are stored.
  • the detection module 302 can be configured to perform matching detection on each of two adjacent photos in accordance with a storage order based on the shooting time.
  • the generating module 303 can be configured to: generate at least one aggregate folder, and the plurality of photos in the album remain unchanged based on a storage order of the shooting time.
  • the generating module 303 can label the aggregate folder according to the identification information of the photo included in each aggregate folder. For example, the generating module 303 may label the first aggregated folder according to the number “1”, mark the second aggregated folder according to the number “2”, and mark the third aggregated folder according to the number “5”.
  • the generating module 303 can sort and store the aggregated folders in the album and the photos that are not aggregated with other photos in the order of the numbers from small to large.
  • the generating module 303 may store the first aggregate folder (the identification information is the number "1") in the first place of the album, and the second aggregate folder (the identification information is the number "2") in the second album.
  • the photo F (identification information is the number "3") is stored in the third place
  • the photo G (the identification information is the number "4") is stored in the fourth place
  • the third aggregated folder (the identification information is the number " 5") is stored in the fifth place of the album.
  • the generating module 303 can sort and store the photos included in each of the aggregated folders according to the shooting time. For example, in the second aggregate folder, the photo C, the photo D, and the photo E are aggregated, and in this aggregate folder, the generation module 303 can sort and store the photo C, the photo D, and the photo E according to the shooting time. For example, the photo C is stored in the first place in the order of the shooting time from the back to the first, the photo D is stored in the second place, and the photo E is stored in the third place.
  • the photo C is arranged before the photo D, and the photo D is arranged before the photo E, then after the three photos are aggregated, the three photos can be sorted so that the photo C is still arranged. Before the photo D, the photo D is still placed before the photo E.
  • FIG. 13 is another schematic structural diagram of a photo processing apparatus according to an embodiment of the present invention.
  • the photo processing apparatus 300 may further include: a deleting module 304, and a setting module 305.
  • the deleting module 304 is configured to delete the corresponding aggregate folder when the number of photos in the aggregate folder is detected to be zero.
  • the deletion module 304 can delete the second aggregate folder.
  • the simplicity of the album can be further improved by deleting the aggregated folder with zero photos.
  • the setting module 305 is configured to set the first photo in each of the aggregated folders as the cover of the aggregated folder according to the order of shooting time.
  • the setting module 305 can set the content of the photo C stored in the first place as the cover of the second aggregate folder. In this way, when viewing the album, the user can know that the second aggregate folder contains a plurality of pictures similar to the photo C.
  • Embodiments of the present invention also provide a computer device, which may include a memory, a processor, and a computer program stored in the memory and operable in the processor, the processor executing the computer program
  • a computer device which may include a memory, a processor, and a computer program stored in the memory and operable in the processor, the processor executing the computer program
  • the computer device may be a mobile terminal such as a tablet computer or a smart phone.
  • FIG. 14 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention.
  • the mobile terminal 500 can include a memory 501 having one or more computer readable storage media, an input unit 502, a display unit 503, a processor 504 including one or more processing cores, a sensor 505, and a power source 506.
  • a memory 501 having one or more computer readable storage media
  • an input unit 502 a display unit 503, a processor 504 including one or more processing cores, a sensor 505, and a power source 506.
  • the mobile terminal structure shown in FIG. 14 does not constitute a limitation of the mobile terminal, and may include more or less components than those illustrated, or combine some components, or different component arrangements.
  • Memory 501 can be used to store applications and data.
  • the application stored in the memory 501 contains executable code.
  • Applications can form various functional modules.
  • the processor 504 executes various functional applications and data processing by running an application stored in the memory 501.
  • the input unit 502 can be configured to receive input numbers, character information or user characteristic information (such as fingerprints), and to generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.
  • user characteristic information such as fingerprints
  • Display unit 503 can be used to display information entered by the user or information provided to the user as well as various graphical user interfaces of the mobile terminal, which can be composed of graphics, text, icons, video, and any combination thereof.
  • the display unit 504 can include a display panel.
  • the processor 504 is a control center of the mobile terminal, and connects various parts of the entire mobile terminal by using various interfaces and lines, and executes the mobile terminal by running or executing an application stored in the memory 501 and calling data stored in the memory 501.
  • the mobile terminal may also include at least one type of sensor 505, such as a light sensor, a gyro sensor, and other sensors.
  • sensor 505 such as a light sensor, a gyro sensor, and other sensors.
  • the mobile terminal can also include a power source 506 (such as a battery, etc.) that powers the various components.
  • a power source 506 such as a battery, etc.
  • the mobile terminal may further include a camera, a Bluetooth module, and the like, and details are not described herein again.
  • the processor 504 in the mobile terminal loads the computer program corresponding to the process of one or more applications into the memory 501 according to the following instruction, and is stored in the memory 501 by the processor 504.
  • the following steps are implemented:
  • the photo album includes photos in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold
  • at least one aggregate folder is generated, and each of the aggregate folders is used for the aggregation storage order and the matching degree is greater than Or a photo equal to the preset threshold.
  • the processor 504 when performing the generating the at least one aggregated folder, may implement the step of generating at least one aggregated folder, and the storage order of the plurality of photos in the album remains unchanged.
  • the processor 504 may perform the following steps: when detecting that the photo album includes a photo in which the storage order is adjacent and the matching degree is greater than or equal to a preset threshold, and at least one aggregate folder is generated, if the If the photo album includes photographs whose storage order is adjacent and the matching degree is greater than or equal to the preset threshold, then according to the storage order, it is sequentially determined whether to mark the same identification information for each two photos adjacent to the storage order, wherein each photo is allowed to be marked once.
  • the photos corresponding to the same identification information are consecutive in the storage order; if the storage order is adjacent and the matching degree is greater than or equal to the preset threshold, the corresponding two photos are marked with the same identification information; if the storage order is adjacent and matched If the degree is less than the preset threshold, the corresponding two photos are marked with different identification information; the photos with the same identification information are respectively aggregated to generate at least one aggregate folder.
  • the processor 504 when performing the matching degree detection on each of the adjacent two photos according to the preset photo storage order, may implement the following steps: performing each of the adjacent two photos according to the storage order based on the shooting time. Matching detection. While the processor 504 is performing the generating of the at least one aggregate folder, and the storage order of the plurality of photos in the album remains unchanged, the following steps are implemented: generating at least one aggregate folder, and multiple photos in the album The storage order based on the shooting time remains unchanged.
  • the processor 504 executes the computer program, the following steps may also be implemented: when it is detected that the number of photos in the aggregate folder is zero, the corresponding aggregate folder is deleted.
  • the following steps may be further implemented: setting the first photo in each of the aggregated folders as the cover of the aggregated folder in the order of shooting time.
  • the processor 504 when the processor 504 performs the acquiring feature information of multiple photos in an album, the following steps may be implemented: acquiring a hash value of multiple photos in the album by using a perceptual hash algorithm, and The hash value is determined as the feature information of the photo.
  • the photo processing apparatus provided by the embodiment of the present invention is the same as the photo processing method in the above embodiment, and any method provided in the embodiment of the photo processing method may be run on the photo processing apparatus, and the specific For details of the implementation process, refer to the embodiment of the photo processing method, and details are not described herein again.
  • the computer program can be stored in a computer readable storage medium, such as in a memory, and executed by at least one processor, and can include a flow of an embodiment of the photo processing method during execution.
  • the storage medium may be a magnetic disk, an optical disk, a read only memory (ROM, Read) Only Memory), random access memory (RAM, Random Access Memory), etc.
  • each functional module may be integrated into one processing chip, or each module may exist physically separately, or two or more modules may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated module if implemented in the form of a software functional module and sold or used as a standalone product, may also be stored in a computer readable storage medium, such as a read only memory, a magnetic disk or an optical disk, etc. .

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Library & Information Science (AREA)
  • Software Systems (AREA)
  • Human Computer Interaction (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Processing Or Creating Images (AREA)
  • Television Signal Processing For Recording (AREA)

Abstract

本发明实施例提供一种照片处理方法包括:获取相册中多张照片的特征信息;根据该特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;若检测出相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。

Description

照片处理方法、装置及计算机设备 技术领域
本发明属于图片处理技术领域,尤其涉及一种照片处理方法、装置及计算机设备。
背景技术
随着诸如智能手机等移动终端的硬件配置越来越高,移动终端已经成为用户日常拍照的主要设备。移动终端的相册中存储有大量的照片,由于照片数量较多且未进行有效地分类整理,用户在相册中查找特定照片时,通常采用逐一翻阅的方式进行查找,这种查找方式往往需要耗费较长时间,导致相册中照片的查找效率较低。
技术问题
本发明实施例提供一种照片处理方法、装置及计算机设备,可以提高查找照片的效率。
技术解决方案
本发明实施例提供一种照片处理方法,包括:
获取相册中多张照片的特征信息;
根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
本发明实施例提供一种照片处理装置,包括:
获取模块,用于获取相册中多张照片的特征信息;
检测模块,用于根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
生成模块,用于若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
本发明实施例提供一种计算机设备,包括存储器,处理器,以及存储在所述存储器中并可在所述处理器中运行的计算机程序,所述处理器执行所述计算机程序时实现如下步骤:
获取相册中多张照片的特征信息;
根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
有益效果
本发明实施例提供一种照片处理方法、装置及计算机设备,可以提高查找照片的效率。
附图说明
图1是本发明实施例提供的照片处理方法的流程示意图。
图2是本发明实施例提供的照片处理方法中对相册中各照片标注标识信息的示意图。
图3是本发明实施例提供的照片处理方法的另一流程示意图。
图4至图11为本发明实施例提供的照片处理方法的场景示意图。
图12是本发明实施例提供的照片处理装置的结构示意图。
图13是本发明实施例提供的照片处理装置的另一结构示意图。
图14是本发明实施例提供的移动终端的结构示意图
本发明的最佳实施方式
请参照图式,其中相同的组件符号代表相同的组件,本发明的原理是以实施在一适当的运算环境中来举例说明。以下的说明是基于所例示的本发明具体实施例,其不应被视为限制本发明未在此详述的其它具体实施例。
以下将详细说明。
请参阅图1,图1是本发明实施例提供的照片处理方法的流程示意图,流程可以包括:
在步骤S101中,获取相册中多张照片的特征信息。
可以理解的是,本发明实施例的执行主体可以是诸如智能手机或平板电脑等终端设备。
比如,随着智能手机等移动终端的硬件配置越来越高,移动终端已经成为用户日常拍照的主要设备。在移动终端的相册中存储有大量的照片。由于照片数量较多且未进行有效地分类整理,用户在相册中查找特定照片时,通常采用逐一翻阅的方式进行查找,这种查找方式往往需要耗费较长时间,导致相册中照片的查找效率较低。
在本发明实施例中,终端可以先获取包含多张照片的相册中各照片的特征信息。
例如,在一种实施方式中,终端可以通过感知哈希算法,计算相册中各照片的哈希值,并将各照片的哈希值确定为相应照片的特征信息。
需要说明的是,感知哈希算法(Perceptual Hash Algorithm)是哈希算法的一类,主要用于相似图片的搜索工作。通过感知哈希算法对图片进行计算处理,可以得到一个哈希值,该哈希值是一个64位长的整数,可以用于表征图片的特征信息。
比如,在计算得到两张照片对应的哈希值之后,可以对这两个哈希值进行比较,检测这两个64位整数的哈希值有多少位是相同的。例如,若两个哈希值的相同数据位达到了55位,则可以认为这两张照片是相似图片。否则,可以认为这两张照片不是相似图片。
在步骤S102中,根据该特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测。
比如,在计算得到相册中各照片的哈希值,并将哈希值确定为相应照片的特征信息之后,终端可以根据各照片的特征信息,按照预设的照片存储次序,对相邻的每两张照片进行匹配度检测。
在一种实施方式中,终端可以按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。
例如,相册中的照片按照拍摄时间由后到先的顺序存储,即相册中的第一张照片为拍摄时间距离当前时间最近的照片,而最后一张照片的拍摄时间要早于相册中的其它照片。在这种情况下,终端可以从相册的第一张和第二张照片开始,依次检测相邻的照片的匹配度。如果存储次序上相邻的两张照片的匹配度大于或等于预设阈值,那么可以将相应的两张照片认为是相似照片。如果存储次序上相邻的两张照片的匹配度小于预设阈值,那么可以认为相应的两张照片不是相似照片。
在步骤S103中,若检测出该相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
比如,在对存储次序上相邻的每两张照片的匹配度进行检测的过程中,终端检测到该相册中包含在存储次序上相邻并且匹配度大于或等于预设阈值的照片。也就是说,终端检测到该相册中包含存储次序上相邻的相似照片,那么终端可以生成至少一个聚合文件夹,每一个聚合文件夹可以用于聚合存储次序上连续的相似照片。也即,每一聚合文件夹中所聚合的照片为在存储次序上连续的相似照片。
例如,在一种实施方式中,当终端检测到该相册中包含存储次序上相邻的相似照片时,终端可以按照预设照片存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息。其中,每一照片允许标注一次,并且同一标识信息所对应的照片在存储次序上连续。也就是说,每张照片在标注过一次标识信息之后,就不能进行第二次标注。若存储次序相邻且匹配度大于或等于预设阈值,则终端可以对相应的两张照片标注相同的标识信息。若存储次序相邻且匹配度小于预设阈值,则终端可以对相应的两张照片标注不同的标识信息。
例如,相册中有十张照片,按照拍摄时间由后到先的存储次序,依次为照片A至照片J。终端在对存储次序上相邻的每两张照片进行匹配度检测时,检测出照片A和照片B的匹配度不小于预设阈值,照片B和照片C的匹配度小于预设阈值,照片C和照片D的匹配度不小于预设阈值,照片D和照片E的匹配度不小于预设阈值,照片E和照片F的匹配度小于预设阈值,照片F和照片G的匹配度小于预设阈值,照片G和照片H的匹配度小于预设阈值,照片H和照片I的匹配度不小于预设阈值,照片I和照片J的匹配度不小于预设阈值。
那么,请参阅图2,终端可以按照存储次序,从照片A和照片B开始依次对相册中的照片进行标识信息的标注。例如,由于照片A和照片B的匹配度不小于预设阈值,因此终端可以对照片A和照片B标注相同的标识信息,例如标注的标识信息为数字“1”。
由于照片B和照片C的匹配度小于预设阈值,因此终端可以对照片C标注与照片B不同的标识信息,例如由于照片B已经具有标识信息“1”,因此可以将照片C标注为数字“2”。
由于照片C和照片D的匹配度不小于预设阈值,因此终端可以将照片D标注为数字“2”。同理,终端也可以将照片E标注为数字“2”。
由于照片E和照片F的匹配度小于预设阈值,因此终端可以对照片F标注与照片E不同的标识信息,例如将照片F标注为数字“3”。同理,终端可以将照片G标注为数字“4”。同理,终端可以将照片H标注为数字“5”。
由于照片H和照片I的匹配度不小于预设阈值,因此终端可以将照片I标注为数字“5”。同理,终端可以将照片J标注为数字“5”。
此后,终端可以生成三个聚合文件夹,分别将标识信息相同的照片聚合在一起。例如,终端可以生成第一聚合文件夹、第二聚合文件夹以及第三聚合文件夹。其中,第一聚合文件夹将标识信息为“1”的照片A和照片B聚合,即第一聚合文件夹中包含照片A和照片B。第二聚合文件夹将标识信息为“2”的照片C、照片D和照片E聚合。第三聚合文件夹将标识信息为“5”的照片H、照片I和照片J聚合。
可以理解的是,本实施例可以将在存储次序上相邻的相似照片聚合在一起并形成相应聚合文件夹,因此本实施例可以提升相册的简洁性,从而提升用户查找照片的效率。
请参阅图3,图3为本发明实施例提供的照片处理方法的另一流程示意图,流程可以包括:
在步骤S201中,终端获取相册中多张照片的特征信息。
比如,终端可以先获取包含多张照片的相册中各照片的特征信息。
例如,在一种实施方式中,终端可以通过感知哈希算法,计算相册中各照片的哈希值,并将各照片的哈希值确定为相应照片的特征信息。
需要说明的是,感知哈希算法是哈希算法的一类,主要用于相似图片的搜索工作。通过感知哈希算法对图片进行计算处理,可以得到一个哈希值,该哈希值是一个64位长的整数,可以用于表征图片的特征信息。
比如,在计算得到两张照片对应的哈希值之后,可以对这两个哈希值进行比较,检测这两个64位整数的哈希值有多少位是相同的。例如,若两个哈希值的相同数据位达到了55位,则可以认为这两张照片是相似图片。否则,可以认为这两张照片不是相似图片。
在步骤S202中,根据该特征信息,终端按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。
比如,在计算得到相册中各照片的哈希值,并将哈希值确定为相应照片的特征信息之后,终端可以根据各照片的特征信息,按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。
例如,相册中的照片按照拍摄时间由后到先的顺序存储,即相册中的第一张照片为拍摄时间距离当前时间最近的照片,而最后一张照片的拍摄时间要早于相册中的其它照片。在这种情况下,终端可以从相册的第一张和第二张照片开始,依次检测相邻的每两张照片的匹配度。如果存储次序上相邻的两张照片的匹配度大于或等于预设阈值,那么可以将相应的两张照片认为是相似照片。如果存储次序上相邻的两张照片的匹配度小于预设阈值,那么可以认为相应的两张照片不是相似照片。
在步骤S203中,若检测出相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则终端按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续。
在步骤S204中,若存储次序相邻且匹配度大于或等于预设阈值,则终端对相应的两张照片标注相同的标识信息;若存储次序相邻且匹配度小于预设阈值,则终端对相应的两张照片标注不同的标识信息。
比如,步骤S203和S204可以包括:
当终端检测到该相册中包含存储次序上相邻的相似照片时,终端可以按照基于拍摄时间的存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息。其中,每一照片允许标注一次,并且同一标识信息所对应的照片在存储次序上连续。也就是说,每张照片在标注过一次标识信息之后,就不能进行第二次标注。若存储次序相邻且匹配度大于或等于预设阈值,则终端可以对相应的两张照片标注相同的标识信息。若存储次序相邻且匹配度小于预设阈值,则终端可以对相应的两张照片标注不同的标识信息。
例如,相册中有十张照片,按照拍摄时间由后到先的存储次序,依次为照片A至照片J。终端在对存储次序上相邻的每两张照片进行匹配度检测时,检测出照片A和照片B的匹配度不小于预设阈值,照片B和照片C的匹配度小于预设阈值,照片C和照片D的匹配度不小于预设阈值,照片D和照片E的匹配度不小于预设阈值,照片E和照片F的匹配度小于预设阈值,照片F和照片G的匹配度小于预设阈值,照片G和照片H的匹配度小于预设阈值,照片H和照片I的匹配度不小于预设阈值,照片I和照片J的匹配度不小于预设阈值。
那么,终端可以按照存储次序,从照片A和照片B开始依次对相册中的照片进行标识信息的标注。例如,由于照片A和照片B的匹配度不小于预设阈值,因此终端可以对照片A和照片B标注相同的标识信息,例如标注的标识信息为数字“1”。
由于照片B和照片C的匹配度小于预设阈值,因此终端可以对照片C标注与照片B不同的标识信息,例如由于照片B已经具有标识信息“1”,因此可以将照片C标注为数字“2”。
由于照片C和照片D的匹配度不小于预设阈值,因此终端可以将照片D标注为数字“2”。同理,终端也可以将照片E标注为数字“2”。
由于照片E和照片F的匹配度小于预设阈值,因此终端可以对照片F标注与照片E不同的标识信息,例如将照片F标注为数字“3”。同理,终端可以将照片G标注为数字“4”。同理,终端可以将照片H标注为数字“5”。
由于照片H和照片I的匹配度不小于预设阈值,因此终端可以将照片I标注为数字“5”。同理,终端可以将照片J标注为数字“5”。
在步骤S205中,终端分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹,且该相册中多张照片基于拍摄时间的存储次序保持不变。
比如,在对相册中的照片进行标识信息的标注之后,终端可以将标识信息相同的照片进行聚合,并生成至少一个聚合文件夹。
例如,终端可以生成三个聚合文件夹,分别将标识信息相同的照片聚合在一起。例如,终端可以生成第一聚合文件夹、第二聚合文件夹以及第三聚合文件夹。其中,第一聚合文件夹将标识信息为“1”的照片A和照片B聚合,即第一聚合文件夹中包含照片A和照片B。第二聚合文件夹将标识信息为“2”的照片C、照片D和照片E聚合。第三聚合文件夹将标识信息为“5”的照片H、照片I和照片J聚合。在生成多个聚合文件夹的过程中,终端相册中的所有照片基于拍摄时间的存储次序可以保持不变。
例如,在未进行照片聚合之前,相册中的照片A至照片J是按照拍摄时间先后的顺序进行存储的。比如,照片A的拍摄时间晚于其它所有照片,排在相册的第一位,照片B的拍摄时间早于照片A,但晚于照片A外的其它照片,排在相册的第二位。而照片J的拍摄时间早于其它所有照片,排在相册的最后一位。
而在进行照片聚合之后,相册中照片A至照片J基于拍摄时间的存储次序可以保持不变。也即,在相册中,第一聚合文件夹排在第一位,在第一聚合文件夹中照片A排在照片B之前。第二聚合文件夹排在第二位,在第二聚合文件夹中照片C排在照片D之前,照片D排在照片E之前。照片F和G分别排在第三位和第四位。第三聚合文件夹排在第五位,在第三聚合文件中照片H排在照片I之前,照片I排在照片J之前。也就是说,在进行照片聚合之后,相册中的照片仍然按照照片A至照片J的存储次序排列。
例如,在一种实施方式中,在生成了聚合文件夹之后,终端可以对每一聚合文件夹,按照其所包含的照片的标识信息,对该聚合文件夹进行标注。例如,终端可以按照数字“1”对第一聚合文件夹进行标注,按照数字“2”对第二聚合文件夹进行标注,按照数字“5”对第三聚合文件夹进行标注。
然后,终端可以按照数字由小到大的顺序,对相册中的聚合文件夹以及未与其它照片聚合的照片进行排序存储。例如,终端可以将第一聚合文件夹(标识信息为数字“1”)存储在相册的第一位,将第二聚合文件夹(标识信息为数字“2”)存储在相册的第二位,将照片F(标识信息为数字“3”)存储在第三位,将照片G(标识信息为数字“4”)存储在第四位,将第三聚合文件夹(标识信息为数字“5”)存储在相册的第五位。
同时,终端可以对每一个聚合文件夹中所包含的照片按照拍摄时间进行排序存储。例如,在第二聚合文件夹中,聚合了照片C、照片D和照片E,那么在这个聚合文件夹中,终端可以按照拍摄时间对照片C、照片D和照片E进行排序存储。例如,按照拍摄时间由后到先的顺序,将照片C存储在第一位,照片D存储在第二位,照片E存储在第三位。也就是说,在进行聚合之前,照片C排在照片D之前,照片D排在照片E之前,那么在对这三张照片进行聚合之后,可以对这三张照片仍然按照拍摄时间先后进行排序,使得照片C仍然排在照片D之前,照片D仍然排在照片E之前。
通过上述排序方式,就可以使得相册中的所有照片基于拍摄时间的存储次序保持不变。
在步骤S206中,终端按照拍摄时间的先后顺序,将每一聚合文件夹中的首张照片设置为聚合文件夹的封面。
比如,在对每一聚合文件夹所包含的照片按照基于拍摄时间进行排序存储之后,终端可以将每一聚合文件夹中的首张照片的内容设置为该聚合文件夹的封面,以供用户查看。
例如,在上述第二聚合文件夹中,终端可以将排在第一位的照片C的内容设置为该第二聚合文件夹的封面。如此一来,用户在查看相册时就可以了解到第二聚合文件夹中包含了多张与照片C相似的图片。
需要说明的是,本实施例中,在未对相册中的照片进行聚合时,各照片是按照基于拍摄时间的存储次序进行排序的。例如,相册中的十张照片按照拍摄时间由后到先的顺序依次存储为照片A、B、C、D、E、F、G、H、I、J。而在对相册中相邻的相似照片进行聚合并按照一定的规则排序存储后,相册中的存储次序依次为第一聚合文件夹(包含照片A、B)、第二聚合文件夹(包含照片C、D、E)、照片F、照片G、第三聚合文件夹(包含照片H、I、J)。因此,相册中各照片在时间轴上的相对位置并没有发生变化。例如,相册中照片B的存储次序仍然排在照片C之前,而照片G仍然排在照片H之前。
可以理解的是,本实施例通过将存储次序上相邻的相似照片进行聚合,并且相册中所有照片基于拍摄时间的存储次序保持不变的方式,一方面可以提升相册的简洁性,提高照片查找效率,另一方面可以保证各照片在相册时间轴上的位置不变,即不破坏相册的时间轴。同时,由于进行聚合的照片都是相似照片,因此可以方便用户准确查找到相邻几次拍摄的近似照片。
在一种实施方式中,本发明实施例提供的照片处理方法还可以包括如下步骤:
当检测到聚合文件夹中的照片数量为零时,终端删除相应的聚合文件夹。
比如,对于上述第二聚合文件夹,其中包含有照片C、照片D和照片E这三张照片。若在使用过程中,用户将第二聚合文件夹中的三张照片均删除了,即终端检测到第二聚合文件夹中的照片数量由三张变为零张,那么第二聚合文件夹就变成了空文件夹。在这种情况下,终端可以将第二聚合文件夹删除。
可以理解的是,通过将照片数量为零的聚合文件夹删除,可以进一步提升相册的简洁性。
请参阅图4至图11,图4至图11为本发明实施例提供的照片处理方法的场景示意图。
比如,终端相册中包含有十张照片,依次为照片A至照片J。这十张照片按照拍摄时间由后到先的顺序存储在相册中,即照片A的拍摄时间晚于其它照片,照片J的拍摄时间早于其它照片。例如,相册的界面如图4所示。
终端可以先获取照片A至照片J的特征信息,然后根据这些照片的特征信息,按照拍摄时间由后到先的存储次序,从照片A和照片B开始,依次对存储次序上相邻的每两张照片进行匹配度检测。
在这一过程中,例如终端检测出照片A和照片B的匹配度不小于预设阈值,照片B和照片C的匹配度小于预设阈值,照片C和照片D的匹配度不小于预设阈值,照片D和照片E的匹配度不小于预设阈值,照片E和照片F的匹配度小于预设阈值,照片F和照片G的匹配度小于预设阈值,照片G和照片H的匹配度小于预设阈值,照片H和照片I的匹配度不小于预设阈值,照片I和照片J的匹配度不小于预设阈值。
之后,终端可以按照存储次序,从照片A和照片B开始依次判断相册中存储次序相邻的每两张照片是否需要标注相同的标识信息。其中,每一照片允许标注一次,并且同一标识信息所对应的照片在存储次序上连续。也就是说,每张照片在标注过一次标识信息之后,就不能进行第二次标注。若存储次序相邻且匹配度大于或等于预设阈值,那么终端可以对相应的两张照片标注相同的标识信息。若存储次序相邻且匹配度小于预设阈值,那么终端可以对相应的两张照片标注不同的标识信息。
例如,由于照片A和照片B的匹配度不小于预设阈值,因此终端可以对照片A和照片B标注相同的标识信息,例如标注的标识信息为数字“1”。
由于照片B和照片C的匹配度小于预设阈值,因此终端可以对照片C标注与照片B不同的标识信息,例如由于照片B已经具有标识信息“1”,因此可以将照片C标注为数字“2”。
由于照片C和照片D的匹配度不小于预设阈值,因此终端可以将照片D标注为数字“2”。同理,终端也可以将照片E标注为数字“2”。
由于照片E和照片F的匹配度小于预设阈值,因此终端可以对照片F标注与照片E不同的标识信息,例如将照片F标注为数字“3”。同理,终端可以将照片G标注为数字“4”。同理,终端可以将照片H标注为数字“5”。
由于照片H和照片I的匹配度不小于预设阈值,因此终端可以将照片I标注为数字“5”。同理,终端可以将照片J标注为数字“5”。
接着,终端可以生成三个聚合文件夹,分别将标识信息相同的照片聚合在一起。例如,终端可以生成第一聚合文件夹、第二聚合文件夹以及第三聚合文件夹。其中,第一聚合文件夹将标识信息为“1”的照片A和照片B聚合,即第一聚合文件夹中包含照片A和照片B。第二聚合文件夹将标识信息为“2”的照片C、照片D和照片E聚合。第三聚合文件夹将标识信息为“5”的照片H、照片I和照片J聚合。
在每一聚合文件夹中,终端可以对聚合文件夹所包含的照片仍然按照拍摄时间由后到先的顺序进行排序存储。例如,在第一聚合文件夹中,由于照片A的拍摄时间晚于照片B,因此照片A存储排在照片B之前。同理,在第二聚合文件夹中,照片C存储排在照片D之前,照片D存储排在照片E之前。而在第三聚合文件夹中,照片H存储排在照片I之前,照片I存储排在照片J之前。
之后,终端还可以对每一聚合文件夹,按照其所包含的照片的标识信息,对该聚合文件夹进行标注。例如,终端可以按照数字“1”对第一聚合文件夹进行标注,按照数字“2”对第二聚合文件夹进行标注,按照数字“5”对第三聚合文件夹进行标注。
然后,终端可以按照数字由小到大的顺序,对相册中的聚合文件以及未与其它照片聚合的文件进行排序存储。例如,终端可以将第一聚合文件夹(标识信息为数字“1”)存储在相册的第一位,将第二聚合文件(标识信息为数字“2”)存储在相册的第二位,将照片F(标识信息为数字“3”)存储在第三位,将照片G(标识信息为数字“4”)存储在第四位,将第三聚合文件(标识信息为数字“5”)存储在相册的第五位。例如,相册界面可以如图5所示。对比图4和图5可知,在经过相似照片的聚合之后,相册变得更加简洁。
在此之后,例如,用户点击了第一聚合文件夹,如图6所示,那么在终端界面上将显示照片A和照片B,如图7所示。
同理,当用户点击第二聚合文件夹时,在终端界面上将显示照片C、照片D和照片E,如图8所示。而当用户点击第三聚合文件夹时,在终端界面上将显示照片H、照片I和照片J,如图9所示。
可以理解的是,在进行照片聚合之后,各照片在时间轴上的相对位置并没有发生变化,从而可以使用户仍然能够按照时间先后的顺序查找相册中的图片,也即用户查找照片的使用习惯可以得以保留。例如,在照片聚合之前,照片B存储在照片C之前,而在照片聚合之后,照片B仍然存储在照片C之前。
在一种实施方式中,例如,用户将第三聚合文件夹中的照片I和照片J删除,那么第三聚合文件中只剩下照片H,如图10所示。在这种情况下,终端可以将照片H从第三聚合文件夹中提取出来,并按照基于拍摄时间的顺序,存储到终端相册中。例如,由于照片H的拍摄时间要早于照片G,因此可以将照片H存储在照片G之后。
接着,终端可以将照片数量为零的第三聚合文件删除,此时终端相册的界面可以如图11所示。
请参阅图12,图12为本发明实施例提供的照片处理装置的结构示意图。照片处理装置300可以包括:获取模块301,检测模块302,以及生成模块303。
获取模块301,用于获取相册中多张照片的特征信息。
比如,终端的获取模块301可以先获取包含多张照片的相册中各照片的特征信息。
例如,在一种实施方式中,获取模块301可以通过感知哈希算法,计算相册中各照片的哈希值,并将各照片的哈希值确定为相应照片的特征信息。
需要说明的是,感知哈希算法是哈希算法的一类,主要用于相似图片的搜索工作。通过感知哈希算法对图片进行计算处理,可以得到一个哈希值,该哈希值是一个64位长的整数,可以用于表征图片的特征信息。
比如,在计算得到两张照片对应的哈希值之后,可以对这两个哈希值进行比较,检测这两个64位整数的哈希值有多少位是相同的。例如,若两个哈希值的相同数据位达到了55位,则可以认为这两张照片是相似图片。否则,可以认为这两张照片不是相似图片。
检测模块302,用于根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测。
比如,在一种实施方式中,在获取模块301计算得到相册中各照片的哈希值,并将哈希值确定为相应照片的特征信息之后,检测模块302可以根据各照片的特征信息,按照预设的照片存储次序,对相邻的每两张照片进行匹配度检测。
在一种实施方式中,检测模块302可以按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。
例如,相册中的照片按照拍摄时间由后到先的顺序存储,即相册中的第一张照片为拍摄时间距离当前时间最近的照片,而最后一张照片的拍摄时间要早于相册中的其它照片。在这种情况下,检测模块302可以从相册的第一张和第二张照片开始,依次检测相邻照片的匹配度。如果存储次序上相邻的两张照片的匹配度大于或等于预设阈值,那么可以将相应的两张照片认为是相似照片。如果存储次序上相邻的两张照片的匹配度小于预设阈值,那么可以认为相应的两张照片不是相似照片。
生成模块303,用于若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
比如,在对存储次序上相邻的每两张照片的匹配度进行检测的过程中,检测模块302检测到该相册中包含在存储次序上相邻并且匹配度大于或等于预设阈值的照片。也就是说,检测模块302检测到该相册中包含存储次序上相邻的相似照片,那么可以由生成模块303生成至少一个聚合文件夹,每一个聚合文件夹可以用于聚合存储次序上连续的相似照片。也即,每一聚合文件夹中所聚合的照片为在存储次序上连续的相似照片。
例如,在一种实施方式中,生成模块303可以用于:
若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续;
若存储次序相邻且匹配度大于或等于预设阈值,则对相应的两张照片标注相同的标识信息;
若存储次序相邻且匹配度小于预设阈值,则对相应的两张照片标注不同的标识信息;
分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹。
比如,在一种实施方式中,当检测模块302检测到该相册中包含存储次序上相邻的相似照片时,生成模块303可以按照预设照片存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息。其中,每一照片允许标注一次,并且同一标识信息所对应的照片在存储次序上连续。也就是说,每张照片在标注过一次标识信息之后,就不能进行第二次标注。若存储次序相邻且匹配度大于或等于预设阈值,则生成模块303可以对相应的两张照片标注相同的标识信息。若存储次序相邻且匹配度小于预设阈值,则生成模块303可以对相应的两张照片标注不同的标识信息。
例如,相册中有十张照片,按照拍摄时间由后到先的存储次序,依次为照片A至照片J。检测模块302在对存储次序上相邻的每两张照片进行匹配度检测时,检测出照片A和照片B的匹配度不小于预设阈值,照片B和照片C的匹配度小于预设阈值,照片C和照片D的匹配度不小于预设阈值,照片D和照片E的匹配度不小于预设阈值,照片E和照片F的匹配度小于预设阈值,照片F和照片G的匹配度小于预设阈值,照片G和照片H的匹配度小于预设阈值,照片H和照片I的匹配度不小于预设阈值,照片I和照片J的匹配度不小于预设阈值。
那么,生成模块303可以按照存储次序,从照片A和照片B开始依次对相册中的照片进行标识信息的标注,以使存储次序相邻且匹配度大于或等于预设阈值的照片的标识信息相同,而存储次序相邻且匹配度小于预设阈值的照片的标识信息不同。同时,每张照片仅运行标注一次,同一标识信息是对应的照片在存储次序上连续。
例如,由于照片A和照片B的匹配度不小于预设阈值,因此生成模块303可以对照片A和照片B标注相同的标识信息,例如标注的标识信息为数字“1”。
由于照片B和照片C的匹配度小于预设阈值,因此生成模块303可以对照片C标注与照片B不同的标识信息,例如由于照片B已经具有标识信息“1”,因此可以将照片C标注为数字“2”。
由于照片C和照片D的匹配度不小于预设阈值,因此生成模块303可以将照片D标注为数字“2”。同理,生成模块303也可以将照片E标注为数字“2”。
由于照片E和照片F的匹配度小于预设阈值,因此生成模块303可以对照片F标注与照片E不同的标识信息,例如将照片F标注为数字“3”。同理,生成模块303可以将照片G标注为数字“4”。同理,生成模块303可以将照片H标注为数字“5”。
由于照片H和照片I的匹配度不小于预设阈值,因此生成模块303可以将照片I标注为数字“5”。同理,生成模块303可以将照片J标注为数字“5”。
此后,生成模块303可以生成三个聚合文件夹,分别将标识信息相同的照片聚合在一起。例如,生成模块303可以生成第一聚合文件夹、第二聚合文件夹以及第三聚合文件夹。其中,第一聚合文件夹将标识信息为“1”的照片A和照片B聚合,即第一聚合文件夹中包含照片A和照片B。第二聚合文件夹将标识信息为“2”的照片C、照片D和照片E聚合。第三聚合文件夹将标识信息为“5”的照片H、照片I和照片J聚合。
在一种实施方式中,生成模块303可以用于:
生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变。
比如,在生成多个聚合文件夹的过程中,生成模块303可以控制相册中的所有照片基于拍摄时间的存储次序保持不变。
例如,在未进行照片聚合之前,相册中的照片A至照片J是按照拍摄时间先后的顺序进行存储的。比如,照片A的拍摄时间晚于其它所有照片,排在相册的第一位,照片B的拍摄时间早于照片A,但晚于照片A外的其它照片,排在相册的第二位。而照片J的拍摄时间早于其它所有照片,排在相册的最后一位。
而在进行照片聚合之后,相册中照片A至照片J基于拍摄时间的存储次序保持不变。也即,在相册中,第一聚合文件夹排在第一位,在第一聚合文件夹中照片A排在照片B之前。第二聚合文件夹排在第二位,在第二聚合文件夹中照片C排在照片D之前,照片D排在照片E之前。照片F和G分别排在第三位和第四位。第三聚合文件夹排在第五位,在第三聚合文件中照片H排在照片I之前,照片I排在照片J之前。也就是说,在进行照片聚合之后,相册中的照片仍然按照照片A至照片J的存储次序排列。
例如,在一种实施方式中,检测模块302可以用于:按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。而生成模块303可以用于:生成至少一个聚合文件夹,且所述相册中多张照片基于拍摄时间的存储次序保持不变。
比如,在生成了聚合文件夹之后,生成模块303可以对每一聚合文件夹,按照其所包含的照片的标识信息,对该聚合文件夹进行标注。例如,生成模块303可以按照数字“1”对第一聚合文件夹进行标注,按照数字“2”对第二聚合文件夹进行标注,按照数字“5”对第三聚合文件夹进行标注。
然后,生成模块303可以按照数字由小到大的顺序,对相册中的聚合文件夹以及未与其它照片聚合的照片进行排序存储。例如,生成模块303可以将第一聚合文件夹(标识信息为数字“1”)存储在相册的第一位,将第二聚合文件夹(标识信息为数字“2”)存储在相册的第二位,将照片F(标识信息为数字“3”)存储在第三位,将照片G(标识信息为数字“4”)存储在第四位,将第三聚合文件夹(标识信息为数字“5”)存储在相册的第五位。
同时,生成模块303可以对每一个聚合文件夹中所包含的照片按照拍摄时间进行排序存储。例如,在第二聚合文件夹中,聚合了照片C、照片D和照片E,那么在这个聚合文件夹中,生成模块303可以按照拍摄时间对照片C、照片D和照片E进行排序存储。例如,按照拍摄时间由后到先的顺序,将照片C存储在第一位,照片D存储在第二位,照片E存储在第三位。也就是说,在进行聚合之前,照片C排在照片D之前,照片D排在照片E之前,那么在对这三张照片进行聚合之后,可以对这三张照片进行排序,使得照片C仍然排在照片D之前,照片D仍然排在照片E之前。
通过上述排序方式,就可以使得相册中的所有照片基于拍摄时间的存储次序保持不变。
请一并参阅图13,图13为本发明实施例提供的照片处理装置的另一结构示意图。在一实施例中,照片处理装置300还可以包括:删除模块304,以及设置模块305。
删除模块304,用于当检测到聚合文件夹中的照片数量为零时,删除相应的聚合文件夹。
比如,对于上述第二聚合文件夹,其中包含有照片C、照片D和照片E这三张照片。若在使用过程中,用户将第二聚合文件夹中的三张照片均删除了,即终端检测到第二聚合文件夹中的照片数量由三张变为零张,那么第二聚合文件夹就变成了空文件夹。在这种情况下,删除模块304可以将第二聚合文件夹删除。
可以理解的是,通过将照片数量为零的聚合文件夹删除,可以进一步提升相册的简洁性。
设置模块305,用于按照拍摄时间的先后顺序,将每一所述聚合文件夹中的首张照片设置为聚合文件夹的封面。
比如,在上述第二聚合文件夹中,设置模块305可以将存储在第一位的照片C的内容设置为该第二聚合文件夹的封面。如此一来,用户在查看相册时就可以了解到第二聚合文件夹中包含了多张与照片C相似的图片。
本发明实施例还提供一种计算机设备,该计算机设备可以包括存储器、处理器,以及存储在所述存储器中并可在所述处理器中运行的计算机程序,所述处理器执行所述计算机程序时可以实现本发明实施例提供的照片处理方法中的步骤。
例如,该计算机设备可以是如平板电脑、智能手机等移动终端。
请参阅图14,图14为本发明实施例提供的移动终端结构示意图。该移动终端500可以包括:有一个或一个以上计算机可读存储介质的存储器501、输入单元502、显示单元503、包括有一个或者一个以上处理核心的处理器504、传感器505以及电源506等部件。本领域技术人员可以理解,图14中示出的移动终端结构并不构成对移动终端的限定,可以包括比图示更多或更少的部件,或者组合某些部件,或者不同的部件布置。
存储器501可用于存储应用程序和数据。存储器501存储的应用程序中包含有可执行代码。应用程序可以组成各种功能模块。处理器504通过运行存储在存储器501的应用程序,从而执行各种功能应用以及数据处理。
输入单元502可用于接收输入的数字、字符信息或用户特征信息(比如指纹),以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。
显示单元503可用于显示由用户输入的信息或提供给用户的信息以及移动终端的各种图形用户接口,这些图形用户接口可以由图形、文本、图标、视频和其任意组合来构成。显示单元504可包括显示面板。
处理器504是移动终端的控制中心,利用各种接口和线路连接整个移动终端的各个部分,通过运行或执行存储在存储器501内的应用程序,以及调用存储在存储器501内的数据,执行移动终端的各种功能和处理数据,从而对移动终端进行整体监控。
移动终端还可以包括至少一种传感器505,比如光线传感器、陀螺仪传感器以及其他传感器。
移动终端还可以包括给各个部件供电的电源506(比如电池等)。
尽管图14中未示出,移动终端还可以包括摄像头、蓝牙模块等,在此不再赘述。
在本实施例中,移动终端中的处理器504会按照如下的指令,将一个或一个以上的应用程序的进程对应的计算机程序加载到存储器501中,并由处理器504来运行存储在存储器501中的计算机程序,从而实现如下步骤:
获取相册中多张照片的特征信息;
根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
处理器504在执行所述生成至少一个聚合文件夹时,可以实现如下步骤:生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变。
处理器504在执行所述若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹时,可以实现如下步骤:若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续;若存储次序相邻且匹配度大于或等于预设阈值,则对相应的两张照片标注相同的标识信息;若存储次序相邻且匹配度小于预设阈值,则对相应的两张照片标注不同的标识信息;分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹。
处理器504在执行所述按照预设照片存储次序,对相邻的每两张照片进行匹配度检测时,可以实现如下步骤:按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测。而处理器504在执行所述生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变时,实现如下步骤:生成至少一个聚合文件夹,且所述相册中多张照片基于拍摄时间的存储次序保持不变。
处理器504执行所述计算机程序时还可以实现如下步骤:当检测到聚合文件夹中的照片数量为零时,删除相应的聚合文件夹。
处理器504执行所述计算机程序时还可以实现如下步骤:按照拍摄时间的先后顺序,将每一所述聚合文件夹中的首张照片设置为聚合文件夹的封面。
在一种实施方式中,处理器504执行所述获取相册中多张照片的特征信息时,可以实现如下步骤:通过感知哈希算法,获取相册中多张照片的哈希值,并将所述哈希值确定为照片的特征信息。
在上述实施例中,对各个实施例的描述都各有侧重,某个实施例中没有详述的部分,可以参见上文针对照片处理方法的详细描述,此处不再赘述。
本发明实施例提供的所述照片处理装置与上文实施例中的照片处理方法属于同一构思,在所述照片处理装置上可以运行所述照片处理方法实施例中提供的任一方法,其具体实现过程详见所述照片处理方法实施例,此处不再赘述。
需要说明的是,对本发明实施例所述照片处理方法而言,本领域普通测试人员可以理解实现本发明实施例所述照片处理方法的全部或部分流程,是可以通过计算机程序来控制相关的硬件来完成,所述计算机程序可存储于一计算机可读取存储介质中,如存储在存储器中,并被至少一个处理器执行,在执行过程中可包括如所述照片处理方法的实施例的流程。其中,所述的存储介质可为磁碟、光盘、只读存储器(ROM,Read Only Memory)、随机存取记忆体(RAM,Random Access Memory)等。
对本发明实施例的所述照片处理装置而言,其各功能模块可以集成在一个处理芯片中,也可以是各个模块单独物理存在,也可以两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现,也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时,也可以存储在一个计算机可读取存储介质中,所述存储介质譬如为只读存储器,磁盘或光盘等。
以上对本发明实施例所提供的一种照片处理方法、装置以及计算机设备进行了详细介绍,本文中应用了具体个例对本发明的原理及实施方式进行了阐述,以上实施例的说明只是用于帮助理解本发明的方法及其核心思想;同时,对于本领域的技术人员,依据本发明的思想,在具体实施方式及应用范围上均会有改变之处,综上所述,本说明书内容不应理解为对本发明的限制。

Claims (20)

  1. 一种照片处理方法,其特征在于,所述方法包括:
    获取相册中多张照片的特征信息;
    根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
    若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
  2. 根据权利要求1所述的照片处理方法,其特征在于,所述生成至少一个聚合文件夹,包括:
    生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变。
  3. 根据权利要求2所述的照片处理方法,其特征在于,所述若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,包括:
    若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续;
    若存储次序相邻且匹配度大于或等于预设阈值,则对相应的两张照片标注相同的标识信息;
    若存储次序相邻且匹配度小于预设阈值,则对相应的两张照片标注不同的标识信息;
    分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹。
  4. 根据权利要求3所述的照片处理方法,其特征在于,所述按照预设照片存储次序,对相邻的每两张照片进行匹配度检测,包括:
    按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测;
    所述生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变,包括:生成至少一个聚合文件夹,且所述相册中多张照片基于拍摄时间的存储次序保持不变。
  5. 根据权利要求4所述的照片处理方法,其特征在于,所述方法还包括:
    当检测到聚合文件夹中的照片数量为零时,删除相应的聚合文件夹。
  6. 根据权利要求5所述的照片处理方法,其特征在于,所述方法还包括:
    按照拍摄时间的先后顺序,将每一所述聚合文件夹中的首张照片设置为聚合文件夹的封面。
  7. 根据权利要求1所述的照片处理方法,其特征在于,所述获取相册中多张照片的特征信息,包括:
    通过感知哈希算法,获取相册中多张照片的哈希值,并将所述哈希值确定为照片的特征信息。
  8. 一种照片处理装置,其特征在于,所述装置包括:
    获取模块,用于获取相册中多张照片的特征信息;
    检测模块,用于根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
    生成模块,用于若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
  9. 根据权利要求8所述的照片处理装置,其特征在于,所述生成模块用于:
    生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变。
  10. 根据权利要求9所述的照片处理装置,其特征在于,所述生成模块用于:
    若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续;
    若存储次序相邻且匹配度大于或等于预设阈值,则对相应的两张照片标注相同的标识信息;
    若存储次序相邻且匹配度小于预设阈值,则对相应的两张照片标注不同的标识信息;
    分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹。
  11. 根据权利要求10所述的照片处理装置,其特征在于,所述检测模块用于:按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测;
    所述生成模块用于:生成至少一个聚合文件夹,且所述相册中多张照片基于拍摄时间的存储次序保持不变。
  12. 根据权利要求11所述的照片处理装置,其特征在于,所述装置还包括:
    删除模块,用于当检测到聚合文件夹中的照片数量为零时,删除相应的聚合文件夹。
  13. 根据权利要求12所述的照片处理装置,其特征在于,所述装置还包括:
    设置模块,用于按照拍摄时间的先后顺序,将每一所述聚合文件夹中的首张照片设置为聚合文件夹的封面。
  14. 根据权利要求8所述的照片处理装置,其特征在于,所述获取模块用于:通过感知哈希算法,获取相册中多张照片的哈希值,并将所述哈希值确定为照片的特征信息。
  15. 一种计算机设备,包括存储器,处理器,以及存储在所述存储器中并可在所述处理器中运行的计算机程序,其特征在于,所述处理器执行所述计算机程序时实现如下步骤:
    获取相册中多张照片的特征信息;
    根据所述特征信息,按照预设照片存储次序,对相邻的每两张照片进行匹配度检测;
    若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹,每一所述聚合文件夹用于聚合存储次序上连续且匹配度大于或等于预设阈值的照片。
  16. 根据权利要求15所述的计算机设备,其特征在于,所述处理器执行所述生成至少一个聚合文件夹时,实现如下步骤:
    生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变。
  17. 根据权利要求16所述的计算机设备,其特征在于,所述处理器在执行所述若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则生成至少一个聚合文件夹时,实现如下步骤:
    若检测出所述相册中包含存储次序相邻且匹配度大于或等于预设阈值的照片,则按照存储次序,依次判断是否对存储次序相邻的每两张照片标注相同的标识信息,其中每一照片允许标注一次,且同一标识信息所对应的照片在存储次序上连续;
    若存储次序相邻且匹配度大于或等于预设阈值,则对相应的两张照片标注相同的标识信息;
    若存储次序相邻且匹配度小于预设阈值,则对相应的两张照片标注不同的标识信息;
    分别将标识信息相同的照片进行聚合,以生成至少一个聚合文件夹。
  18. 根据权利要求17所述的计算机设备,其特征在于,所述处理器在执行所述按照预设照片存储次序,对相邻的每两张照片进行匹配度检测时,实现如下步骤:
    按照基于拍摄时间的存储次序,对相邻的每两张照片进行匹配度检测;
    所述处理器在执行所述生成至少一个聚合文件夹,且所述相册中多张照片的存储次序保持不变时,实现如下步骤:生成至少一个聚合文件夹,且所述相册中多张照片基于拍摄时间的存储次序保持不变。
  19. 根据权利要求18所述的计算机设备,其特征在于,所述处理器执行所述计算机程序时还实现如下步骤:
    当检测到聚合文件夹中的照片数量为零时,删除相应的聚合文件夹。
  20. 根据权利要求19所述的计算机设备,其特征在于,所述处理器执行所述计算机程序时还实现如下步骤:
    按照拍摄时间的先后顺序,将每一所述聚合文件夹中的首张照片设置为聚合文件夹的封面。
PCT/CN2017/081100 2017-04-19 2017-04-19 照片处理方法、装置及计算机设备 WO2018191889A1 (zh)

Priority Applications (4)

Application Number Priority Date Filing Date Title
EP17906536.2A EP3611629A4 (en) 2017-04-19 2017-04-19 PHOTO PROCESSING METHOD AND DEVICE AND COMPUTER DEVICE
US16/605,468 US11429660B2 (en) 2017-04-19 2017-04-19 Photo processing method, device and computer equipment
PCT/CN2017/081100 WO2018191889A1 (zh) 2017-04-19 2017-04-19 照片处理方法、装置及计算机设备
CN201780087001.6A CN110313001A (zh) 2017-04-19 2017-04-19 照片处理方法、装置及计算机设备

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/081100 WO2018191889A1 (zh) 2017-04-19 2017-04-19 照片处理方法、装置及计算机设备

Publications (1)

Publication Number Publication Date
WO2018191889A1 true WO2018191889A1 (zh) 2018-10-25

Family

ID=63855619

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/081100 WO2018191889A1 (zh) 2017-04-19 2017-04-19 照片处理方法、装置及计算机设备

Country Status (4)

Country Link
US (1) US11429660B2 (zh)
EP (1) EP3611629A4 (zh)
CN (1) CN110313001A (zh)
WO (1) WO2018191889A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110717058A (zh) * 2019-09-23 2020-01-21 Oppo广东移动通信有限公司 信息推荐方法及装置、存储介质
CN113360687A (zh) * 2021-06-24 2021-09-07 平安普惠企业管理有限公司 图片保存方法、装置、移动终端及存储介质

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11449545B2 (en) * 2019-05-13 2022-09-20 Snap Inc. Deduplication of media file search results

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102265598A (zh) * 2008-10-26 2011-11-30 惠普开发有限公司 使用基于内容的过滤和基于主题的聚类将图像布置到页面中
CN104111778A (zh) * 2014-06-25 2014-10-22 小米科技有限责任公司 图片显示方法和装置
CN104133917A (zh) * 2014-08-15 2014-11-05 百度在线网络技术(北京)有限公司 照片的分类存储方法及装置
WO2016173350A1 (zh) * 2015-04-29 2016-11-03 腾讯科技(深圳)有限公司 图片处理方法及装置

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7412449B2 (en) * 2003-05-23 2008-08-12 Sap Aktiengesellschaft File object storage and retrieval using hashing techniques
US8725780B2 (en) * 2009-06-12 2014-05-13 Imation Corp. Methods and systems for rule-based worm enforcement
US9218701B2 (en) * 2013-05-28 2015-12-22 Bank Of America Corporation Image overlay for duplicate image detection
US20150142742A1 (en) * 2013-11-17 2015-05-21 Zhen-Chao HONG System and method for syncing local directories that enable file access across multiple devices
CN103744996A (zh) * 2014-01-23 2014-04-23 惠州Tcl移动通信有限公司 一种移动终端相册分类的方法及系统
CN104866501B (zh) * 2014-02-24 2021-06-25 腾讯科技(深圳)有限公司 电子旅行相册生成方法和系统
CN106155924B (zh) 2015-04-08 2019-05-28 Tcl集团股份有限公司 图片合并方法、装置及智能设备
CN106326820A (zh) * 2015-07-03 2017-01-11 中兴通讯股份有限公司 照片分享方法及装置
CN105095479A (zh) * 2015-08-12 2015-11-25 惠州Tcl移动通信有限公司 一种移动终端及其实现照片分类管理的方法
US9639708B2 (en) * 2015-08-18 2017-05-02 Google Inc. Methods and systems of encrypting file system directories
CN105760461A (zh) * 2016-02-04 2016-07-13 上海卓易科技股份有限公司 相册的自动建立方法及其装置
CN105956031A (zh) * 2016-04-25 2016-09-21 深圳市永兴元科技有限公司 文本分类方法和装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102265598A (zh) * 2008-10-26 2011-11-30 惠普开发有限公司 使用基于内容的过滤和基于主题的聚类将图像布置到页面中
CN104111778A (zh) * 2014-06-25 2014-10-22 小米科技有限责任公司 图片显示方法和装置
CN104133917A (zh) * 2014-08-15 2014-11-05 百度在线网络技术(北京)有限公司 照片的分类存储方法及装置
WO2016173350A1 (zh) * 2015-04-29 2016-11-03 腾讯科技(深圳)有限公司 图片处理方法及装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3611629A4 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110717058A (zh) * 2019-09-23 2020-01-21 Oppo广东移动通信有限公司 信息推荐方法及装置、存储介质
CN110717058B (zh) * 2019-09-23 2023-06-09 Oppo广东移动通信有限公司 信息推荐方法及装置、存储介质
CN113360687A (zh) * 2021-06-24 2021-09-07 平安普惠企业管理有限公司 图片保存方法、装置、移动终端及存储介质

Also Published As

Publication number Publication date
EP3611629A1 (en) 2020-02-19
US20200372068A1 (en) 2020-11-26
EP3611629A4 (en) 2020-02-19
CN110313001A (zh) 2019-10-08
US11429660B2 (en) 2022-08-30

Similar Documents

Publication Publication Date Title
WO2021132927A1 (en) Computing device and method of classifying category of data
WO2016072674A1 (en) Electronic device and method of controlling the same
WO2017142143A1 (en) Method and apparatus for providing summary information of a video
WO2017054463A1 (zh) 事件信息推送方法、事件信息推送装置及存储介质
WO2016167407A1 (ko) 암호화 데이터 관리 방법 및 장치
WO2017067286A1 (zh) 一种指纹模板更新方法、装置及终端
WO2017028573A1 (zh) 一种基于移动终端的图片信息处理的方法及系统
WO2016027983A1 (en) Method and electronic device for classifying contents
WO2016003219A1 (en) Electronic device and method for providing content on electronic device
EP3254209A1 (en) Method and device for searching for image
WO2018191889A1 (zh) 照片处理方法、装置及计算机设备
WO2018062894A1 (ko) 전력을 제어하는 전자 장치
WO2020149689A1 (ko) 영상 처리 방법 및 이를 지원하는 전자 장치
WO2017206454A1 (zh) 一种指纹拍照处理方法及装置
WO2020190021A1 (en) Method and device for storing a data file in a cloud-based storage
EP3821378A1 (en) Apparatus for deep representation learning and method thereof
WO2018021723A1 (ko) 이미지의 유사도에 기초하여 이미지들을 연속적으로 표시하는 방법 및 장치
WO2022080659A1 (ko) 전자 장치 및 이의 제어 방법
WO2015178716A1 (en) Search method and device
WO2016080653A1 (en) Method and apparatus for image processing
WO2019146951A1 (en) Electronic apparatus and control method thereof
EP3516843A1 (en) Electronic device and method for operating the same
WO2024112108A1 (ko) 실시간 drm 기반 영상 스트리밍 시스템 및 그의 영상 스트리밍 방법
WO2019074185A1 (en) ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF
WO2020075960A1 (ko) 전자 장치, 외부 전자 장치 및 전자 장치를 이용한 외부 전자 장치를 제어하는 방법

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17906536

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2017906536

Country of ref document: EP

Effective date: 20191115