WO2017016160A1 - 目标图片分类存储方法及其终端 - Google Patents

目标图片分类存储方法及其终端 Download PDF

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Publication number
WO2017016160A1
WO2017016160A1 PCT/CN2015/098790 CN2015098790W WO2017016160A1 WO 2017016160 A1 WO2017016160 A1 WO 2017016160A1 CN 2015098790 W CN2015098790 W CN 2015098790W WO 2017016160 A1 WO2017016160 A1 WO 2017016160A1
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Prior art keywords
information
voice
module
target
classification information
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PCT/CN2015/098790
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English (en)
French (fr)
Inventor
魏党伟
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北京奇虎科技有限公司
奇智软件（北京）有限公司
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Publication of WO2017016160A1 publication Critical patent/WO2017016160A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/11—File system administration, e.g. details of archiving or snapshots
    • G06F16/113—Details of archiving
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification

Definitions

  • the present invention relates to the field of image storage technologies for intelligent terminals, and in particular, to a target picture classification storage method and a corresponding terminal thereof.
  • the driving recorder can record the video image and sound of the vehicle during driving, which is equivalent to the black box of the vehicle.
  • the camera on the driving recorder is turned on, and the scenery or road condition information along the way can be captured by the camera, and then the captured video information is stored in a local storage device or transmitted to the cloud through the network.
  • the storage space of the driving recorder is limited, and the storage of video data requires a large amount of storage space.
  • An object of the present invention is to solve at least the above problems, and to provide a target picture classification storage method and a terminal thereof.
  • the invention provides a target image classification storage method, which comprises the following steps:
  • the target picture is saved to a target folder corresponding to the classification information.
  • the invention also provides a target picture classification storage terminal, comprising:
  • a capture module configured to capture a target image by capturing a camera by capturing a target with a capture instruction with classification information
  • An attribute setting module configured to add the classification information to attribute information of the target picture
  • a storage module configured to save the target image to a target folder corresponding to the classification information.
  • Also disclosed is a computer program comprising computer readable code that causes the method to be executed when the intelligent electronic device runs the computer readable code.
  • the camera performs normal shooting
  • a snapping instruction based on the classification information of the screen feature is issued, and the target image is obtained by capturing the camera by the camera in response to the instruction; Information is added to the attribute information of the target picture; and the target picture is saved to a target folder corresponding to the classification information. Therefore, the special picture that is of interest to the user is captured based on a certain classification information, and is stored in a separate storage area corresponding to the classified information, and the problem that the video is easily covered by the video data when the video is stored in the same storage area does not occur.
  • the user when the user wants to find a special picture based on a certain category information, the user can directly access the folder corresponding to the category information, without spending a lot of manpower and time to quickly query all the videos by fast-forwarding and rewinding. obtain.
  • the capture command is a voice command
  • the classification information of the character, the scenery, the car accident, and the road condition is determined from the natural language included in the voice command.
  • the present invention also sets navigation information such as time, geographical location, driving direction, driving speed, geographic latitude and longitude in the attributes of the picture. Set navigation information and classification information in the captured image to facilitate users to find more accurately. And when the image is uploaded to the cloud server, it can better cooperate with the cloud search application to provide more accurate image search information for other users and improve search efficiency.
  • the present invention is further implemented in conjunction with a cloud technology to determine the classification information by transmitting a voice recognition request including the voice stream data and receiving a string text obtained by the remote server corresponding to parsing the voice stream data, due to the remote server.
  • the data is more comprehensive and scientific, so that the classified information obtained is more scientific and precise, and has universal adaptability, so as to avoid misjudgment and further improve reliability.
  • the present invention can further upload the target picture through the local area network, thereby transmitting the target picture to a certain device in the local area network, realizing the transfer of the picture file, and effectively protecting the picture file from being lost due to being covered.
  • FIG. 1 is a flow chart of a program of an embodiment of a target picture classification storage method of the present invention
  • FIG. 2 is a flow chart of a program of still another embodiment of the target picture classification storage method of the present invention.
  • FIG. 3 is a flow chart showing a procedure of another embodiment of the target picture classification storage method of the present invention.
  • FIG. 4 is a flow chart of a program of an embodiment of a target picture classification storage method of the present invention.
  • FIG. 5 is a schematic structural diagram of an embodiment of a target picture classification storage terminal of the present invention.
  • FIG. 6 is a schematic structural view of a capture module in still another embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of an attribute setting module in another embodiment of the present invention.
  • Figure 8 is a schematic structural view of an embodiment of the present invention.
  • Figure 9 shows a block diagram of an intelligent electronic device for performing the method according to the invention.
  • Figure 10 shows a schematic diagram of a memory unit for holding or carrying program code implementing a method in accordance with the present invention.
  • terminal and terminal device used herein include both a wireless signal receiver device, a device having only a wireless signal receiver without a transmitting capability, and a receiving and transmitting hardware.
  • Such a device may comprise: a cellular or other communication device having a single line display or a multi-line display or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service), which may Combined voice, data processing, fax and/or data communication capabilities; PDA (Personal Digital Assistant), which can include radio frequency receivers, pagers, Internet/Intranet access, web browsers, notepads, calendars and / Or a GPS (Global Positioning System) receiver; a conventional laptop and/or palmtop computer or other device having a conventional laptop and/or palmtop computer or other including a radio frequency receiver or other device.
  • PCS Personal Communications Service
  • PDA Personal Digital Assistant
  • terminal may be portable, transportable, installed in a vehicle (aviation, sea and/or land), or adapted and/or configured to operate locally, and/or Run in any other location on the Earth and/or space in a distributed form.
  • the "terminal” and “terminal device” used herein may also be a communication terminal, an internet terminal, a music/video playing terminal, and may be, for example, a PDA, a MID (Mobile Internet Device), and/or have a music/video playback.
  • Functional mobile phones can also be smart TVs, set-top boxes and other devices.
  • the concepts of servers, clouds, remote network devices, and the like used herein have equivalent effects, including but not limited to computers, network hosts, single network servers, multiple network server sets, or multiple servers.
  • the cloud is composed of a large number of computers or network servers based on Cloud Computing, which is a kind of distributed computing, a super virtual computer composed of a group of loosely coupled computers.
  • the communication between the remote network device, the terminal device and the WNS server can be implemented by any communication method, including but not limited to, mobile communication based on 3GPP, LTE, WIMAX, TCP/IP, UDP protocol. Computer network communication and short-range wireless transmission based on Bluetooth and infrared transmission standards.
  • the application method of the related method and terminal of the present invention is based on a hardware recorder based on a driving recorder with a camera, a processor, a communication module and a storage module, and is exemplified by a driving recorder equipped with a processor of a Linux system. It should be noted that the description is merely exemplary, and the scope of the present invention is not limited thereto. The method and terminal of the embodiments of the present invention are also applicable to other operating systems, and are essentially independent of the operating system.
  • the present invention is not limited to the driving recorder, but also includes other intelligent terminals that do not have a user operation interface, or are not convenient for the user to operate in time, such as a smart camera, a smart watch, and the like.
  • the target image is obtained by the camera capture.
  • the camera always captures scenery and road condition information along the way during the exercise of the automobile.
  • a snap instruction with the screen classification information can be directly issued.
  • the capture command may be a physical button or a touch panel that is set on the driving recorder, or may be a voice command.
  • the capture command is obtained by triggering a physical button or a touch panel disposed on the driving recorder, the physical button or the touch panel should be preset in plurality and each button needs to correspond to one of the classification information.
  • a voice command is preferably used as the capture instruction, wherein the natural language of the voice command issued by the user includes classification information.
  • the type of the classification information includes any number of types of characters, landscapes, car accidents, and road conditions.
  • the step S11 may further include the following steps:
  • the present invention preferably employs a microphone as a voice recording device to acquire voice stream data for the user.
  • the sound collection direction of the voice recording device is optimal for the position of a certain seat in the vehicle.
  • the voice receiving range of the voice recording device is defined as the driver, that is, the microphone is placed closer to the driver's position to receive a voice signal having low interference and high signal to noise ratio.
  • the driver can issue a voice command of "character beat", "landscape beat”, "car accident shoot” or "road condition shoot”, wherein "person”, “landscape”, “car accident”, “road condition” is classification information.
  • the voice analog signal recorded by the voice recording device is converted into digital voice stream data by A/D and then stored in the buffer of the processor core.
  • the voice stream data recognition program reads the sampled digital voice stream data from the buffer of the processor core by calling the read function, and recognizes and converts the data into the string text format.
  • the process of identifying classification information from voice stream data can be implemented by two embodiments provided by the present invention.
  • the step may be the classification information obtained by uploading to the cloud server for obtaining the string text format, or may be the matching information with the local voice library to obtain the classification information of the string text format. .
  • the step is to obtain the classification information of the string text format by uploading to the cloud server for identification, which specifically includes the following steps:
  • the voice stream data identifying program includes the obtained voice stream data into the voice recognition request and submits to the remote voice cloud server through the remote interface;
  • S112b Identifying and parsing the voice stream data in a voice recognition platform of the remote voice cloud server to obtain a string text
  • the voice stream data identification program and the voice cloud server use the Socket-based TCP protocol for communication, and adopt an asynchronous control method, so as to avoid blocking of the voice data stream and ensure The timely reporting of voice data streams provides users with a better control experience.
  • the voice cloud server is a processing platform with a voice library, and may be an independent server in the network, or a collection of multiple servers providing different voice recognition services.
  • the voice library may be provided by a separate server, or Integrated with a voice server.
  • the cloud technology is implemented, by sending a voice recognition request including the voice stream data and receiving a string text obtained by the remote server correspondingly parsing the voice stream data to determine the Classification information, because the data in the remote server is more comprehensive and scientific, the obtained classification information is more scientific and accurate, and has universal adaptability, thereby avoiding misjudgment and further improving reliability.
  • the step is to perform the matching and identifying process with the local voice library to obtain the classification information of the string text format, which specifically includes the following steps:
  • S112A Perform matching and identification processing on the acquired voice stream data and the local voice library.
  • the voice stream data recognition program calls the local voice library, and the acquired voice stream data is matched and identified.
  • S112B Obtain classification information in a string text format that matches the voice stream data.
  • the voice stream data and the character string text format are stored in advance.
  • the class information is a list of mapping relationships, and the classification information of the string text format matching the voice stream data is obtained.
  • the voice library can be a local voice library formed by downloading and saving to a local voice cloud server. If the classification information of the string text format corresponding to the voice stream data is not found in the local voice library, the local voice library may be updated by communicating with the remote cloud server.
  • the method of the present invention further includes a step S113 of capturing a target picture corresponding to the classification information by capturing a camera.
  • the classification information of the target picture has been obtained from the voice instruction, and further, the camera capture is called to obtain the target picture corresponding to the classification information.
  • the USB camera is taken as an example here.
  • calling the camera capture to obtain the target image corresponding to the classification information may be implemented by using two embodiments.
  • the target picture is obtained by triggering a photograph by calling a photographing mode.
  • a USB driver for driving the camera is preloaded. It is not difficult to understand, you can communicate with the USB camera by calling the USB low-level operation library libusb, provide USB control commands, switch the camera to camera mode, and set the camera aperture, shutter, ISO and other parameters through software instructions.
  • the driving recorder obtains the snapping instruction with the classification information, the software command is used to trigger the shutter of the camera to capture the target image.
  • the target picture is obtained by intercepting a video image of a time point corresponding to when the capture instruction is issued. After responding to the capture instruction, the video frame static data at the time point corresponding to the capture instruction is intercepted by a certain interception algorithm to obtain a target picture.
  • the interception algorithm is well known to those skilled in the art and will not be described in detail herein.
  • this step further comprising: performing classification information identification on the voice instruction only when it is determined that the feature information extracted from the voice data stream of the voice instruction matches the locally pre-stored voiceprint feature.
  • This step is for security reasons, preventing the illegal user from controlling the terminal that implements the solution of the present invention to take a snapshot, and causing some pictures that the user does not need to be photographed or even invading other people's privacy to occupy the storage space or bring unnecessary troubles. . Therefore, the user's voice data is pre-acquired locally, and the voiceprint feature that uniquely identifies the user's identity can be extracted and saved locally.
  • the feature information of the voice data stream corresponding to the voice instruction is extracted, and matched with the voiceprint feature of the legal user pre-collected and pre-stored locally, if two If the match is matched, the voice command is considered legal. Otherwise, it is illegal. Only when the instruction is legal, the voice instruction is classified information identification, and then the subsequent process of capturing by the camera is started.
  • the target picture corresponding to the classification information is obtained.
  • the method of the present invention further includes the step S12 of adding the classification information to the attribute information of the target picture.
  • the step S12 further includes:
  • GIF is a lossless compression, using LZW compression algorithm for encoding, using 8-bit color compression, can only process up to 256 colors, not easy to save true color images
  • PNG is a lossless data compression bitmap graphics file format
  • JPEG is a widely used distortion compression standard method for photo images, using Huffman compression algorithm for destructive compression.
  • the captured target picture data is converted to a target picture in JPEG format by a Huffman compression algorithm.
  • the navigation module When the image is compressed into a picture format of a specific format, the navigation module needs to be called to obtain the current navigation information, so that the navigation information is subsequently loaded into the image attribute.
  • the navigation module may be built in the driving recorder or may be an external navigation module, which is not limited by the present invention.
  • the navigation module may be a GPS navigation module or a Beidou satellite navigation.
  • the navigation module is a GPS navigation module.
  • the GPS navigation module obtains navigation information of the target image according to the NMEA-0182 protocol, or obtains navigation information of the target image by using a base station positioning manner.
  • the navigation information includes any one or any of a plurality of time, a geographical location, a driving direction, a driving speed, and a geographic latitude and longitude.
  • the obtaining of the current navigation information by calling the navigation module in this step can be implemented by using two embodiments. The implementation process of each embodiment is specifically described below:
  • the GPS navigation module obtains navigation information of a target picture according to the NMEA-0182 protocol.
  • the NMEA-0183 protocol is a standardized GPS data format protocol.
  • the data may include time, geographical location, longitude and latitude, driving direction, driving speed and the like, and the GPS navigation module acquires the satellite positioning signal from the GPS satellite and calculates the navigation data.
  • the processing module in the GPS navigation module analyzes and processes the received ASCII code statement based on the NMEA-0183 protocol format to obtain navigation information.
  • the GPS navigation module obtains the navigation information of the target image by using the base station positioning manner, and the method is a technical means commonly used by those skilled in the art, and will not be described in detail herein.
  • This embodiment uses the target picture in the JPEG format as an example to briefly describe the implementation method of this step.
  • Exif (Exchangeable Image File) is an image file format.
  • the Exif format is the information inserted into the JPEG format header, which can load the aperture, shutter, balance white, ISO, focus, date, time and navigation information of the picture. Therefore, classification information and navigation information can be added to the Exif information of the obtained target picture.
  • the JPEG file begins with the string "0XFFD8" and ends with the string "0XFFD9” and is used between the string "OXFFE0-0XFFEF” for storing Exif information.
  • the navigation information and the classification information are added between the character string “OXFFE0-0XFFEF” in the process of compressing the obtained target image data in the RGB format into the target image in the JPEG format by the Huffman compression algorithm.
  • the attribute setting of the target picture in the present invention is implemented.
  • a file format such as PNG can also be adopted by the present invention, which is represented by the suffix of the image file, which is .jpeg, .jpg, .png, and the like.
  • a memo form corresponding to all related picture files stored therein may be built in each target folder, and the picture file name and the navigation information are established in the table.
  • the mapping relationship data between the two types can solve the problem of the addition of the attribute information caused by the difference in the format, and the same can satisfy the requirements of the present invention.
  • the foregoing method steps complete the acquisition of the target picture and the attribute setting of the target picture.
  • the method of the present invention further includes the step S13 of saving the target picture to a target folder corresponding to the classification information.
  • the present invention uses an SD card as a storage medium as an example to describe the implementation manner thereof, but does not constitute a limitation on the invention, and other A non-volatile memory device in the art can be used as a storage medium for a target folder in this embodiment.
  • the target folder is set in the file system of the SD card, and each category information corresponds to a unique target folder.
  • the target folder corresponding to the category information “person” is named 1 or “person” "
  • the target folder corresponding to the classification information "Landscape” is named 2 or "Landscape”.
  • the method further includes the following steps: detecting whether a target folder corresponding to the classification information exists in a file system of the SD card; if yes, saving the target image to the target folder; if not, creating the target folder The target folder corresponding to the category information and save the target picture to the target folder.
  • the target picture with the "person” classification information is moved to the target folder; after obtaining a target picture with the classified information as "car accident” First, check whether the corresponding target folder exists in the SD card. When the target folder corresponding to it is not detected, create a folder named "Car accident” or named 3 as the corresponding target folder, and then Move the target image with the "car accident” classification information to the newly created destination folder.
  • the micro in the driving recorder communicates with the SD card through the SPI (Serial Peripheral Interface) to establish a folder and store data in the SD card file system.
  • SPI Serial Peripheral Interface
  • the present invention further includes step S14: uploading the target picture in each target folder by radio waves in response to an external command, please refer to FIG. 4.
  • the peer-to-peer can be supported by Bluetooth or WIFI. -Hoc or WiFi Direct, SmartLink, etc.
  • the LAN built by the connection technology transmits the target picture to the mobile terminal.
  • the driving recorder can communicate with a mobile terminal such as a mobile phone or a PAD.
  • the embodiment is not limited to the transmission of the target picture. Under the condition that the traffic and the network bandwidth permit, the target folder corresponding to a certain category information of interest including a plurality of target pictures may be directly directly used.
  • the target picture can be uploaded through the local area network, so that the target picture can be transmitted to a certain device in the local area network, the picture file is transferred, and the picture file is effectively protected from being lost due to being overwritten.
  • the camera performs normal shooting
  • a snapping instruction based on the classification information of the screen feature is issued, and the target image is captured by the camera in response to the instruction; Adding the classification information to the attribute information of the target picture; and saving the target picture to a target folder corresponding to the classification information. Therefore, the special picture that is of interest to the user is captured based on a certain classification information, and is stored in a separate storage area corresponding to the classified information, and the problem that the video is easily covered by the video data when the video is stored in the same storage area does not occur.
  • the user when the user wants to find a special picture based on a certain category information, the user can directly access the folder corresponding to the category information, without spending a lot of manpower and time to quickly query all the videos by fast-forwarding and rewinding. obtain.
  • the present invention provides a terminal for classifying and storing the target image.
  • the terminal includes a capture module 11, an attribute setting module 12, and a storage module 13, by using the capture module 11.
  • the attribute setting module 12 and the storage module 13 construct a principle framework of the entire terminal, thereby implementing a modular implementation.
  • the specific functions implemented by each module are specifically disclosed below.
  • the capture module 11 is configured to obtain a target picture by capturing a camera by responding to a capture instruction with classification information.
  • the camera always captures scenery and road condition information along the way during the exercise of the automobile.
  • a snap instruction with the screen classification information can be directly issued.
  • the capture instruction may be a physical button or a touch panel that is set on the capture module 11, or may be a voice command.
  • the capture command is obtained by triggering a physical button or a touch panel disposed on the capture module 11, the physical button or the touch panel should be preset in plurality and each button needs to correspond to one of the classification information.
  • a voice command is preferably used as the capture instruction, wherein the natural language of the voice command issued by the user includes classification information.
  • the type of the classification information includes any number of types of characters, landscapes, car accidents, and road conditions.
  • the capture module 11 may further include a voice receiving module 111, a voice recognition module 112, and a processing module 113.
  • the voice receiving module 111 is configured to acquire voice stream data with classification information to be identified.
  • a microphone is preferably used as the voice receiving module 111 to acquire voice stream data of the user.
  • the sound collection direction of the voice receiving module 111 is optimal for the position of a certain seat in the vehicle.
  • the voice receiving range of the voice receiving module 111 is defined as the driver, that is, the module is placed closer to the driver's position to receive a voice signal having low interference and high signal to noise ratio.
  • the driver can issue a voice command of "character", "landscape", "car accident” or "road condition", in which "person", “landscape”, “car accident”, “road condition” For the classified information contained.
  • the voice analog signal recorded by the voice receiving module 111 is converted into digital voice stream data by A/D and then stored in a buffer of the processor core.
  • the voice recognition module 112 is configured to identify the voice stream data, and parse the category information in a string text format.
  • the speech recognition module 112 reads the sampled digital voice stream data from the buffer of the processor core by calling the read function, and performs identification and conversion into the classification information in the string text format.
  • the process of identifying the classification information from the voice stream data by the speech recognition module 112 can be implemented by two embodiments provided by the present invention.
  • the module may obtain the classification information of the string text format by being uploaded to the cloud server, or may be classified by the local voice library to obtain the classification of the string text format. information.
  • the voice recognition module 112 obtains the classification information of the string text format by uploading to the cloud server for identification, which specifically includes:
  • the voice recognition module 112 includes the acquired voice stream data into the voice recognition request and submits to the remote voice cloud server through the remote interface.
  • 112b Identify and parse the voice stream data in a voice recognition platform of the remote voice cloud server to obtain a string text.
  • the voice recognition module 112 and the voice cloud server use the Socket-based TCP protocol for communication, and adopt an asynchronous control method, so as to avoid blocking of the voice data stream and ensure voice.
  • the timely reporting of data streams provides users with a better control experience.
  • the voice cloud server is a processing platform with a voice library, and may be an independent server in the network, or a collection of multiple servers providing different voice recognition services.
  • the voice library may be provided by a separate server, or Integrated with a voice server.
  • the voice recognition module 112 obtains, by the remote interface, the classification information in a string text format obtained by responding to the voice recognition request and corresponding to parsing the voice stream data.
  • the voice recognition module 112 transmits a voice recognition request including the voice stream data and receives a string text obtained by the remote server and correspondingly parsing the voice stream data to determine
  • the classification information because the data in the remote server is more comprehensive and scientific, makes the classified information more scientific and accurate, and has universal adaptability, thereby avoiding misjudgment and further improving reliability.
  • the speech recognition module 112 is configured to perform the matching and identifying process with the local speech library to obtain the classification information of the string text format, which specifically includes:
  • the voice recognition module 112 performs matching and identification processing on the acquired voice stream data and the local voice library.
  • the voice recognition module 112 is used to call the local voice library, and the acquired voice stream data is matched and identified.
  • the speech recognition module 112 obtains classification information in a string text format that matches the voice stream data.
  • the voice library can be a local voice library formed by downloading and saving to a local voice cloud server.
  • the local voice library may be updated by communicating with the remote cloud server.
  • the capture module 11 of the present invention further includes a processing module 113, and the processing module 113 captures a target image corresponding to the classification information by capturing a camera.
  • the classification information of the target picture has been obtained from the voice instruction, and further, the processing module 113 calls the camera to capture the target picture corresponding to the classification information.
  • a USB camera is taken as an example here.
  • the calling of the camera capture by the processing module 113 to obtain the target image corresponding to the classification information may be implemented by using two embodiments.
  • the target picture is obtained by the processing module 113 invoking a photographing mode to trigger a photograph.
  • a USB driver for driving the camera is preloaded. It is not difficult to understand that the USB underlying operating library libusb can be called by the processing module 113 to communicate with the USB camera, provide USB control commands, switch the camera to the camera mode, and set the camera aperture, shutter, ISO and other parameters through software instructions.
  • the processing module 113 triggers the shutter of the camera to be pressed by the software instruction, and captures the target image.
  • the target picture is obtained by the processing module 113 intercepting a video image at a time point corresponding to when the capture instruction is issued. After responding to the capture instruction, the processing module 113 intercepts the video frame static data at the time point corresponding to the capture instruction by a certain interception algorithm to obtain the target picture.
  • the interception algorithm is well known to those skilled in the art and will not be described in detail herein.
  • the voice module only judges the voice from the voice command
  • the classified information is identified by the voice instruction.
  • the illegal user is prevented from controlling the terminal that implements the solution of the present invention to take a snapshot, which results in taking pictures that are not of interest to the user or even invading the privacy of others, occupying the storage space or causing unnecessary trouble. Therefore, the user's voice data is pre-acquired locally, and the voiceprint feature that uniquely identifies the user's identity can be extracted and saved locally.
  • the voice receiving module 111 first extracts the feature information of the voice data stream corresponding to the voice instruction, and performs the voiceprint feature with the local legal user pre-collected and pre-stored locally. Match, if the two match, the voice command is considered legal, otherwise it is illegal. Only when the instruction is legal, the subsequent recognition of the voice instruction by the voice recognition module 112 is performed, and the subsequent process of capturing the camera by the processing module 113 is started.
  • the target picture corresponding to the classification information is obtained by the capture module 11.
  • the present invention further includes an attribute setting module 12, and the attribute setting module 12 adds the classification information to the attribute information of the target picture.
  • the attribute setting module 12 further includes a compression module 121, a navigation information acquiring module 122, and an attribute loading module 123.
  • the compression module 121 is configured to compress the target image into a specific format file.
  • GIF is a lossless compression, using LZW compression algorithm for encoding, using 8-bit color compression, can only process up to 256 colors, not easy to save true color images
  • PNG is a lossless data compression bitmap graphics file format
  • JPEG is a widely used distortion compression standard method for photo images, using Huffman compression algorithm for destructive compression.
  • the compression module 121 preferably compresses the target picture into a JPEG format file.
  • the compression module 121 converts the captured target image data into a target image in the JPEG format by a Huffman compression algorithm.
  • the navigation information acquiring module 122 is configured to invoke the navigation module to acquire current navigation information.
  • the navigation information acquiring module 122 first needs to invoke the navigation module to acquire the current navigation information, so as to be subsequently loaded into the picture attribute.
  • the navigation module may be built in the driving recorder or may be an external navigation module, which is not limited by the present invention.
  • the navigation module may be a GPS navigation module or a Beidou satellite navigation.
  • the navigation module is a GPS navigation module.
  • the GPS navigation module obtains navigation information of the target image according to the NMEA-0182 protocol, or obtains navigation information of the target image by using a base station positioning manner.
  • the navigation information includes any one or any of a plurality of time, a geographical location, a driving direction, a driving speed, and a geographic latitude and longitude.
  • the navigation information acquisition module 122 first invokes the navigation module to obtain the current navigation information, which can be implemented by using two embodiments. The implementation process of each embodiment is specifically described below:
  • the navigation information acquisition module 122 invokes the GPS navigation module to obtain navigation information of the target picture according to the NMEA-0182 protocol.
  • the NMEA-0183 protocol is a standardized GPS data format protocol.
  • the data may include time, geographical location, longitude and latitude, driving direction, driving speed and the like, and the GPS navigation module acquires the satellite positioning signal from the GPS satellite and calculates the navigation data.
  • the navigation information obtaining module 122 analyzes and processes the ASCII code statement based on the NMEA-0183 protocol format received from the interface of the navigation module to obtain the navigation information.
  • the navigation information acquiring module 122 obtains the navigation information of the target image based on the base station positioning manner by calling the GPS navigation module, and the method is a technical means commonly used by those skilled in the art. This is not detailed.
  • the attribute loading module 123 is configured to add the navigation information and the classification information to the attribute information of the specific format picture file.
  • the attribute loading module 123 is further required to add the navigation information and the classification information to the attribute information of the file.
  • This embodiment uses the target picture in the JPEG format as an example to briefly describe the implementation method of the embodiment.
  • Exif (Exchangeable Image File) is an image file format.
  • the Exif format is a message inserted into the JPEG format header, which can load the aperture, shutter, balance white, ISO, focus, date, time and navigation information of the picture. Therefore, classification information and navigation information can be added to the Exif information of the obtained target picture.
  • the JPEG file begins with the string "0XFFD8" and ends with the string "0XFFD9” and is used between the string "OXFFE0-0XFFEF” for storing Exif information.
  • the navigation information and the classification information are added between the character string “OXFFE0-0XFFEF” in the process of compressing the obtained target image data in the RGB format into the target image in the JPEG format by the Huffman compression algorithm.
  • the attribute setting of the target picture in the present invention is implemented.
  • a file format such as PNG can also be adopted by the present invention, which is represented by the image file suffix name, which is .jpeg,. Jpg, .png, etc.
  • a memo form corresponding to all related picture files stored therein may be built in each target folder, and the picture file name and the navigation information are established in the table.
  • the mapping relationship data between the two types can solve the problem of the addition of the attribute information caused by the difference in the format, and the same can satisfy the requirements of the present invention.
  • the foregoing capture module 11 completes the acquisition of the target image and the attribute setting module 12 completes the attribute setting of the target image.
  • the present invention further includes a storage module 13, and the storage module 13 is configured to save the target image to a target folder corresponding to the classification information.
  • the present invention uses the SD card as a storage medium of the storage module 13 as an example to describe the present embodiment, but does not constitute the invention.
  • the SD card as a storage medium of the storage module 13 as an example to describe the present embodiment, but does not constitute the invention.
  • other prior art non-volatile memory devices can be used as the storage medium for the target folder in this embodiment.
  • the target folder is set in the file system of the SD card, and each category information corresponds to a unique target folder.
  • the target folder corresponding to the category information “person” is named 1 or “person” "
  • the target folder corresponding to the classification information "Landscape” is named 2 or "Landscape”.
  • the storage module 13 is further configured to detect whether the file system of the SD card exists. a destination folder corresponding to the classification information; if yes, the storage module 13 saves the target image to the target folder; if not, creates the target folder corresponding to the classification information through the storage module 13 And save the target image to the target folder.
  • the capture module 11 obtains a target image with the classification information as "person” and adds the attribute information through the attribute setting module 12, and detects whether the SD card exists in the storage module 13 through the storage module 13.
  • the storage module 13 moves the target picture with the classification information "person” to the target folder;
  • the storage module 13 first detects whether there is a target folder corresponding to the SD card, and when the target folder corresponding thereto is not detected, the storage module 13 establishes a target folder.
  • a folder named "Car Accident” or 3 is used as the corresponding destination folder, and the target picture with "Car Accident” is moved to the newly created destination folder.
  • the storage module 13 when the storage module 13 first classifies and stores the target image of a certain type of classification information, it is necessary to create a target folder corresponding to the classification information, and in the subsequent classification operation, directly move the target image to be classified to have been Some correspond to the target folder.
  • the storage module 13 communicates with the SD card through an SPI (Serial Peripheral Interface) serial peripheral interface to implement folder creation and storage of data in the SD card file system.
  • SPI Serial Peripheral Interface
  • the present invention further includes a transmitting module 14, please refer to FIG.
  • the sending module 14 is configured to upload a target picture in each target folder by radio waves in response to an external command.
  • the sending module is a Bluetooth module or a WIFI module. Due to the limited storage capacity in the SD card, when the capacity of the SD card is almost full, or when the user wants to transfer a certain target image of interest to a mobile terminal such as a mobile phone or a PAD, the peer-to-peer can be supported by a Bluetooth module or a WIFI module.
  • the LAN configured by the connection technology (AD-Hoc or WiFi Direct, Smartlink, etc.) transmits the target picture to the mobile terminal.
  • the transmitting module 14 can communicate with a mobile terminal such as a mobile phone or a PAD in advance.
  • the target image is not limited to be transmitted. Under the condition that the traffic of the sending module 14 or the network bandwidth is allowed, a certain category information of interest including a plurality of target pictures may be directly corresponding.
  • the destination folder is transferred to the mobile phone or mobile terminal.
  • the target picture can be uploaded through the local area network, so that the target picture can be transmitted to a certain device in the local area network to realize the transfer of the picture file, and the picture file can be effectively protected from being lost due to being covered.
  • the camera performs normal shooting
  • a snap command based on the classification information of the screen feature is issued, and the snap module 11 captures the target image through the camera capture in response to the instruction.
  • the special picture that is of interest to the user is captured based on a certain classification information, and is stored in a separate storage area corresponding to the classified information, and the problem that the video data is easily covered when the video is stored in the same storage area does not occur.
  • the user when the user wants to find a special picture based on a certain category information, the user can directly access the folder corresponding to the category information, without spending a lot of manpower and time to quickly query all the videos by fast-forwarding and rewinding. obtain.
  • the driving recorder installed on the automobile in which the technical solution of the present invention is implemented is in a power-on state, and any person in the cockpit can issue a voice command at any time.
  • the driver sends a “landscape” voice command
  • the driving recorder immediately recognizes the voice command, converts the corresponding information into “landscape” text information, captures the current car front screen, and stores it in the corresponding SD.
  • the "Landscape" target folder on the card the entire process from receiving voice commands to analysis to capturing to storage is completed. If the user's mobile phone and the driving recorder are in a point-to-point connection state, the driving recorder can also transfer the photographed image file to the mobile phone.
  • the present invention can quickly capture and classify storage according to user instructions under relatively safe conditions, and can realize acquisition and order organization of captured pictures in a very short time, especially suitable for human-computer interaction interface.
  • the terminal device In the terminal device.
  • the various component embodiments of the present invention may be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof.
  • a microprocessor or digital signal processor may be used in practice to implement some or all of the functionality of some or all of the components of the visual graphics encoding in accordance with embodiments of the present invention.
  • the invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for performing some or all of the methods described herein.
  • a program implementing the invention may be stored on a computer readable medium or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.
  • FIG. 9 illustrates a file encryption method and encryption with the file according to the present invention.
  • the method of intelligent electronic devices conventionally includes a processor 710 and a computer program product or computer readable medium in the form of a memory 720.
  • Memory 720 can be an electronic memory such as a flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM.
  • Memory 720 has a memory space 730 for program code 731 for performing any of the method steps described above.
  • storage space 730 for program code may include various program code 731 for implementing various steps in the above methods, respectively.
  • the program code can be read from or written to one or more computer program products.
  • Such computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks.
  • Such a computer program product is typically a portable or fixed storage unit as described with reference to FIG.
  • the storage unit may have a storage section or a storage space or the like arranged similarly to the storage 720 in the intelligent electronic device of FIG.
  • the program code can be compressed, for example, in an appropriate form.
  • the storage unit comprises a program 731' for performing the steps of the method according to the invention, ie code that can be read by a processor, such as 710, which, when run by the intelligent electronic device, causes the intelligent electronic device Perform the various steps in the method described above.

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Abstract

一种目标图片分类存储方法及其对应的终端，该目标图片分类存储方法包括步骤：响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片（S11）；将所述分类信息加入所述目标图片的属性信息中（S12）；将所述目标图片保存至与分类信息相对应的目标文件夹（S13）。还提供了一种采用上述方法的目标分类存储终端，其包括抓拍模块（11）、属性设置模块（12）和存储模块（13）。基于分类信息分类存储目标图片到对应的目标文件夹，当用户查找目标图片时，只需直接访问对应的目标文件夹，方便查找，提高用户的可操控性。

Description

目标图片分类存储方法及其终端 【技术领域】
本发明涉及智能终端图片存储技术领域，特别涉及一种目标图片分类存储方法及其对应的终端。
【背景技术】
行车记录仪可以记录车辆在行驶过程中的视频图像和声音，相当于车辆的黑匣子。用户开车时，开启行车记录仪上的摄像机，就可以通过摄像机拍摄沿途的风景或路况信息，然后将所拍摄的视频信息存储在本地的存储装置中或通过网络传输到云端。但是行车记录仪的存储空间有限，而视频数据的存储需要耗费大量的存储空间。同时，以这种视频数据来存储，用户需要寻找某类型或特定事件的图像时，需要花费大量的人力和时间。例如，在某一个场景中，当用户在拍摄的视频数据中查询某天某个时间段发生的某种交通事故时，只能手动快进快退浏览查询所有的录像，使用很不方便。
实际上，摄像机所拍摄的画面大部分是属于正常状态，如果能及时将用户感兴趣的特殊画面分类存储下来，不仅可以大大减少存储量和传输量，还方便用户搜索。然而，行车过程中，手控拍照是非常危险的。因而，在极短的时间内期望通过行车记录仪实现抓拍并对图片进行有序组织，对车主而言是非常困难的。
另一方面，存储在行车记录仪、智能摄像头之类的终端上的图片文件，在存储区域存满时，如果没有及时转移，通常会被新增的图片文件覆盖。图片文件通常占据较大的空间，通过移动通信网络提供的互联网接入直接向服务器上传图片文件，既未顾及车速过高导致的网络通信质量及效率的问题，还会产生高额的流量费用。
诚然，同样的问题不仅局限于行车记录仪，还包括其他不具有用户操作界面，或者用户并不方便及时操作的智能终端，例如智能摄像头、智能手表等。
【发明内容】
本发明的目的在于解决上述至少一个问题，提供了一种目标图片分类存储方法及其终端。
为实现该目的，本发明采用如下技术方案：
本发明提供的一种目标图片分类存储方法，包括以下步骤：
响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片；
将所述分类信息加入所述目标图片的属性信息中；
将所述目标图片保存至与分类信息相对应的目标文件夹。
本发明还提供了一种目标图片分类存储终端，包括有：
抓拍模块，用于响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片；
属性设置模块，用于将所述分类信息加入所述目标图片的属性信息中；
存储模块，用于将所述目标图片保存至与分类信息相对应的目标文件夹。
同时公开了一种计算机程序，包括计算机可读代码，当智能电子设备运行所述计算机可读代码时，导致上述方法被执行。
同时公开了一种计算机可读介质，其中存储了上述计算机程序。与现有技术相比，本发明具备如下优点：
1、本发明在摄像机进行正常拍摄的情况下，当用户希望保存某一画面时，发出基于该画面特征的分类信息的抓拍指令，响应于该指令通过摄像头抓拍获得目标图片；同时将所述分类信息加入所述目标图片的属性信息中；并将所述目标图片保存至与分类信息相对应的目标文件夹。从而实现基于某分类信息将用户感兴趣的特殊画面抓拍下来，保存在一个单独的与该分类信息相对应的存储区域，不会出现与视频保存在同一存储区域时易被视频数据覆盖的问题。而且，当用户想要基于某一分类信息查找特殊画面时，可直接访问与该分类信息相对应的文件夹而获得，而不用花费大量的人力和时间通过快进快退浏览查询所有的录像来获得。
2、本发明中抓拍指令为语音指令，从语音指令所含自然语言中确定所述人物、风景、车祸和路况等类型的分类信息。采用语音来作为抓拍指令，可避免出现当司机正在开车时，还需要用手去触发设置在行车记录仪端的物理 按键或触摸控键而易出现安全隐患的问题，可大大提高了用户体验度和安全性。
3、本发明在图片的属性中还设置有时间、地理位置、行车方向、行车速度、地理经纬度等导航信息。在抓拍的图片中设置导航信息和分类信息，方便用户更精确的查找。且当图片被上传到云服务器中后，可以与云端的搜索应用程序更好的配合，为其他用户提供更精确的图片搜索信息，提高搜索效率。
4、本发明进一步结合云端技术实现，通过发送包含所述语音流数据的语音识别请求并接收远程服务器反馈的对应解析该语音流数据而获得的字符串文本确定所述分类信息，由于远程服务器中的数据更全面科学，使得得到的分类信息也更加科学精确，具有普遍适应性，从而可以避免造成误判，进一步提高可靠性。
5、本发明进一步可将目标图片通过局域网进行上传，因而可以将目标图片传输给局域网内的某台设备，实现图片文件的转移，有效保护图片文件不因被覆盖而丢失。
本发明附加的方面和优点将在下面的描述中部分给出，这些将从下面的描述中变得明显，或通过本发明的实践了解到。
【附图说明】
本发明上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：
图1是本发明的目标图片分类存储方法的一个实施例的程序流程图；
图2是本发明的目标图片分类存储方法的又一个实施例的程序流程图；
图3是本发明的目标图片分类存储方法的另一个实施例的程序流程图；
图4是本发明的目标图片分类存储方法的一个实施例的程序流程图；
图5是本发明的目标图片分类存储终端的一个实施例的结构示意图；
图6是本发明的又一个实施例中抓拍模块的结构示意图；
图7是本发明的另一个实施例中属性设置模块的结构示意图；
图8是本发明的一个实施例的结构示意图；
图9示出了用于执行根据本发明的方法的智能电子设备的框图；以及
图10示出了用于保持或者携带实现根据本发明的方法的程序代码的存储单元示意图。
【具体实施方式】
下面结合附图和示例性实施例对本发明作进一步地描述，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，仅用于解释本发明，而不能解释为对本发明的限制。此外，如果已知技术的详细描述对于示出本发明的特征是不必要的，则将其省略。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本发明的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解，当我们称元件被“连接”或“耦接”到另一元件时，它可以直接连接或耦接到其他元件，或者也可以存在中间元件。此外，这里使用的“连接”或“耦接”可以包括无线连接或无线耦接。这里使用的措辞“和/或”包括一个或更多个相关联的列出项的全部或任一单元和全部组合。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)，具有与本发明所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语，应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像这里一样被特定定义，否则不会用理想化或过于正式的含义来解释。
本技术领域技术人员可以理解，这里所使用的“终端”、“终端设备”既包括无线信号接收器的设备，其仅具备无发射能力的无线信号接收器的设备，又包括接收和发射硬件的设备，其具有能够在双向通信链路上，执行双向通信的接收和发射硬件的设备。这种设备可以包括：蜂窝或其他通信设备，其具有单线路显示器或多线路显示器或没有多线路显示器的蜂窝或其他通信设备；PCS(Personal Communications Service，个人通信系统)，其可以 组合语音、数据处理、传真和/或数据通信能力；PDA(Personal Digital Assistant，个人数字助理)，其可以包括射频接收器、寻呼机、互联网/内联网访问、网络浏览器、记事本、日历和/或GPS(Global Positioning System，全球定位系统)接收器；常规膝上型和/或掌上型计算机或其他设备，其具有和/或包括射频接收器的常规膝上型和/或掌上型计算机或其他设备。这里所使用的“终端”、“终端设备”可以是便携式、可运输、安装在交通工具(航空、海运和/或陆地)中的，或者适合于和/或配置为在本地运行，和/或以分布形式，运行在地球和/或空间的任何其他位置运行。这里所使用的“终端”、“终端设备”还可以是通信终端、上网终端、音乐/视频播放终端，例如可以是PDA、MID(Mobile Internet Device，移动互联网设备)和/或具有音乐/视频播放功能的移动电话，也可以是智能电视、机顶盒等设备。
本技术领域技术人员可以理解，这里所使用的服务器、云端、远端网络设备等概念，具有等同效果，其包括但不限于计算机、网络主机、单个网络服务器、多个网络服务器集或多个服务器构成的云。在此，云由基于云计算(Cloud Computing)的大量计算机或网络服务器构成，其中，云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。本发明的实施例中，远端网络设备、终端设备与WNS服务器之间可通过任何通信方式实现通信，包括但不限于，基于3GPP、LTE、WIMAX的移动通信、基于TCP/IP、UDP协议的计算机网络通信以及基于蓝牙、红外传输标准的近距无线传输方式。
本发明的有关方法和终端的应用场景，是基于带有摄像头、处理器、通信模块和存储模块的行车记录仪为硬件基础，以安装有Linux系统的处理器的行车记录仪为例进行示例性说明，但应该说明的是，该描述仅是示例性的，本发明的范围并不限于此，本发明实施例的方法和终端也可适用于其他操作系统，本质上与操作系统无关。不难理解，本发明不仅局限于行车记录仪，还包括其他不具有用户操作界面，或者用户并不方便及时操作的智能终端，例如智能摄像头、智能手表等。
下面结合附图1来说明本发明提供的一种目标图片分类存储方法，其包括以下步骤：
S11，响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片。
本发明中行车记录仪在汽车的行使过程中，摄像头一直在拍摄沿途的风景和路况信息。当用户发现沿途中有某一感兴趣的画面需要抓拍下来时，可直接发出带有该画面分类信息的抓拍指令。所述的抓拍指令可以是触发设置在行车记录仪上的物理按键或触控面板，也可以是语音指令。当所述抓拍指令是通过触发设置在行车记录仪上的物理按键或触控面板得到时，所述物理按键或触控面板应预先设置多个且每个按键需对应于分类信息中的其中一类，以方便处理器从触发某一按键所得到的抓拍指令中得到所述的分类信息，但是在该方法中当司机正在开车时，还需要用手去触发设置在行车记录仪端的物理按键或触摸控键，易出现安全隐患。在本发明的其中一个实施例中，为了保证司机驾驶安全性，优选采用语音指令作为所述的抓拍指令，其中用户发出的语音指令的自然语言中包含有分类信息。具体的，所述分类信息所包含的类型包括人物、风景、车祸、路况各类型中的任意数量种类型。
参见附图2，在本发明的一个实施例中，该步骤S11具体还可以包括以下步骤：
S111，获取待识别的带有分类信息的语音流数据。
在一个实施例中，本发明优选采用麦克风作为语音录制设备来获取用户的语音流数据。其中，所述语音录制设备的声音采集方向对着车内某一个座椅的位置最佳。例如在一个实施例中，语音录制设备的声音接收范围限定为驾驶员，即麦克风设置在离驾驶员位置较近的地方，以接收到干扰小、信噪比高的语音信号。例如，驾驶员可以发出“人物拍”、“风景拍”、“车祸拍”或“路况拍”的语音指令，其中“人物”、“风景”、“车祸”、“路况”即为分类信息。语音录制设备录制的语音模拟信号经过A/D转换为数字语音流数据后再保存在处理器内核的缓冲区中。
S112，识别所述语音流数据，解析出字符串文本格式的分类信息。
语音流数据识别程序通过调用read函数从处理器内核的缓冲区中读取采样得到的数字语音流数据，并进行识别后转化为字符串文本格式的分类信息。从语音流数据识别出分类信息的过程，可以由本发明提供的两个实施例来实现。其中，该步骤既可以是上传到云服务器中识别而获得所述的字符串文本格式的分类信息，也可以是经过与本地语音库进行匹配识别处理来得到所述的字符串文本格式的分类信息。
如下揭示该过程的各个具体实例：
1、在本发明的一个实施例中，该步骤是通过上传到云服务器中识别而获得所述的字符串文本格式的分类信息，具体包括以下步骤：
S112a,语音流数据识别程序将获取的语音流数据包含到语音识别请求中通过远程接口提交到远程语音云服务器；
S112b,在远程语音云服务器的语音识别平台对该语音流数据进行识别和解析，得到字符串文本；
为了进一步增加本发明实施例中方法的稳定性，语音流数据识别程序和语音云服务器之间采用基于Socket的TCP协议进行通讯，并采用异步的控制方法，这样可以避免语音数据流的阻塞，保证语音数据流的及时上报，为用户提供更好的操控体验。其中，语音云服务器是带有语音库的处理平台，可以是网络中独立的服务器，也可以是多个提供不同的语音识别服务的服务器的集合，语音库可以由单独的服务器中提供，也可以与某一语音服务器集成在一起提供。
S112c,然后再通过该远程接口获取响应于该语音识别请求而反馈的对应解析该语音流数据而获得的字符串文本格式的分类信息。
不难理解，在实施例的方法中结合云端技术来实现，通过发送包含所述语音流数据的语音识别请求并接收远程服务器反馈的对应解析该语音流数据而获得的字符串文本以确定所述分类信息，由于远程服务器中的数据更全面科学，使得得到的分类信息也更加科学精确，具有普遍适应性，从而可以避免造成误判，进一步提高可靠性。
2、在本发明的又一个实施例中，该步骤是经过与本地语音库进行匹配识别处理来得到所述的字符串文本格式的分类信息，具体包括以下步骤：
S112A,将获取的语音流数据与本地语音库进行匹配识别处理。
在本地语音库中，预先存储有语音流数据与字符串文本呈映射关系的列表，该步骤中语音流数据识别程序调用本地语音库，将获取的语音流数据与其进行匹配识别处理。
S112B，获得与该语音流数据相匹配的字符串文本格式的分类信息。
本步骤中，通过遍历查找预先存储有语音流数据与字符串文本格式的分 类信息呈映射关系的列表，得到与语音流数据相匹配的的字符串文本格式的分类信息。当然，该语音库可以是从远程语音云服务器中下载保存至本地而形成的本地语音库。若本地语音库中没有查找到与该语音流数据对应的字符串文本格式的分类信息时，可以与远程云服务器实现通信更新本地语音库。
进一步的，本发明的方法还包括步骤S113，通过摄像头抓拍以获取与该分类信息对应的目标图片。
在前述步骤中，已经从语音指令中得到了目标图片的分类信息，进一步的要调用摄像头抓拍以获得与该分类信息对应的目标图片。为便于理解程序实现，此处以USB摄像头为例进行说明。而本步骤中调用摄像头抓拍以获得与该分类信息对应的目标图片具体可采用两个实施例来实现。
1、在本发明的一个实施例中，所述目标图片通过调用拍照模式触发拍照得到。在行车记录仪的带有Linux系统的处理器中，预先加载有驱动摄像头的USB驱动程序。不难理解，可以通过调用USB底层操作库libusb与USB摄像头实现通信，提供USB的控制指令，来切换摄像头为相机模式，并通过软件指令来设置相机光圈、快门、ISO等参数。当行车记录仪得到带有分类信息的抓拍指令后，会采用软件指令触发按下相机的快门，抓拍得到目标图片。
2、在本发明的另一个实施例中，所述目标图片通过截获抓拍指令发出时所对应时间点的视频图像而得到。在响应于抓拍指令后，将该抓拍指令发出时所对应的时间点的视频帧静态数据通过一定的截获算法截获，得到目标图片。其中，截获算法为本领域内技术人员的公知技术，在此不再详述。
在该步骤中，进一步的，还包括有仅当判断从所述语音指令的语音数据流提取的特征信息与本地预存的声纹特征相匹配时，才对所述语音指令进行分类信息识别。该步骤是为安全起见，防止非法用户控制实现了本发明的方案的终端进行抓拍，而导致拍到一些用户不需要的图片甚至是侵犯他人隐私的图片而占据存储空间或带来不必要的麻烦。因此，在本地要预先采集用户的语音数据，该数据中能提取出表征用户身份的唯一性的声纹特征并保存在本地。从而可以进一步在对语音指令进行分类信息识别之前，先提取该语音指令相对应的语音数据流的特征信息，将其与本地预先采集并预存到本地的合法用户的声纹特征进行匹配，如果两者相匹配，则视为该语音指令合法， 否则，则为非法。仅当该指令合法时，才对语音指令进行分类信息识别，进而启动通过摄像头抓拍的后续过程。
综上所述，通过以上步骤，得到了与分类信息相对应的目标图片。
进一步的，本发明的方法还包括步骤S12，将所述分类信息加入所述目标图片的属性信息中。
为了便于后续的分类存储和用户精确搜索，需要在得到的目标图片中加载与该目标图片的分类信息和导航信息。具体的，参见附图3，该步骤S12还包括：
S121，将所述目标图片压缩为特定格式文件。
由于采用相机模式抓拍或截获摄像机的静态图片得到的目标图片往往容量较大，为了减小图片的容量，在抓拍得到目标图片后需要采用Huffman、RLE(run-length encoding)、LZW(Lempel-Ziv-Welch Encoding)等压缩算法将目标图片压缩为特定的格式。众所周知，常用的现有技术中将图片压缩为JPEG(Joint Photographic Experts Group)、GIF(Graphics Interchange Format)或PNG(Portable Network Graphics)格式。其中，GIF是一种无损压缩，采用LZW压缩算法进行编码，采用了8位色压缩，最多只能处理256种颜色，不易于保存真彩图像；PNG是一种无损数据压缩位图图形文件格式，同样缺点和GIF一样，不利于图片的优化处理，且文件容量较其他格式要大；JPEG是一种针对相片影像而广泛使用的一种失真压缩标准方法，采用Huffman压缩算法进行破坏性压缩，首先把图片从RGB转换为YUV，用亮度、色调和饱和度储存每个象素的信息。然后减少色调和饱和度的信息数量，这种差别不容易被肉眼察觉到，但是图像字节数会大幅减小。因此，在本发明的一个实施例中，优选将所述目标图片压缩为JPEG格式文件。在一个实施例中，将抓拍得到的目标图片数据，通过Huffman压缩算法转换为JPEG格式的目标图片。
S122，调用导航模块获取当前导航信息。
在图片压缩为特定格式的图片格式时，需要先调用导航模块来获取当前导航信息，以备后续将该导航信息加载到图片属性中。需要说明的是，所述导航模块可以是内置在行车记录仪中，也可以是外置的导航模块，本发明对此不作限定。进一步的，所述导航模块可以是GPS导航模块或北斗卫星导航。 例如在本发明的一个实施例中，所述导航模块为GPS导航模块。可选的，所述GPS导航模块依据NMEA-0182协议获得目标图片的导航信息，或通过基站定位方式获得目标图片的导航信息。具体的，所述导航信息包括时间、地理位置、行车方向、行车速度、地理经纬度中的任意一种或任意多种。该步骤中通过调用导航模块来获取当前导航信息可采用两个实施例来实现，下文具体说明各实施例的实现过程：
1、在本发明的一个实施例中，所述GPS导航模块依据NMEA-0182协议获得目标图片的导航信息。具体的，NMEA-0183协议是规范的GPS数据格式协议。其中可包括时间、地理位置、经度和纬度、行车方向、行车速度等数据，GPS导航模块从GPS卫星获取卫星定位信号，并解算出导航数据。GPS导航模块中的处理模块分析和处理接收到的基于NMEA-0183协议格式的ASCII码语句，得到导航信息。
2、在本发明的另一的实施例中，所述GPS导航模块通过基站定位方式获得目标图片的导航信息，该方法为本领域内技术人员常用的技术手段，在此不再详述。
S123，将所述导航信息与分类信息添加到该文件的属性信息中。
通过以上步骤得到导航信息后，进一步的，需要将所述导航信息和分类信息添加到该文件的属性信息中。本实施例以JPEG格式的目标图片为例来简要说明该步骤的实现方法。
本领域技术人员应该知晓，JPEG格式的图片属性设置在图片的Exif信息中。Exif(Exchangeable Image File)是一种图像文件格式。实际上Exif格式就是JPEG格式头插入了图片的信息，可以加载图片拍摄的光圈、快门、平衡白、ISO、聚焦、日期、时间及导航信息。因此可以在得到的目标图片的Exif信息中加入分类信息和导航信息。在一个具体的实施例中，JPEG文件以字符串“0XFFD8”开头，并以字符串“0XFFD9”结束，而在字符串“OXFFE0-0XFFEF”之间用于存储Exif信息。在一个实施例中，在将得到的RGB格式的目标图片数据通过Huffman压缩算法压缩为JPEG格式的目标图像过程中，将所述的导航信息和分类信息添加在字符串“OXFFE0-0XFFEF”之间的Exif信息中，即实现了本发明中目标图片的属性设置。
需要指出的是，尽管本发明以JPEG文件格式进行示例，但本领域技术人 员应当理解，PNG之类的文件格式也可以被本发明采用，表现在图片文件后缀名上，便是.jpeg、.jpg，.png等。某些实施例中，对于并不支持EXIF的图片格式文件，可以在各个目标文件夹中构建与存储于其中的所有相关图片文件相对应的备注表格，在该表格建立图片文件名与上述导航信息之间的映射关系数据，解决格式差异引起的属性信息添加的障碍，同理可以满足本发明的需求。
综上所述，前述方法步骤完成了目标图片的获取和目标图片的属性设置。
进一步的，本发明的方法还包括步骤S13，将所述目标图片保存至与分类信息相对应的目标文件夹。
具体的，为了单独存储与分类信息相对应的目标文件夹，在一个实施例中，本发明以SD卡作为存储介质为例来说明其实施方式，但是并不构成对该发明的限制，其他现有技术中非易失性存储装置均可作为该实施例中目标文件夹的存储介质。
进一步的，所述目标文件夹被设置在SD卡的文件系统中，且每个分类信息对应一个唯一的目标文件夹，例如，分类信息“人物”所对应的目标文件夹名为1或“人物”，分类信息“风景”所对应的目标文件夹名为2或“风景”。具体的，还包括以下步骤：检测SD卡的文件系统中是否存在所述分类信息对应的目标文件夹；若为是，将该目标图片保存至该目标文件夹；若为否，则创建与该分类信息相对应的所述目标文件夹并将该目标图片保存至该目标文件夹。例如在本发明的一个实施例中，在获得了一个带有分类信息的“人物”的目标图片并添加完属性信息后，检测SD卡中是否存在与其对应的目标文件夹，待检测到存在文件夹名为“人物”或1的目标文件夹后，将所述带有“人物”分类信息的目标图片移至该目标文件夹；在获得了一个带有分类信息为“车祸”的目标图片后，先检测SD卡中是否存在与其对应的目标文件夹，当没有检测到与其对应的目标文件夹时，建立一个名为“车祸”或名为3的文件夹作为与其对应的目标文件夹，再将该带有“车祸”分类信息的目标图片移至该新建的目标文件夹。
也就是说，在首次分类存储某一类分类信息的目标图片时需要创建与其分类信息相对应的目标文件夹，在后续的分类操作中，直接将待分类的目标图片移动至已有的对应目标文件夹中即可。在本实施中，行车记录仪中的微 控制器通过SPI(Serial Peripheral Interface串行外设接口)与SD卡实现通信，来实现在SD卡文件系统中建立文件夹和存储入数据，该技术的具体实施方式是本领域内技术人员的公知技术，在此不再详述。
进一步的，为了使图片文件及时转移，本发明还包括步骤S14：响应于外部指令通过无线电波上传各目标文件夹中的目标图片，请参阅图4。
由于SD卡中的存储容量有限，当SD卡的容量快满时，或者用户希望将某一感兴趣的目标图片传输到手机、PAD等移动终端上时，可以通过蓝牙或WIFI等支持点对点(AD-Hoc或WiFi Direct、SmartLink等)连接技术而构建的局域网传输所述目标图片到移动终端上，当然，前提是行车记录仪能与手机或PAD等移动终端实现通信。需要说明的是，本实施例也并不限定为传输目标图片，在流量和网络带宽允许的条件下，亦可直接将包含有若干张目标图片的某一感兴趣的分类信息对应的目标文件夹传输给手机或移动终端。通过该步骤，可将目标图片通过局域网进行上传，因而可以将目标图片传输给局域网内的某台设备，实现图片文件的转移，有效保护图片文件不因被覆盖而丢失。
综上所述，本发明在摄像机进行正常拍摄的情况下，当用户希望保存某一画面时，发出基于该画面特征的分类信息的抓拍指令，响应于该指令通过摄像头抓拍获得目标图片；并同时将所述分类信息加入所述目标图片的属性信息中；并将所述目标图片保存至与分类信息相对应的目标文件夹。从而实现基于某分类信息将用户感兴趣的特殊画面抓拍下来，保存在一个单独的与该分类信息相对应的存储区域，不会出现与视频保存在同一存储区域时易被视频数据覆盖的问题。而且，当用户想要基于某一分类信息查找特殊画面时，可直接访问与该分类信息相对应的文件夹而获得，而不用花费大量的人力和时间通过快进快退浏览查询所有的录像来获得。
进一步，依据计算机软件的功能模块化思维，本发明提供一种目标图片分类存储的终端，请参阅图5，该终端包括抓拍模块11、属性设置模块12和存储模块13，利用该抓拍模块11、属性设置模块12和存储模块13来搭建起整个终端的原理框架，从而实现模块化实施方案。以下具体揭示各模块实现的具体功能。
所述抓拍模块11，用于响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片。
本发明中行车记录仪在汽车的行使过程中，摄像头一直在拍摄沿途的风景和路况信息。当用户发现沿途中有某一感兴趣的画面需要抓拍下来时，可直接发出带有该画面分类信息的抓拍指令。所述的抓拍指令可以是触发设置在抓拍模块11上的物理按键或触控面板，也可以是语音指令。当所述抓拍指令是通过触发设置在抓拍模块11上的物理按键或触控面板得到时，所述物理按键或触控面板应预先设置多个且每个按键需对应于分类信息中的其中一类，以方便处理器从触发某一按键所得到的抓拍指令中得到所述的分类信息，但是在该方法中当司机正在开车时，还需要用手去触发设置在抓拍模块11上的物理按键或触摸控键，易出现安全隐患。在本发明的其中一个实施例中，为了保证司机驾驶安全性，优选采用语音指令作为所述的抓拍指令，其中用户发出的语音指令的自然语言中包含有分类信息。具体的，所述分类信息所包含的类型包括人物、风景、车祸、路况各类型中的任意数量种类型。
参见附图6，在本发明的一个实施例中，该抓拍模块11还可以包括有语音接收模块111、语音识别模块112和处理模块113。
所述语音接收模块111，用于获取待识别的带有分类信息的语音流数据。
在本发明的一个实施例中，优选采用麦克风作为语音接收模块111来获取用户的语音流数据。其中，所述语音接收模块111的声音采集方向对着车内某一个座椅的位置最佳。例如在一个实施例中，语音接收模块111的声音接收范围限定为驾驶员，即该模块设置在离驾驶员位置较近的地方，以接收到干扰小、信噪比高的语音信号。例如在具体应用时，驾驶员可以发出“人物拍”、“风景拍”、“车祸拍”或“路况拍”的语音指令，其中“人物”、“风景”、“车祸”、“路况”即为所包含的分类信息。语音接收模块111录制的语音模拟信号经过A/D转换为数字语音流数据后再保存在处理器内核的缓冲区中。
所述语音识别模块112，用于识别所述语音流数据，解析出字符串文本格式的分类信息。
语音识别模块112通过调用read函数从处理器内核的缓冲区中读取采样得到的数字语音流数据，并进行识别后转化为字符串文本格式的分类信息。 通过语音识别模块112从语音流数据识别出分类信息的过程，可以由本发明提供的两个实施例来实现。其中，该模块既可以是通过上传到云服务器中识别而获得所述的字符串文本格式的分类信息，也可以是经过与本地语音库进行匹配识别处理来得到所述的字符串文本格式的分类信息。
如下揭示该模块的各个具体实例：
1、在本发明的一个实施例中，该语音识别模块112是通过上传到云服务器中识别而获得所述的字符串文本格式的分类信息，具体包括：
112a,语音识别模块112将获取的语音流数据包含到语音识别请求中通过远程接口提交到远程语音云服务器。
112b,在远程语音云服务器的语音识别平台对该语音流数据进行识别和解析，得到字符串文本。
为了进一步增加本发明实施例中模块的稳定性，语音识别模块112和语音云服务器之间采用基于Socket的TCP协议进行通讯，并采用异步的控制方法，这样可以避免语音数据流的阻塞，保证语音数据流的及时上报，为用户提供更好的操控体验。其中，语音云服务器是带有语音库的处理平台，可以是网络中独立的服务器，也可以是多个提供不同的语音识别服务的服务器的集合，语音库可以由单独的服务器中提供，也可以与某一语音服务器集成在一起提供。
112c,然后语音识别模块112再通过该远程接口获取响应于该语音识别请求而反馈的对应解析该语音流数据而获得的字符串文本格式的分类信息。
不难理解，在实施例中结合云端技术来实现，通过语音识别模块112发送包含所述语音流数据的语音识别请求并接收远程服务器反馈的对应解析该语音流数据而获得的字符串文本以确定所述分类信息，由于远程服务器中的数据更全面科学，使得得到的分类信息也更加科学精确，具有普遍适应性，从而可以避免造成误判，进一步提高可靠性。
2、在本发明的又一个实施例中，该语音识别模块112是经过与本地语音库进行匹配识别处理来得到所述的字符串文本格式的分类信息，具体包括：
112A,语音识别模块112将获取的语音流数据与本地语音库进行匹配识别处理。
在本地语音库中，预先存储有语音流数据与字符串文本呈映射关系的列表，采用语音识别模块112调用本地语音库，将获取的语音流数据与其进行匹配识别处理。
112B，语音识别模块112获得与该语音流数据相匹配的字符串文本格式的分类信息。
本实施例中，通过遍历查找预先存储有语音流数据与字符串文本格式的分类信息呈映射关系的列表，得到与语音流数据相匹配的的字符串文本格式的分类信息。当然，该语音库可是从远程语音云服务器中下载保存至本地而形成的本地语音库。当本地语音库中没有查找到与该语音流数据对应的字符串文本格式的分类信息时，可以与远程云服务器实现通信更新本地语音库。
进一步的，本发明中抓拍模块11还包括处理模块113，所述处理模块113通过摄像头抓拍以获取与该分类信息对应的目标图片。
在前述的语音识别模块112中，已经从语音指令中得到了目标图片的分类信息，进一步的要通过处理模块113调用摄像头抓拍以获得与该分类信息对应的目标图片。为便于理解该模块的实现，此处以USB摄像头为例进行说明。而通过处理模块113调用摄像头抓拍以获得与该分类信息对应的目标图片具体可采用两个实施例来实现。
1、在本发明的一个实施例中，所述目标图片通过处理模块113调用拍照模式触发拍照得到。在行车记录仪的带有Linux系统的处理器中，预先加载有驱动摄像头的USB驱动程序。不难理解，可以通过处理模块113调用USB底层操作库libusb与USB摄像头实现通信，提供USB的控制指令，来切换摄像头为相机模式，并通过软件指令来设置相机光圈、快门、ISO等参数。当语音接收模块111得到带有分类信息的抓拍指令后，处理模块113会采用软件指令触发按下相机的快门，抓拍得到所述目标图片。
2、在本发明的另一个实施例中，所述目标图片通过处理模块113截获抓拍指令发出时所对应时间点的视频图像而得到。在响应于抓拍指令后，处理模块113将该抓拍指令发出时所对应的时间点的视频帧静态数据通过一定的截获算法截获，得到所述目标图片。其中，截获算法为本领域内技术人员的公知技术，在此不再详述。
在该模块中，进一步的，所述语音模块仅当判断从所述语音指令的语音 数据流提取的特征信息与本地预存的声纹特征相匹配时，才对所述语音指令进行分类信息识别。为了安全起见，防止非法用户控制实现了本发明的方案的终端进行抓拍，而导致拍到一些用户不感兴趣的图片甚至是侵犯他人隐私的图片而占据存储空间或带来不必要的麻烦。因此，在本地要预先采集用户的语音数据，该数据中能提取出表征用户身份的唯一性的声纹特征并保存在本地。从而可以进一步在对语音指令进行分类信息识别之前，语音接收模块111先提取该语音指令相对应的语音数据流的特征信息，将其与本地预先采集并预存到本地的合法用户的声纹特征进行匹配，如果两者相匹配，则视为该语音指令合法，否则，则为非法。仅当该指令合法时，才通过语音识别模块112执行后续的对语音指令进行分类信息识别，进而通过处理模块113启动摄像头抓拍的后续过程。
综上所述，通过抓拍模块11得到了与分类信息相对应的的目标图片。
进一步的，本发明还包括有属性设置模块12，所述属性设置模块12将所述分类信息加入所述目标图片的属性信息中。
为了便于后续的分类存储和用户精确搜索，需要在得到的目标图片中加载与该目标图片的分类信息和导航信息。具体的，参见附图7，在本发明的一个实施例中，所述属性设置模块12还包括有压缩模块121、导航信息获取模块122和属性加载模块123。
所述压缩模块121，用于将所述目标图片压缩为特定格式文件。
由于采用相机模式抓拍或截获摄像机的静态图片得到的目标图片往往容量较大，为了减小图片的容量，在抓拍得到目标图片后需要采用Huffman、RLE(run-length encoding)、LZW(Lempel-Ziv-Welch Encoding)等压缩算法将目标图片压缩为特定的格式。众所周知，常用的现有技术将图片压缩为JPEG(Joint Photographic Experts Group)、GIF(Graphics Interchange Format)或PNG(Portable Network Graphics)格式。众所周知，GIF是一种无损压缩，采用LZW压缩算法进行编码，采用了8位色压缩，最多只能处理256种颜色，不易于保存真彩图像；PNG是一种无损数据压缩位图图形文件格式，同样缺点和GIF一样，不利于图片的优化处理，且文件容量较其他格式要大；JPEG是一种针对相片影像而广泛使用的一种失真压缩标准方法，采用Huffman压缩算法进行破坏性压缩，首先把图片从RGB转换为YUV，用 亮度、色调和饱和度储存每个象素的信息。然后减少色调和饱和度的信息数量，这种差别不容易被肉眼察觉到，但是图像字节数会大幅减小。因此，在本发明的一个实施例中，所述压缩模块121优选将所述目标图片压缩为JPEG格式文件。在本发明的一个实施例中，压缩模块121将抓拍得到的目标图片数据，通过Huffman压缩算法转换为JPEG格式的目标图片。
所述导航信息获取模块122，用于调用导航模块获取当前导航信息。
在前述中压缩模块121将图片压缩为特定格式的图片格式时，需要导航信息获取模块122先调用导航模块来获取当前导航信息，以备后续将该导航信息加载到图片属性中。需要说明的是，所述导航模块可以是内置在行车记录仪中，也可以是外置的导航模块，本发明对此不作限定。进一步的，所述导航模块可以是GPS导航模块或北斗卫星导航。例如在本发明的一个实施例中，所述导航模块为GPS导航模块。可选的，所述GPS导航模块依据NMEA-0182协议获得目标图片的导航信息，或通过基站定位方式获得目标图片的导航信息。具体的，所述导航信息包括时间、地理位置、行车方向、行车速度、地理经纬度中的任意一种或任意多种。通过导航息获取模块122先调用导航模块来获取当前导航信息可采用两个实施例来实现，下文具体说明各实施例的实现过程：
1、在本发明的一个实施例中，通过导航信息获取模块122调用GPS导航模块依据NMEA-0182协议获得目标图片的导航信息。具体的，NMEA-0183协议是规范的GPS数据格式协议。其中可包括时间、地理位置、经度和纬度、行车方向、行车速度等数据，GPS导航模块从GPS卫星获取卫星定位信号，并解算出导航数据。导航信息获取模块122分析和处理从导航模块的接口接收到的基于NMEA-0183协议格式的ASCII码语句，得到所述导航信息。
2、在本发明的另一的实施例中，所述导航信息获取模块122通过调用GPS导航模块基于基站定位方式获得目标图片的导航信息，该方法为本领域内技术人员常用的技术手段，在此不再详述。
所述属性加载模块123，用于将所述导航信息与分类信息添加到该特定格式图片文件的属性信息中。
通过前述导航信息获取模块122得到导航信息后，进一步的，还需要采用属性加载模块123将所述导航信息和分类信息添加到该文件的属性信息 中。本实施例以JPEG格式的目标图片为例来简要说明该实施例的实现方法。
本领域技术人员应该知晓，JPEG格式的图片属性设置在图片的Exif信息中。Exif(Exchangeable Image File)是一种图像文件格式。实际上Exif格式就是在JPEG格式头插入了图片的信息，可以加载图片拍摄的光圈、快门、平衡白、ISO、聚焦、日期、时间及导航信息。因此可以在得到的目标图片的Exif信息中加入分类信息和导航信息。在一个具体的实施例中，JPEG文件以字符串“0XFFD8”开头，并以字符串“0XFFD9”结束，而在字符串“OXFFE0-0XFFEF”之间用于存储Exif信息。在一个实施例中，在将得到的RGB格式的目标图片数据通过Huffman压缩算法压缩为JPEG格式的目标图像过程中，将所述的导航信息和分类信息添加在字符串“OXFFE0-0XFFEF”之间的Exif信息中，即实现了本发明中目标图片的属性设置。
需要指出的是，尽管本发明以JPEG文件格式进行示例，但本领域技术人员应当理解，PNG之类的文件格式也可以被本发明采用，表现在图片文件后缀名上，便是.jpeg、.jpg，.png等。某些实施例中，对于并不支持EXIF的图片格式文件，可以在各个目标文件夹中构建与存储于其中的所有相关图片文件相对应的备注表格，在该表格建立图片文件名与上述导航信息之间的映射关系数据，解决格式差异引起的属性信息添加的障碍，同理可以满足本发明的需求。
综上所述，前述抓拍模块11完成了目标图片的获取和属性设置模块12完成了目标图片的属性设置。
进一步的，本发明还包括有存储模块13，所述的存储模块13，被配置为将所述目标图片保存至与分类信息相对应的目标文件夹。
具体的，为了单独存储与分类信息相对应的目标文件夹，在一个实施例中，本发明以SD卡作为该存储模块13的存储介质为例来说明本实施方式，但是并不构成对该发明的限制，其他现有技术中非易失性存储装置均可作为该实施例中目标文件夹的存储介质。
进一步的，所述目标文件夹被设置在SD卡的文件系统中，且每个分类信息对应一个唯一的目标文件夹，例如，分类信息“人物”所对应的目标文件夹名为1或“人物”，分类信息“风景”所对应的目标文件夹名为2或“风景”。具体的，所述存储模块13还配置为检测SD卡的文件系统中是否存在 所述分类信息对应的目标文件夹；若为是，存储模块13将该目标图片保存至该目标文件夹；若为否，则通过存储模块13创建与该分类信息相对应的所述目标文件夹并将该目标图片保存至该目标文件夹。例如在本发明的一个实施例中，抓取模块11在获得了一个带有分类信息为“人物”的目标图片并通过属性设置模块12添加完属性信息，通过存储模块13检测SD卡中是否存在与其对应的目标文件夹，待检测到存在文件夹名为“人物”或1的目标文件夹后，存储模块13将所述带有分类信息“人物”的目标图片移至该目标文件夹；在获得了一个带有分类信息为“车祸”的目标图片后，存储模块13先检测SD卡中是否存在与其对应的目标文件夹，当没有检测到与其对应的目标文件夹时，存储模块13建立一个名为“车祸”或为3的文件夹作为与其对应的目标文件夹，再将该带有“车祸”的目标图片移至该新建的目标文件夹。
也就是说，在存储模块13首次分类存储某一类分类信息的目标图片时需要创建与该分类信息相对应的目标文件夹，在后续的分类操作中，直接将待分类的目标图片移动至已有的对应目标文件夹中即可。在本实施中，存储模块13通过SPI(Serial Peripheral Interface)串行外设接口与SD卡实现通信，来实现在SD卡文件系统中建立文件夹和存储入数据，该技术的具体实施方式是本领域内技术人员的公知技术，在此不再详述。
进一步的，为了图片文件及时转移，本发明还包括有发送模块14，请参见附图8。所述发送模块14，用于响应于外部指令通过无线电波上传各目标文件夹中的目标图片。可选的，所述发送模块为蓝牙模块或WIFI模块。由于SD卡中的存储容量有限，当SD卡的容量快满时，或者用户希望将某一感兴趣的目标图片传输到手机、PAD等移动终端上时，可以通过蓝牙模块或WIFI模块等支持点对点(AD-Hoc或WiFi Direct、Smartlink等)连接技术而构建的局域网传输所述目标图片到移动终端上，当然，前提是发送模块14预先能与手机或PAD等移动终端实现通信。需要说明的是，本实施例也并不限定为传输目标图片，在发送模块14的流量或网络带宽允许的条件下，亦可直接将包含有若干张目标图片的某一感兴趣的分类信息对应的目标文件夹传输给手机或移动终端。通过该发送模块14，可将目标图片通过局域网进行上传，因而可以将目标图片传输给局域网内的某台设备，实现图片文件的转移，有效保护图片文件不因被覆盖而丢失。
综上所述，本发明在摄像机进行正常拍摄的情况下，当用户希望保存某一画面时，发出基于该画面特征的分类信息的抓拍指令，抓拍模块11响应于该指令通过摄像头抓拍获得目标图片；并同时通过属性设置模块12将所述分类信息加入所述目标图片的属性信息中；并通过存储模块13将所述目标图片保存至与分类信息相对应的目标文件夹。从而实现基于某分类信息将用户感兴趣的的特殊画面抓拍下来，保存在一个单独的与该分类信息相对应的存储区域，不会出现与视频保存在同一存储区域时易被视频数据覆盖的问题。而且，当用户想要基于某一分类信息查找特殊画面时，可直接访问与该分类信息相对应的文件夹而获得，而不用花费大量的人力和时间通过快进快退浏览查询所有的录像来获得。
在本发明的一个应用场景中，实施了本发明的技术方案的安装在汽车上的行车记录仪处于开机状态，驾驶舱内的任何人员任何时候，均可发出语音指令。汽车行驶过程中，由驾驶员发出“风景拍”语音指令，行车记录仪即刻识别该语音指令，将其对应转换为“风景拍”文本信息，抓拍当前车前方画面，将其存储到对应的SD卡上的“风景”目标文件夹中，完成从接收语音指令到分析到抓拍到存储的全过程。如果用户手机与行车记录仪处于点对点连接状态时，则行车记录仪还能将拍摄完成的图片文件传输到该手机中。
概而言之，本发明能够在相对安全的情况下，根据用户指令快速抓拍并分类存储，能够在极短时间内实现对抓拍图片的获取和有序组织，尤其适用于人机交互界面不够友好的终端设备中。
本发明的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本发明实施例的移动终端处理可视化图形编码中的一些或者全部部件的一些或者全部功能。本发明还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如，计算机程序和计算机程序产品)。这样的实现本发明的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
例如，图9示出了可以实现根据本发明的文件加密方法及与该文件加密 的方法的智能电子设备。该智能电子设备传统上包括处理器710和以存储器720形式的计算机程序产品或者计算机可读介质。存储器720可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM、硬盘或者ROM之类的电子存储器。存储器720具有用于执行上述方法中的任何方法步骤的程序代码731的存储空间730。例如，用于程序代码的存储空间730可以包括分别用于实现上面的方法中的各种步骤的各个程序代码731。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，紧致盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为如参考图10所述的便携式或者固定存储单元。该存储单元可以具有与图9的智能电子设备中的存储器720类似布置的存储段或者存储空间等。程序代码可以例如以适当形式进行压缩。通常，存储单元包括用于执行根据本发明的方法步骤的程序731’，即可以由例如诸如710之类的处理器读取的代码，这些代码当由智能电子设备运行时，导致该智能电子设备执行上面所描述的方法中的各个步骤。
在此处所提供的说明书中，虽然说明了大量的具体细节。然而，能够理解，本发明的实施例可以在没有这些具体细节的情况下实践。在一些实施例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
虽然上面已经示出了本发明的一些示例性实施例，但是本领域的技术人员将理解，在不脱离本发明的原理或精神的情况下，可以对这些示例性实施例做出改变，本发明的范围由权利要求及其等同物限定。

Claims (34)

  1. 一种目标图片分类存储方法，其特征在于，包括以下步骤：
    响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片；
    将所述分类信息加入所述目标图片的属性信息中；
    将所述目标图片保存至与分类信息相对应的目标文件夹。
  2. 根据权利要求1所述的方法，其特征在于：所述抓拍指令是语音指令，所述分类信息从语音指令所含自然语言中确定。
  3. 根据权利要求1所述的方法，其特征在于：所述响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片的步骤，具体包括：
    获取待识别的带有分类信息的语音流数据；
    识别所述语音流数据，解析出字符串文本格式的分类信息；
    通过摄像头抓拍以获取与该分类信息对应的目标图片。
  4. 根据权利要求3所述的方法，其特征在于：所述识别所述语音流数据，解析出字符串文本格式的分类信息的步骤，包括：
    将获取的语音流数据包含到语音识别请求中通过远程接口提交；
    通过该远程接口获取响应于该语音识别请求而反馈的对应解析该语音流数据而获得的字符串文本格式的分类信息。
  5. 根据权利要求1所述的方法，其特征在于：所述识别所述语音流数据，解析出字符串文本格式的分类信息的步骤，包括：
    将获取的语音流数据与本地语音库进行匹配识别处理；
    获得与该语音流数据相匹配的字符串文本格式的分类信息。
  6. 根据权利要求1所述的方法，其特征在于：将所述分类信息加入所述目标图片的属性信息中的步骤，还包括：
    将所述目标图片压缩为特定格式文件；
    调用导航模块获取当前导航信息；
    将所述导航信息与分类信息添加到该文件的属性信息中。
  7. 根据权利要求1所述的方法，其特征在于：所述目标文件夹建立在SD卡上。
  8. 根据权利要求1所述的方法，其特征在于，将所述目标图片保存至与 分类信息相对应的目标文件夹的步骤，包括：
    检测是否存在所述分类信息对应的目标文件夹；
    若为是，将该目标图片保存至该目标文件夹；
    若为否，则创建与该分类信息相对应的所述目标文件夹并将该目标图片保存至该目标文件夹。
  9. 根据权利要求6所述的方法，其特征在于：所述导航模块依据NMEA-0182协议获得目标图片的导航信息，或通过基站定位方式获得目标图片的导航信息。
  10. 根据权利要求6所述的方法，其特征在于：所述导航信息和分类信息被添加到所述目标图片的EXIF信息中。
  11. 根据权利要求6所述的方法，其特征在于，所述特定格式文件的后缀名为JPG、JPEG、PNG中任意一项。
  12. 根据权利要求1所述的方法，其特征在于：所述目标图片通过调用拍照模式触发拍照得到；或通过截获抓拍指令发出时所对应时间点的视频图像而得到。
  13. 根据权利要求1所述的方法，其特征在于：所述分类信息所包含的类型包括人物、风景、车祸、路况各类型中的任意数量种类型。
  14. 根据权利要求6所述的方法，其特征在于：所述导航信息包括时间、地理位置、行车方向、行车速度、地理经纬度中的任意一种或任意多种。
  15. 根据权利要求1所述的方法，还包括步骤：响应于外部指令通过局域网上传各目标文件夹中的目标图片。
  16. 根据权利要求2所述的方法，其特征在于，仅当判断从所述语音指令的语音数据流提取的特征信息与本地预存的声纹特征相匹配时，才对所述语音指令进行分类信息识别。
  17. 一种目标图片分类存储终端，其特征在于，包括有：
    抓拍模块，用于响应于带有分类信息的抓拍指令，通过摄像头抓拍获得目标图片；
    属性设置模块，用于将所述分类信息加入所述目标图片的属性信息中；
    存储模块，用于将所述目标图片保存至与分类信息相对应的目标文件夹。
  18. 根据权利要求17所述的终端，其特征在于：所述抓拍模块是语音模 块，所述分类信息从语音模块所接收的语音指令所含自然语言中确定。
  19. 根据权利要求17所述的终端，其特征在于，所述语音模块还包括有：
    语音接收模块，用于获取待识别的带有分类信息的语音流数据；
    语音识别模块，用于识别所述语音流数据，解析出字符串文本格式的分类信息；
    处理模块，用于通过摄像头抓拍以获取与该分类信息对应的目标图片。
  20. 根据权利要求17所述的终端，其特征在于，所述语音识别模块被配置为：
    将获取的语音流数据包含到语音识别请求中通过远程接口提交；
    通过该远程接口获取响应于该语音识别请求而反馈的对应解析该语音流数据而获得的字符串文本格式的分类信息。
  21. 根据权利要求17所述的终端，其特征在于：所述语音识别模块还被配置为：
    将获取的语音流数据与本地语音库进行匹配识别处理；
    获得与该语音流数据相匹配的字符串文本格式的分类信息。
  22. 根据权利要求17所述的终端，其特征在于，所述属性设置模块还包括有：
    压缩模块，用于将所述目标图片压缩为特定格式文件；
    导航信息获取模块，用于调用导航模块获取当前导航信息；
    属性加载模块，用于将所述导航信息与分类信息添加到该文件的属性信息中。
  23. 根据权利要求17所述的终端，其特征在于：所述目标文件夹建立在SD卡上。
  24. 根据权利要求17所述的终端，其特征在于：所述存储模块还被配置为检测是否存在所述分类信息对应的目标文件夹；
    若为是，将该目标图片保存至该目标文件夹；
    若为否，则创建与该分类信息相对应的所述目标文件夹并将该目标图片保存至该目标文件夹。
  25. 根据权利要求22所述的终端，其特征在于：所述导航模块通过NMEA-0182协议获得目标图片的导航信息，或通过基站定位方式获得目标图 片的导航信息。
  26. 根据权利要求22所述的终端，其特征在于：所述属性加载模块被配置为将所述导航信息和分类信息添加到所述目标图片的EXIF信息中。
  27. 根据权利要求22所述的终端，其特征在于：所述特定格式文件的后缀名为JPG、JPEG、PNG中任意一项。
  28. 根据权利要求17所述的终端，其特征在于：所述抓拍模块被配置为通过调用拍照模式触发拍照得到所述目标图片；或被配置为通过截获抓拍指令发出时所对应时间点的视频图像而得到所述目标图片。
  29. 根据权利要求17所述的终端，其特征在于：所述分类信息所包含的类型包括人物、风景、车祸、路况各类型中的任意数量种类型。
  30. 根据权利要求22所述的终端，其特征在于：所述导航信息包括时间、地理位置、行车方向、行车速度、地理经纬度中的任意一种或任意多种。
  31. 根据权利要求17所述的终端，其特征在于：还包括有发送模块，
    所述发送模块，用于响应于外部指令通过局域网上传各目标文件夹中的目标图片。
  32. 根据权利要求18所述的终端，其特征在于：所述语音模块还被配置为仅当判断从所述语音指令的语音数据流提取的特征信息与本地预存的声纹特征相匹配时，才对所述语音指令进行分类信息识别。
  33. 一种计算机程序，包括计算机可读代码，当智能电子设备运行所述计算机可读代码时，导致权利要求1-16中的任一项权利要求所述的方法被执行。
  34. 一种计算机可读介质，其中存储了如权利要求33所述的计算机程序。
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