CN113852823B - Image data uploading method, system and device based on Internet of things - Google Patents
Image data uploading method, system and device based on Internet of things Download PDFInfo
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- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
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Abstract
The invention discloses an image data uploading method, system and device based on the Internet of things. Compared with the original image, the preview image data greatly reduces the capacity of the preview image data, and the preview image data can be quickly uploaded to the cloud end to form backup reference data. When the segmented original image data block encounters congestion, it can be distributed to other communication terminals for re-uploading. And after the divided original image is uploaded to the cloud, the divided original image can be adaptively recombined according to the backup reference data and the original image data can be restored. According to the invention, through setting the cooperation of a plurality of communication middle terminals and executing the preprocessing operation of the original image, the speed and the accuracy of uploading image data from the terminal to the cloud can be improved, and the user experience is greatly improved.
Description
Technical Field
The invention relates to the technical field of information transmission of the Internet of things, in particular to an image data uploading method, system and device based on the Internet of things.
Background
At present, products based on the internet of things are more and more widely applied, internet of things technology truly realizes the interconnection of everything, and the application field of the internet of things covers all aspects of smart homes, smart traffic, smart cities, smart buildings and the like. The technology of the Internet of things can not only realize small data transmission of industrial control instructions, but also realize large data transmission of audio and video images, such as face recognition, traffic images and the like. Aiming at image or video data transmission in the field of Internet of things, the method mainly comprises the following steps: and uploading the terminal to a cloud end, and downloading the terminal from the cloud end.
The method comprises the steps that a terminal uploads to a cloud end, namely the terminal encodes and compresses collected image data and sends the image data to the cloud end in a wireless communication mode, and the cloud end receives the compressed image data and then executes decoding operation to restore an original image; the cloud terminal downloads the image data to the terminal, namely the image data of the cloud terminal is sent to the terminal in a wireless communication mode after being encoded and compressed, and the terminal executes decoding operation after receiving the compressed image data to restore the original image.
However, the following problems exist in the stage of uploading the terminal to the cloud:
1) due to cost, the uploading bandwidth is far smaller than the downloading bandwidth, so that the uploading speed is slower than the downloading speed, and the image data received by the cloud end is long in time.
2) Due to the fact that the uploading bandwidth is small, data jam and loss easily occur to image data in the process of being uploaded to the cloud end by a terminal, and therefore probability distortion exists in the image data received by the cloud end.
Based on this, there is a need for an image data uploading scheme that can solve the existing technical problems.
Disclosure of Invention
The invention provides an image data uploading method, system and device based on the Internet of things, aiming at overcoming the defects of long image uploading time and data distortion in the field of the existing Internet of things, and the method, system and device have the following characteristics:
1) according to the uploaded bandwidth ratio, image data transmission is carried out by means of a plurality of wireless communication devices, and the speed of image data transmission is increased;
2) performing preview compression processing and segmentation operation on the image to form backup reference data at the cloud end, so that the received image data is prevented from being lost;
in order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, an image data uploading method based on the internet of things is applied to data communication among a cloud terminal, a communication middle terminal and an intelligent terminal, and comprises the following steps:
step S100, acquiring an original image and executing preprocessing operation;
step S200, executing the uploading operation of the preprocessed image data;
step S300, decoding the uploaded image data and recombining the image data;
the preprocessing operation refers to the operation of executing preview processing, segmentation processing, association matching processing and preview uploading processing on the original image at the intelligent terminal;
the preview processing is to execute compression processing with high compression ratio on the original image to form a preview image corresponding to the original image;
the segmentation processing means that the original image and the preview image are simultaneously segmented according to a preset image segmentation rule to form a plurality of original image data blocks and a plurality of original preview image data blocks;
the association matching processing is to perform association matching on the plurality of divided original image data blocks and the plurality of preview image data blocks;
the preview uploading processing refers to uploading the preview image to the cloud;
the image data uploading operation means that the communication middle terminal selectively executes the self uploading or forwards the acquired compressed image data block to other communication middle terminals for uploading according to the self uploading bandwidth condition;
the image data decoding operation refers to that the cloud end restores an original image data block after decoding operation is carried out on the obtained compressed data block;
and the image data reorganizing operation refers to the cloud end performing arrangement and reorganization on the decoded original image data blocks to restore the original image.
Further, the acquiring an original image and performing a preprocessing operation specifically includes the following steps:
step S110, the execution of preview processing comprises the steps of obtaining an original image, and executing compression preprocessing on the original image to form a preview image;
step S120, the segmentation processing comprises the step of executing segmentation operation on the preview image to form a plurality of sub preview image data blocks;
step S130, according to the segmentation operation of the preview image, segmenting the original image into a plurality of sub-original image data blocks;
step S140, the association matching process includes the association matching of the plurality of sub-original image data blocks and the plurality of sub-preview image data blocks;
step S150, the preview upload processing includes uploading the preview image data to the cloud, and forming backup reference data.
Further, the image data uploading operation after the execution of the preprocessing specifically includes the following steps:
step S210, compressing the sub-original image data block to form a compressed data block;
step S220, uploading the compressed data block to a first communication middle terminal;
step S230, determining whether the ratio of the upload bandwidth of the current first communication middle end is greater than a first threshold;
step S240, if yes, the first communication middle end sends the compressed data block to a second communication middle end;
step S250, determining whether the ratio of the upload bandwidth of the current second communication middle end is greater than a second threshold;
step S260, if yes, the second communication middle end sends the compressed data block to a third communication middle end;
if the ratio of the uploading bandwidth of the Nth communication middle end receiving the compressed data block is less than or equal to the second threshold value, the second threshold value is set; the Nth communication middle terminal uploads the compressed data block to the cloud terminal;
and the second communication middle end to the Nth communication middle end adopt a second threshold value.
Further, the executing of the operation of decoding the uploaded image data and recombining the image data specifically includes the following steps:
s310, decoding the uploaded compressed data block to form a sub-original image data block;
s320, executing the reorganization and arrangement of the sub-original image data blocks to form original image data;
s330, judging whether the sub-original image data and the backup reference data have matching relevance;
s340, if the matching relevance exists, uploading the original image data successfully;
if the sub-original image data and the backup reference data do not have matching relevance, the step S310 is required to be returned.
Meanwhile, an image data uploading system based on the Internet of things is provided for executing the method;
an image data uploading system based on the Internet of things comprises a cloud end, a communication middle end and an intelligent terminal;
the cloud end is used for receiving compressed data block data of the communication middle end, performing decoding and decompressing operation on the compressed data block to enable the compressed data block to form a sub-original image data block, and performing recombination and arrangement operation on the sub-original image data block to enable each sub-original image data block to form original image data;
the communication middle end is used for receiving the compressed data block of the intelligent terminal and finally uploading the compressed data block to the cloud end;
the communication middle end comprises a first communication middle end, a second communication middle end, … … and an Nth communication middle end;
uploading the compressed data block to a first communication middle end, and judging whether the uploading bandwidth ratio of the first communication middle end is greater than a first threshold value or not;
if so, the first communication middle end sends the compressed data block to a second communication middle end;
judging whether the ratio of the uploading bandwidth of the current second communication middle end is larger than a second threshold value;
if so, the second communication middle end sends the compressed data block to a third communication middle end;
by analogy, if the ratio of the uploading bandwidth of the nth communication middle end receiving the compressed data block is less than or equal to a second threshold corresponding to the nth communication middle end; the Nth communication middle terminal uploads the compressed data block to the cloud terminal;
the second communication middle end to the Nth communication middle end adopt a second threshold value;
the intelligent terminal acquires an original image and carries out preprocessing operation on the original image to form a preview image which can be referenced and verified.
Further, the cloud further comprises: the image processing device comprises a data processing unit, a preview image backup unit, an image decoding unit, an image recombination unit and a first cloud communication unit;
the data processing unit is used for verifying the identity matching of the sub-original image data block and the sub-preview image data block;
the preview image backup unit is used for storing backup reference data; the backup reference data is preview image data composed of the sub preview image data blocks;
the decoding unit is used for executing decoding and decompressing operations of the compressed data blocks to enable the compressed data blocks to form the sub-original image data blocks;
the image recombination unit is used for executing the recombination arrangement of each sub-original image data block according to the backup reference data and finally forming original image data;
the first cloud communication unit is in wireless connection with the communication middle end, and communication connection between the cloud end and the communication middle end is achieved.
Further, the communication middle end comprises: the system comprises a bandwidth ratio analysis unit, a first middle-end communication unit, a second cloud-end communication unit and a second terminal communication unit;
the bandwidth ratio analysis unit is used for analyzing the residual uploading bandwidth capacity of the current communication middle end;
the first middle-end communication unit is used for the wireless connection between the current communication middle end and other communication middle ends;
the second cloud communication unit is used for being in wireless connection with the first cloud communication unit;
the second terminal communication unit is used for realizing wireless connection between the communication middle end and the terminal;
the first cloud communication unit and the second cloud communication unit both include: WiFi, Bluetooth or 2.4G communication mode.
Further, the intelligent terminal further comprises: the system comprises an image preprocessing unit, an image coding unit, a first terminal communication unit and an image acquisition unit;
the image acquisition unit is used for acquiring an original image;
the image preprocessing unit is used for executing high-compression-ratio preview processing, segmentation processing and matching associated processing operations on the original image;
the image coding unit is used for executing coding compression operation on the segmented original image;
and the first terminal communication unit is in wireless connection with the second terminal communication unit.
According to another aspect of the present application, a storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the internet of things-based image data uploading method of any one of the above.
According to another aspect of the application, a computer device includes a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, and the processor implements the internet of things-based image data uploading method when executing the computer program.
In summary, the technical solution of the present invention performs compression preprocessing on the original image to form preview image data, and performs corresponding segmentation processing on the preview image data and the original image. Compared with the original image, the preview image data greatly reduces the capacity of the preview image data, and the preview image data can be quickly uploaded to the cloud end to form backup reference data. When the segmented original image data block encounters congestion, it can be distributed to other communication terminals for re-uploading. And after the divided original image is uploaded to the cloud, the divided original image can be adaptively recombined according to the backup reference data and the original image data can be restored. The beneficial technical effects of the invention are as follows:
1) according to the invention, the cooperation of a plurality of communication middle terminals is set, so that the speed of uploading image data from the terminal to the cloud can be increased, the quick uploading of the data of the Internet of things is realized, and the user experience is improved.
2) According to the method and the device, the accuracy of uploading the image data from the terminal to the cloud is greatly improved by executing the preprocessing operation of the original image, the accurate uploading of the data of the Internet of things is realized, and the user experience is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 shows an architecture diagram of an internet of things-based image data uploading system provided in the present application;
fig. 2 shows an internet of things-based image data uploading device architecture diagram provided by the present application;
fig. 3 shows a flowchart of an image data uploading method provided in embodiment 1 of the present application;
fig. 4 shows a flowchart of a preferred image data uploading method provided in embodiment 1 of the present application;
fig. 5 shows a flowchart of a preferred image data uploading method provided in embodiment 1 of the present application;
fig. 6 shows a flowchart of a preferred image data uploading method provided in embodiment 1 of the present application;
fig. 7 is a schematic diagram illustrating sub-image data block association matching provided in embodiment 1 of the present application;
fig. 8 shows a schematic diagram of an identity matching accessory package provided in embodiment 2 of the present application.
The various reference numbers in the figures have the meaning:
1-cloud end; 11-a data processing unit; 12-preview image backup unit; 13-an image decoding unit; 14-an image reorganization unit; 15-a first cloud communication unit;
2-a communication middle end; 21-bandwidth ratio analysis unit; 22-a first intermediate communication unit; 23-a second cloud communication unit; 24-a second terminal communication unit;
3, an intelligent terminal; 31-an image pre-processing unit; 32-an image encoding unit; 33-a first terminal communication unit; 34-image acquisition unit.
Detailed Description
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1 to 7, an image data uploading method based on the internet of things is provided, and is applied to data communication between a cloud end, a communication middle end and an intelligent terminal, and specifically, referring to fig. 1, the image data uploading method includes the following steps:
and step S100, acquiring an original image and executing preprocessing operation.
In this step, the intelligent terminal acquires and forms an original image, and performs a preprocessing operation on the original image. The original image comprises a picture obtained by photographing through a camera of a smart phone, a camera of a smart home or a camera of smart traffic.
The preprocessing operation refers to executing preview processing, segmentation processing, association matching processing and preview uploading processing on the original image at the intelligent terminal.
The preview processing is to execute compression processing with high compression ratio on the original image to form a preview image corresponding to the original image;
the segmentation processing means that the original image and the preview image are simultaneously segmented according to a preset image segmentation rule to form a plurality of original image data blocks and a plurality of original preview image data blocks;
the association matching processing is to perform association matching on the plurality of divided original image data blocks and the plurality of preview image data blocks;
the preview uploading processing refers to uploading the formed preview image to the cloud.
Through the preprocessing operation, the original image data blocks can be transmitted separately, and the preview image is transmitted integrally. The preview image is not used as data used by a user, but is used for data guiding and reference, after compression processing with a high compression ratio, the capacity of the preview image can reach 1/20 or even 1/50 of the original image, and when the uploading bandwidth is seriously extruded, the preview image can be easily uploaded to the cloud.
In general, the preview image is a frame of the original image, and details of the image are erased through compression processing, so as to guide arrangement and reorganization of the data blocks of the original image.
And step S200, uploading the preprocessed image data.
In this step, the intelligent terminal needs to perform coding compression processing on the divided original image data blocks, and then sends the original image data blocks to the communication middle terminal.
The image data uploading operation refers to that the communication middle terminal selectively executes the self uploading or forwards the acquired compressed image data block to other communication middle terminals for uploading according to the self uploading bandwidth condition.
The communication middle end is a communication device used for connecting the intelligent terminal and the cloud end.
It can be understood that if the communication middle end finds that the uploading bandwidth of the communication middle end is in a more unoccupied state, the communication middle end can select to upload the compressed image data to the cloud end by itself; if the communication middle end finds that the uploading bandwidth of the communication middle end is seriously extruded, the compressed image is forwarded to other communication middle ends, and the other communication middle ends evaluate the uploading condition.
It is to be understood that, in the image data uploading system of the internet of things, as shown in fig. 1, the communication middle terminal is composed of a plurality of communication middle terminals together.
Step S300, decoding the uploaded image data and reconstructing the image data are performed.
In this step, the communication middle end uploads the compressed image data module to the cloud.
The image data decoding operation refers to that the cloud end restores the original image data block after decoding operation is performed on the obtained compressed image data block.
The image data reorganizing operation refers to the cloud side conducting arrangement and reorganization on the decoded original image data blocks, and the original image is restored.
It can be understood that, after the segmented original image is compressed by encoding and decoded and decompressed, the original image is restored by rearranging and recombining according to the preview image.
It can be understood that when the communication middle end encounters congestion of image data uploading, other communication middle ends participate in the image data uploading, the image data compression block started to be uploaded comes first after the communication middle end exists, the image data block started to be uploaded comes later, and at the moment, a preview image is needed to be used as a guide to arrange and recombine the decoded image data block to restore the original image data.
Preferably, based on step S100, in order to make the preprocessing operation method for uploading image data clearer, the preprocessing operation method specifically further includes the following steps:
step S110, the executing of the preview processing includes acquiring an original image, and executing compression preprocessing on the original image to form a preview image.
In this step, compression processing at a high compression ratio is performed on the acquired original data to form a preview image. The size of the preview image is consistent with that of the original image, but the resolution of the preview image is far lower than that of the original image, and the self-capacity of the preview image is also far lower than that of the original image.
The high compression ratio can be selected from 1/20, 1/30, 1/50 and the like.
It will be appreciated that the selection of the compression ratio may be performed according to the width of the upload bandwidth and the upload demand.
Step S120, the segmentation process includes performing a segmentation operation on the preview image to form a plurality of sub preview image data blocks.
In this step, referring to fig. 7, as shown in fig. 7, the original image is compressed at a high compression ratio to form a preview image, and the preview image is represented by a thin border line in fig. 7. And dividing the preview image into 16 sub preview image data blocks according to the rule of 4 x 4. Which respectively comprise: sub preview image data chunk a, sub preview image data chunk b, and sub preview image data chunk c … …, sub preview image data chunk p.
Further, when the preview image is divided, division rules such as a 2 × 2 division rule, a 3 × 3 division rule, and a 5 × 5 division rule may be equally divided.
Further, when the preview image is divided, non-uniform division rules such as 1 × 5 division rule, 2 × 6 division rule, 3 × 4 division rule, and the like may be executed.
Further, in performing the division of the preview image, a division rule of an irregular shape may also be performed.
Step S130, dividing the original image into a plurality of sub-original image data blocks according to the dividing operation of the preview image.
In this step, referring to fig. 7, as shown in fig. 7, the raw image is represented by a thick border line. And dividing the preview image into 16 preview image data blocks according to the rule of 4-by-4.
The segmentation rule of the original image is consistent with the segmentation rule of the preview image.
It should be noted that, in the case where the number of communication middles and the uploading condition are satisfied, the more the original image and the preview image are divided, the faster the uploading speed and the higher the accuracy.
Step S140, the association matching process includes associating and matching the plurality of sub original image data blocks with the plurality of sub preview image data blocks.
In this step, referring to fig. 7, when the preview image and the original image have performed the same segmentation rule, the preview image and the original image have formed the same number of image data blocks. Since the preview image and the original image are differentiated in resolution without any change in size, an association matching operation can be performed at the overlapping position of the two images, that is, the sub-original image data block 1 is associated and matched with the sub-preview image data block a, the sub-original image data block 2 is associated and matched with the sub-preview image data block b, and so on until the last image data block.
Further, the association matching is to add an identity attachment packet header to the data packets of the sub-original image data block 1 and the sub-preview image data block a by adding an identity attachment packet which can be recognized by each other to the packet header of the data packets when the two sub-image data blocks form the code language data packet, see fig. 8.
It should be noted that the sub original image data block and the sub preview image data block are composed of a plurality of data packets, and the arrangement and reassembly efficiency can be effectively improved by adding mutually identifiable identity additional packets to the packet header of the data packet. For example, when the packet headers of the sub original image module 1 and the sub preview image data block a are not consistent, the comparison of the image contents is not performed any more, and the comparison time of the original image is greatly saved.
Step S150, the preview upload processing includes uploading the preview image data to the cloud, and forming backup reference data.
In this step, the segmented preview image data is uploaded to the cloud end, and is backed up at the cloud end for guiding the arrangement and recombination of the sub-original image data blocks.
Furthermore, the divided preview image can be uploaded by adopting a whole package of preview image data, and can also be uploaded by adopting a single sub preview data module respectively.
It should be noted that the preview image is compressed at a high compression ratio, and the capacity of the preview image is very small, so that the preview image can be easily uploaded to the cloud even when the uploading bandwidth of the communication terminal is severely squeezed.
Based on step S200, in order to make the uploading operation method of the preprocessed image data clearer, the uploading operation method specifically further includes the following steps:
step S210, performing compression processing on the sub-original image data block to form a compressed data block.
In the step, the intelligent terminal performs coding compression processing on the divided sub-original image data blocks, so that the capacity of the sub-original image data blocks is reduced, and the time consumed for uploading image data to a cloud end is shorter.
It should be noted that, compared with the original image being encoded and compressed and then being divided, the divided sub-original image data blocks are encoded and compressed again, which is more beneficial to maintaining the accuracy of the data after decoding and decompression. According to the encoding and compressing principle, many same characteristics are erased in the re-encoding and compressing process, so that a relatively high encoding and compressing rate is achieved, and relatively more detailed characteristics are reserved in the process of performing encoding and compressing on the decomposed original image data.
Step S220, uploading the compressed data block to the first communication middle terminal.
In this step, the intelligent terminal uploads the compressed data block after the coding compression to the first communication middle terminal. The communication middle ends comprise a first communication middle end, a second communication middle end, … … and an Nth communication middle end, each communication middle end is in communication connection with the cloud end, and the communication middle ends are interconnected within a condition allowable range. Further, the first communication middle end is a main communication middle end for compressing the data block.
The ratio of the uploading bandwidth of the compressed data block when the compressed data block is uploaded at the main communication middle end has a higher threshold value relative to the ratio of the uploading bandwidth of the non-main communication middle end.
It can be understood that, when the uploading bandwidth of the compressed data block at the primary communication middle end accounts for less than 90%, the first communication middle end will select to upload the compressed data block by itself;
when the uploading bandwidth occupation ratio of the compressed data block at the main communication middle end is more than 90%, the first communication middle end selectively forwards the compressed data block to other communication middle ends;
the upload bandwidth ratio is more than 90%, which means that less than 10% of bandwidth capacity is left at the communication middle end for uploading data to the cloud end; the upload bandwidth accounts for less than 90%, which means that at least 10% of bandwidth capacity is left in the communication end for uploading data to the cloud. As shown in fig. 2, for example: the current uploading bandwidth capacity is 10M, wherein 9.5M is used for uploading the compressed data block of the mobile phone, the remaining 0.5M is the bandwidth capacity which can be used by the camera and the monitoring device, and the uploading bandwidth occupation ratio is 95%.
Further, the other communication middle end is a non-primary communication middle end of the compressed data block.
When the compressed data block is uploaded at the non-main communication middle end, the uplink bandwidth of the compressed data block has a lower threshold value than that of the main communication middle end.
It can be understood that, when the uploading bandwidth of the compressed data block on the non-primary communication middle end is less than 70%, the non-primary communication middle end chooses to upload the compressed data block by itself;
and when the uploading bandwidth of the compressed data block at the non-main communication middle end is more than 70%, the non-main communication middle end selects to forward the compressed data block to other non-main communication middle ends.
It should be noted that the non-main communication middle end is a main communication middle end of other compressed data blocks, and if and only if the non-main communication middle end has more surplus bandwidth capacity, the compressed data block from the main communication middle end can be uploaded, so as to avoid the bandwidth capacity of the non-main communication middle end being insufficient for self use.
Step S230, determining whether the ratio of the upload bandwidth of the current first communication middle end is greater than a first threshold.
In this step, the current first communication middle end is the main communication middle end of the compressed data block, and after the first middle end acquires the compressed data block, it is determined whether the upload bandwidth ratio of the first middle end is greater than a first threshold.
For example, the first threshold refers to a bandwidth occupancy of 90%, i.e., a remaining upload bandwidth occupancy of 10%.
Further, the first threshold may be custom set.
Further, if the ratio of the uploading bandwidth of the current first communication middle end is less than or equal to the first threshold, the first communication middle end uploads the compressed data block to the cloud.
Step S240, if the ratio of the upload bandwidth of the current first communication middle end is greater than the first threshold, the first communication middle end sends the compressed data block to the second communication middle end.
In this step, it is a precondition that the ratio of the upload bandwidth of the first communication intermediate terminal is greater than the first threshold. And the first communication middle end sends the compressed data block to the second communication middle end.
The second communication middle end is a non-primary communication middle end of the compressed data block.
Step S250, determining whether the ratio of the upload bandwidth of the current second communication middle end is greater than a second threshold.
In this step, the current second communication middle end is a non-primary communication middle end of the compressed data block, and after the second middle end acquires the compressed data block, it is determined whether the upload bandwidth ratio of the second middle end is greater than a second threshold.
For example, the second threshold refers to a bandwidth occupancy of 70%, i.e., a remaining upload bandwidth occupancy of 30%.
Further, the second threshold may be custom set.
Further, if the uploading bandwidth ratio of the current second communication middle terminal is less than or equal to a second threshold, the second communication middle terminal uploads the compressed data block to the cloud.
Step S260, if the ratio of the upload bandwidth of the current second communication middle end is greater than the second threshold, the second communication middle end sends the compressed data block to the third communication middle end.
In this step, the second communication middle end sends the compressed data block to the third communication middle end on the premise that the ratio of the upload bandwidth of the second communication middle end is greater than the second threshold.
The third communication middle terminal is a non-primary communication middle terminal of the compressed data block.
Step S270, determining whether the ratio of the upload bandwidth of the current third communication middle terminal is greater than a second threshold.
In this step, the current third communication middle end is also a non-primary communication middle end of the compressed data block, and after the third middle end acquires the compressed data block, it is determined whether the upload bandwidth ratio of the third middle end is greater than a second threshold.
Further, if the uploading bandwidth ratio of the current third communication middle terminal is less than or equal to a second threshold, the third communication middle terminal uploads the compressed data block to the cloud.
And repeating the steps until all the compressed data blocks are uploaded, or the ratio of the uploading bandwidth of all the non-main communication middle ends is larger than a second threshold value.
If the ratio of the uploading bandwidth of the Nth communication middle end receiving the compressed data block is less than or equal to the second threshold value, the second threshold value is set; the Nth communication middle terminal uploads the compressed data block to the cloud terminal;
and the second communication middle end to the Nth communication middle end adopt a second threshold value to judge the ratio of the uploading bandwidth.
Step S270, uploading the compressed data block to the cloud.
In this step, if the current communication middle end meets the condition of uploading the compressed data block, the uploading of the compressed data block is executed.
Based on step S300, in order to make the operation method of decoding and recombining the uploaded image data clearer, the operation method of decoding and recombining further includes the following steps:
s310, decoding the uploaded compressed data block to form a sub-original image data block.
In this step, the cloud acquires the compressed data block at the communication middle end, and performs decoding and decompression operation on the compressed data block to restore the sub-original image data block.
Furthermore, the decoded sub-original image data block is a sub-original image data block with an identity; and the identity of the sub-original image data block is matched with the identity of the backup reference data.
The backup reference data refers to the combination of the sub preview image data blocks with the identity marks.
It will be appreciated that after the sub-original image data block is decoded, it will perform identity matching with the backup reference data.
And S320, performing recombination arrangement of the sub-original image data blocks to form original image data.
In this step, after the matching operation according to the identities of the sub-original image data blocks, the sub-original image data blocks decoded in sequence are rearranged and arranged according to the backup reference data (each sub-preview image data block).
It will be appreciated that, with reference to fig. 7, for example: as shown in fig. 7, if the cloud receives and decodes the sub-original image data block 3, the sub-original image data block 5, the sub-original image data block 2, the sub-original image data block 1, and the sub-original image data block 4 in sequence, then according to the matching rule at the intelligent terminal, it will re-assemble and arrange, which is in sequence: a sub-original image data block 1, a sub-original image data block 2, a sub-original image data block 3, a sub-original image data block 4, a sub-original image data block 5, and finally, a sub-original image completely corresponding to the sub-preview image is formed.
S330, judging whether the sub-original image data and the backup reference data have matching relevance.
In this step, the sub-original image data is composed of each decoded sub-original image data block step by step, and before the complete sub-original image data is formed, the sub-original image data needs to be continuously associated, matched and compared with the backup reference data.
Further, if there is a missing sub-original image data block in the sub-original image data, and a complete correlation match cannot be formed after comparing with the backup reference data, it is necessary to return to step S310 to perform a decoding operation on the uploaded compressed data block to form the sub-original image data block.
And S340, if the matching relevance exists, uploading the original image data successfully.
In this step, all the sub-original image data blocks are completely associated and matched with the backup reference data (all the sub-preview image data blocks), which indicates that the original image data is successfully uploaded.
Example 2
Referring to fig. 1 to 8, an image data uploading system based on the internet of things is provided, referring to fig. 1, and includes a cloud 1, a communication middle end 2 and an intelligent terminal 3.
The cloud 1 is configured to receive a compressed data block of the communication middle terminal 2, perform decoding and decompression operations on the compressed data block to enable the compressed data block to form a sub-original image data block, and perform rearrangement operations on the sub-original image data block to enable each sub-original image data block to form original image data.
The communication middle end 2 is used for receiving the compressed data block of the intelligent terminal 3 and finally uploading the compressed data block to the cloud end 1.
The communication middle end 2 comprises a first communication middle end, a second communication middle end, … … and an Nth communication middle end;
uploading the compressed data block to a first communication middle end, and judging whether the uploading bandwidth ratio of the first communication middle end is greater than a first threshold value or not;
if so, the first communication middle end sends the compressed data block to a second communication middle end;
judging whether the ratio of the uploading bandwidth of the current second communication middle end is larger than a second threshold value;
if so, the second communication middle end sends the compressed data block to a third communication middle end;
if the ratio of the uploading bandwidth of the Nth communication middle end receiving the compressed data block is less than or equal to the second threshold value, the second threshold value is set; the Nth communication middle terminal uploads the compressed data block to the cloud terminal;
and the second communication middle end to the Nth communication middle end adopt a second threshold value to judge the ratio of the uploading bandwidth.
After the other communication middle terminals acquire the compressed data blocks, according to the judgment that the other communication middle terminals can be used for uploading bandwidth capacity, the other communication middle terminals select to execute self-uploading of the compressed data blocks or execute the compressed data blocks and then forward the compressed data blocks to the communication middle terminals with the wireless connection relation, and so on until the compressed data blocks are executed and uploaded to the cloud terminal 1.
The intelligent terminal 3 acquires an original image, and performs preprocessing operation on the original image to form a preview image which can be referred to for verification. And according to a preset segmentation rule, the intelligent terminal performs segmentation operation on the preview image and the original image to respectively form a sub preview image data block and a sub original image data block. And performing association matching on the sub preview image data blocks and the sub original image data blocks respectively. And finally, uploading the preview image data and the encoded and compressed sub-original image data to a cloud.
The cloud 1 further comprises: the image processing device comprises a data processing unit 11, a preview image backup unit 12, an image decoding unit 13, an image reorganizing unit 14 and a first cloud communication unit 15.
The data processing unit 11 is configured to verify that the identities of the sub original image data block and the sub preview image data block are matched; referring to fig. 8, the identity matching is based on the comparison of the data packet headers of the sub original image data block and the sub preview image data block.
The preview image backup unit 12 is configured to store backup reference data, where the backup reference data is preview image data composed of each sub preview image data block.
The decoding unit 13 is configured to perform decoding and decompressing operations on the compressed data blocks, so that the compressed data blocks form sub-original image data blocks.
The image reorganizing unit 14 is configured to perform reorganization and arrangement of each sub-original image data block according to the backup reference data, and finally form original image data.
And the first cloud communication unit 15 is used for wirelessly connecting with the communication middle terminal 2.
The communication middle end 2 further comprises: the system comprises a bandwidth ratio analysis unit 21, a first middle-end communication unit 22, a second cloud-end communication unit 23 and a second terminal communication unit 24.
The bandwidth occupation analysis unit 21 is configured to analyze remaining upload bandwidth capacity of the current communication middle terminal according to the compressed data block received from the intelligent terminal, and if the current upload bandwidth occupation ratio is higher than a first threshold, feed back the compressed data block to the first middle terminal communication unit, and allow the first middle terminal communication unit to forward the compressed data block to other communication middle terminals.
The first middle communication unit 22 is used for wireless connection with other middle communication terminals.
The second cloud communication unit 23 is configured to wirelessly connect with the first cloud communication unit 15 of the cloud.
And the second terminal communication unit 24 is configured to implement wireless connection between the communication middle end and the terminal.
The first cloud communication unit 15 and the second cloud communication unit 23 each include: WiFi, bluetooth, 2.4G and other communication means.
The intelligent terminal 3 further includes: an image preprocessing unit 31, an image coding unit 32, a first terminal communication unit 33, and an image acquisition unit 34.
The image acquisition unit 34 is used for acquiring an original image;
the image preprocessing unit 31 is configured to perform operations of high-compression preview processing, segmentation processing, and matching association processing on the original image.
The image encoding unit 32 is configured to perform encoding and compression operations on the segmented original image, so as to facilitate subsequent data uploading.
A first terminal communication unit 33 for wireless connection with the second terminal communication unit 24.
The first terminal communication unit 33 and the second terminal communication unit 24 include: WiFi, bluetooth, 2.4G and other communication means.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the implementation scenarios of the present application.
In an embodiment of the present invention, there is provided a computer device including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements any one of the above when executing the computer program.
Optionally, the computer device may also include a user interface, a network interface, a camera, Radio Frequency (RF) circuitry, sensors, audio circuitry, a WI-FI module, and so forth. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the present embodiment provides a computer device architecture that is not limiting of the computer device, and that may include more or fewer components, or some components in combination, or a different arrangement of components.
The storage medium may further include an operating system and a network communication module. An operating system is a program that manages and maintains the hardware and software resources of a computer device, supporting the operation of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among components in the storage medium and other hardware and software in the entity device.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and can also implement its corresponding software by a hardware platform.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (10)
1. An image data uploading method based on the Internet of things is applied to data communication among a cloud end, a communication middle end and an intelligent terminal, and is characterized by comprising the following steps:
step S100, acquiring an original image and executing preprocessing operation;
step S200, performing image data uploading operation after preprocessing operation;
step S300, performing image data decoding and image data recombination operation after the image data uploading operation;
the preprocessing operation refers to the operation of executing preview processing, segmentation processing, association matching processing and preview uploading processing on the original image at the intelligent terminal;
the preview processing is to execute compression processing with high compression ratio on the original image to form a preview image corresponding to the original image;
the segmentation processing means that the original image and the preview image are simultaneously segmented according to a preset image segmentation rule to form a plurality of sub original image data blocks and a plurality of sub preview image data blocks;
the association matching processing refers to performing association matching on the plurality of divided sub original image data blocks and the plurality of sub preview image data blocks;
the preview uploading processing refers to uploading the sub preview image data blocks to the cloud;
the image data uploading operation refers to that the communication middle terminal selectively executes self uploading or forwards the acquired compressed data block to other communication middle terminals for uploading according to the self uploading bandwidth condition, wherein the compressed data block refers to that the sub-original image data block is compressed to form a compressed data block;
the image data decoding operation refers to that the cloud end restores a sub-original image data block after decoding operation is carried out on the obtained compressed data block;
and the image data recombination operation refers to that the cloud terminal performs arrangement and recombination on the decoded plurality of sub-original image data blocks to restore an original image.
2. The internet of things-based image data uploading method according to claim 1, wherein the steps of obtaining an original image and performing preprocessing include the following steps:
step S110, the execution of preview processing comprises the steps of obtaining an original image, and executing compression processing with high compression ratio on the original image to form a preview image; step S120, the segmentation processing comprises the step of executing segmentation operation on the preview image to form a plurality of sub preview image data blocks;
step S130, according to the segmentation operation of the preview image, segmenting the original image into a plurality of sub-original image data blocks;
step S140, the association matching process includes associating and matching the plurality of sub original image data blocks with the plurality of sub preview image data blocks;
and step S150, the preview uploading process comprises the step of uploading the sub preview image data blocks to the cloud end to form backup reference data.
3. The internet of things-based image data uploading method according to claim 2, wherein the pre-processed image data uploading operation is executed, and the method specifically comprises the following steps:
step S210, compressing the sub-original image data block to form a compressed data block;
step S220, uploading the compressed data block to a first communication middle terminal;
step S230, determining whether the ratio of the upload bandwidth of the current first communication middle end is greater than a first threshold;
step S240, if yes, the first communication middle end sends the compressed data block to a second communication middle end;
step S250, determining whether the ratio of the upload bandwidth of the current second communication middle end is greater than a second threshold;
step S260, if yes, the second communication middle end sends the compressed data block to a third communication middle end;
by analogy, if the uploading bandwidth ratio of the nth communication middle end receiving the compressed data block is less than or equal to the second threshold, the nth communication middle end uploads the compressed data block to the cloud end;
and the second communication middle end to the Nth communication middle end adopt the second threshold value.
4. The internet of things-based image data uploading method according to claim 3, wherein the uploaded image data decoding and image data recombining operation is executed, and the method specifically comprises the following steps:
s310, decoding the uploaded compressed data block to form a sub-original image data block;
s320, executing the reorganization and arrangement of the sub-original image data blocks to form original image data;
s330, judging whether the sub-original image data block and the backup reference data have matching relevance;
s340, if the matching relevance exists, uploading the original image data successfully;
if the sub-original image data block does not have matching correlation with the backup reference data, the process returns to step S310.
5. An image data uploading system based on the Internet of things is characterized in that the image data uploading system is used for executing the image data uploading method based on the Internet of things of any one of claims 1-4, and comprises a cloud end (1), a communication middle end (2) and an intelligent terminal (3);
the cloud end (1) is used for receiving compressed data blocks of the communication middle end (2), decoding and decompressing the compressed data blocks to enable the compressed data blocks to form sub-original image data blocks, and performing recombination and arrangement operation on the sub-original image data blocks to enable each sub-original image data block to form original image data;
the communication middle terminal (2) is used for receiving the compressed data block of the intelligent terminal (3) and finally uploading the compressed data block to the cloud terminal (1);
the communication middle end (2) comprises a first communication middle end, a second communication middle end, … … and an Nth communication middle end;
uploading the compressed data block to a first communication middle end, and judging whether the uploading bandwidth ratio of the first communication middle end is greater than a first threshold value or not;
if so, the first communication middle end sends the compressed data block to a second communication middle end;
judging whether the ratio of the uploading bandwidth of the current second communication middle end is larger than a second threshold value;
if so, the second communication middle end sends the compressed data block to a third communication middle end;
by analogy, if the uploading bandwidth ratio of the nth communication middle end receiving the compressed data block is less than or equal to a second threshold corresponding to the nth communication middle end, the nth communication middle end uploads the compressed data block to the cloud end;
the second threshold is adopted from the second communication middle end to the Nth communication middle end;
the intelligent terminal (3) acquires an original image, and performs preprocessing operation on the original image to form a preview image which can be referenced and verified.
6. The image data upload system of claim 5,
the cloud (1) further comprises: the image processing device comprises a data processing unit (11), a preview image backup unit (12), an image decoding unit (13), an image recombination unit (14) and a first cloud communication unit (15);
the data processing unit (11) is used for verifying that the identities of the sub-original image data block and the sub-preview image data block are matched;
the preview image backup unit (12) is used for storing backup reference data; the backup reference data is preview image data composed of the sub preview image data blocks;
the image decoding unit (13) is used for executing decoding and decompressing operations of the compressed data blocks, so that the compressed data blocks form the sub-original image data blocks;
the image reorganization unit (14) is used for executing reorganization and arrangement of the sub original image data blocks according to the backup reference data and finally forming original image data;
the first cloud communication unit (15) is in wireless connection with the communication middle end (2) to achieve communication connection between the cloud end (1) and the communication middle end (2).
7. The image data upload system of claim 6,
the communication middle terminal (2) comprises: the system comprises a bandwidth ratio analysis unit (21), a first middle-end communication unit (22), a second cloud-end communication unit (23) and a second terminal communication unit (24);
the bandwidth ratio analysis unit (21) is used for analyzing the residual uploading bandwidth capacity of the current communication middle end;
the first middle-end communication unit (22) is used for the wireless connection between the current middle-end communication and other middle-end communication;
the second cloud communication unit (23) is in wireless connection with the first cloud communication unit (15);
a second terminal communication unit (24) for realizing the wireless communication connection between the communication middle end and the terminal;
the first cloud communication unit (15) and the second cloud communication unit (23) each include: WiFi, Bluetooth or 2.4G communication mode.
8. The image data upload system of claim 7,
the intelligent terminal (3) further comprises: the device comprises an image preprocessing unit (31), an image coding unit (32), a first terminal communication unit (33) and an image acquisition unit (34);
the image acquisition unit (34) is used for acquiring an original image;
the image preprocessing unit (31) is used for executing high-compression-ratio preview processing, segmentation processing and matching association processing operations on the original image;
the image encoding unit (32) is used for carrying out encoding compression operation on the divided original image;
a first terminal communication unit (33) for wireless connection with the second terminal communication unit (24).
9. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the internet of things-based image data uploading method of any one of claims 1 to 4.
10. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the internet of things-based image data uploading method according to any one of claims 1 to 4 when executing the computer program.
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