CN110991213A - Automatic big data distribution platform - Google Patents
Automatic big data distribution platform Download PDFInfo
- Publication number
- CN110991213A CN110991213A CN201910396432.1A CN201910396432A CN110991213A CN 110991213 A CN110991213 A CN 110991213A CN 201910396432 A CN201910396432 A CN 201910396432A CN 110991213 A CN110991213 A CN 110991213A
- Authority
- CN
- China
- Prior art keywords
- image
- equipment
- video recording
- signal
- big data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003384 imaging method Methods 0.000 claims abstract description 20
- 235000021167 banquet Nutrition 0.000 claims abstract description 18
- 235000013361 beverage Nutrition 0.000 claims abstract description 12
- 230000009471 action Effects 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims description 64
- 230000000877 morphologic effect Effects 0.000 claims description 32
- 238000000034 method Methods 0.000 claims description 23
- 238000004458 analytical method Methods 0.000 claims description 18
- 238000001914 filtration Methods 0.000 claims description 15
- 230000007797 corrosion Effects 0.000 claims description 12
- 238000005260 corrosion Methods 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 9
- 238000013507 mapping Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 5
- 238000009499 grossing Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 abstract description 7
- 238000010295 mobile communication Methods 0.000 description 9
- 230000005540 biological transmission Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000013500 data storage Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000004806 packaging method and process Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/12—Hotels or restaurants
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
- G06V20/36—Indoor scenes
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Multimedia (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Image Processing (AREA)
Abstract
The invention relates to an automatic big data distribution platform, which comprises: the wired video recording equipment is positioned above a dining table of the banquet hall and used for executing video recording action on the position of the dining table so as to obtain a current video recording frame; the big data end storage device is connected with the data acquisition device through a network and is used for storing and sending the male imaging characteristics and the female imaging characteristics; and the data acquisition equipment is connected with the bus type single chip microcomputer and is used for identifying the number of male personnel and the number of female personnel in the image to be processed based on the male imaging characteristics and the female imaging characteristics. The automatic big data distribution platform is reliable in principle and convenient to operate. Since the number of wine packages and the number of beverage packages to be supplied at the table are automatically determined based on the number of different genders of persons seated at each table of the banquet hall, cumbersome links of communication between service staff and diners are reduced.
Description
Technical Field
The invention relates to the field of big data storage, in particular to an automatic big data distribution platform.
Background
"big data" generally refers to data sets that are large in size, difficult to collect, process, analyze, and also refers to data that is stored in a traditional infrastructure for a long period of time. Here, "large" has several levels of meaning, which may dictate the size of the organization, and more importantly, the size of the IT infrastructure in an enterprise. Industry has placed an infinite expectation on big data applications-the more value that business information accumulates-simply we need a method to mine these values.
With the explosive growth of big data applications, it has derived its own unique architecture and has also pushed the development of storage, networking and computing technologies directly. After all, handling the special requirement of big data is a new challenge. The development of hardware is ultimately driven by software requirements, and in this instance it is apparent that the development of data storage infrastructure is being influenced by the demands of large data analysis applications.
Viewed from another perspective, this change is not an opportunity for storage vendors and other IT infrastructure vendors to not taste. With the continuous growth of the amount of structured data and unstructured data, and the diversification of analytical data sources, the design of previous storage systems has been unable to meet the needs of large data applications. Storage vendors, having realized this, have begun to modify the architectural design of block and file based storage systems to accommodate these new requirements.
Disclosure of Invention
The invention needs to have the following two points:
(1) in view of the characteristic that an image subjected to image interpolation processing based on a cubic interpolation method has lower redundancy than an original image, in order to reduce the redundancy of the image and improve the effectiveness of subsequent image detection processing, a self-adaptive re-interpolation selection mechanism is adopted to further enrich the image content;
(2) the number of packages of wine and the number of packages of beverages to be served at the table are automatically determined based on the number of different genders of persons seated at each table of the banquet hall, thereby reducing cumbersome links of communication between service staff and diners.
According to an aspect of the present invention, there is provided an automated big data distribution platform, the platform comprising:
the wired video recording equipment is positioned above a dining table of the banquet hall and used for executing video recording action on the position of the dining table so as to obtain a current video recording frame;
the big data end storage device is connected with the data acquisition device through a network and is used for storing and sending the male imaging characteristics and the female imaging characteristics;
the data acquisition equipment is connected with the bus type single chip microcomputer and used for identifying the number of male personnel and the number of female personnel in the image to be processed based on male imaging characteristics and female imaging characteristics;
a signal mapping device connected to the data acquisition device for determining the number of wine packages served at the party based on the number of male persons and for determining the number of beverage packages served at the party based on the number of female persons
The wireless uploading device is respectively connected with the signal mapping device and a server of a rear control room of the banquet hall and is used for wirelessly uploading the number of the wine packages and the number of the beverage packages to the server of the rear control room of the banquet hall;
the morphological processing equipment is connected with the wired video recording equipment, arranged in an instrument box below the dining table and used for executing morphological processing on the received current video recording frame so as to obtain and output a corresponding morphological processing image;
the morphological processing equipment comprises signal corrosion sub-equipment and signal expansion sub-equipment, wherein the signal expansion sub-equipment is connected with the signal corrosion sub-equipment and sends a processed image to the signal corrosion sub-equipment;
a cubic interpolation device connected to the morphological processing device, for performing an image interpolation process based on a cubic interpolation method on the received morphologically processed image to obtain and output a cubic interpolation image;
and the redundancy analysis device is connected with the cubic interpolation device and used for receiving the cubic interpolation image and the morphological processing image, analyzing the signal redundancy of the morphological processing image based on each pixel value of each pixel point of the morphological processing image, and analyzing the signal redundancy of the cubic interpolation image based on each pixel value of each pixel point of the cubic interpolation image.
The automatic big data distribution platform is reliable in principle and convenient to operate. Since the number of wine packages and the number of beverage packages to be supplied at the table are automatically determined based on the number of different genders of persons seated at each table of the banquet hall, cumbersome links of communication between service staff and diners are reduced.
Detailed Description
An embodiment of the automated big data distribution platform of the present invention will be described in detail below.
The research of the automatic control technology is beneficial to freeing human from complex, dangerous and fussy working environment and greatly improving the control efficiency. Automatic control is a branch of engineering science. It involves automatic influence on the dynamic system using feedback principles to bring the output value close to what we want. From a process point of view, it is based on mathematical system theory. What we call automatic control today is a branch of the theory of control that arose in the middle of the twentieth century. The underlying conclusions are presented by norbert wiener, ludaff kalman.
For example, the regulation of the indoor temperature is a simple and easy-to-understand example. The purpose is to maintain the indoor temperature at a constant value theta despite the fact that factors such as windowing cause indoor heat to be emitted outdoors (disturbance d). To achieve this, the heating must be suitably influenced. The temperature is kept constant by adjusting the valve. In addition, the temperature of the hot water of the warmer is disturbed by the outside temperature until the user feels it.
At present, the quantity of wine packagings and beverage packagings of each dining table in the banquet hall is all customized, and the quantity of each dining table is all the same, can not carry out differential customization and processing because of the quantity and the sex of the personnel that the banquet was eaten in the future, leads to service personnel and personnel of having dinner often to be trapped in loaded down with trivial details link of communicating.
In order to overcome the defects, the invention builds an automatic big data distribution platform and can effectively solve the corresponding technical problem.
The automatic big data distribution platform shown according to the embodiment of the invention comprises:
the wired video recording equipment is positioned above a dining table of the banquet hall and used for executing video recording action on the position of the dining table so as to obtain a current video recording frame;
the big data end storage device is connected with the data acquisition device through a network and is used for storing and sending the male imaging characteristics and the female imaging characteristics;
the data acquisition equipment is connected with the bus type single chip microcomputer and used for identifying the number of male personnel and the number of female personnel in the image to be processed based on male imaging characteristics and female imaging characteristics;
a signal mapping device connected to the data acquisition device for determining the number of wine packages served at the party based on the number of male persons and for determining the number of beverage packages served at the party based on the number of female persons
The wireless uploading device is respectively connected with the signal mapping device and a server of a rear control room of the banquet hall and is used for wirelessly uploading the number of the wine packages and the number of the beverage packages to the server of the rear control room of the banquet hall;
the morphological processing equipment is connected with the wired video recording equipment, arranged in an instrument box below the dining table and used for executing morphological processing on the received current video recording frame so as to obtain and output a corresponding morphological processing image;
the morphological processing equipment comprises signal corrosion sub-equipment and signal expansion sub-equipment, wherein the signal expansion sub-equipment is connected with the signal corrosion sub-equipment and sends a processed image to the signal corrosion sub-equipment;
a cubic interpolation device connected to the morphological processing device, for performing an image interpolation process based on a cubic interpolation method on the received morphologically processed image to obtain and output a cubic interpolation image;
a redundancy analyzing device connected to the cubic interpolating device, for receiving the cubic interpolation image and the morphologically processed image, analyzing the signal redundancy of the morphologically processed image based on each pixel value of each pixel point of the morphologically processed image, and analyzing the signal redundancy of the cubic interpolation image based on each pixel value of each pixel point of the cubic interpolation image;
the command extraction device is connected with the redundancy analysis device and used for sending a first driving command when the multiple obtained by dividing the signal redundancy of the three-time interpolation image by the signal redundancy of the morphological processing image exceeds the limit;
the command extraction device is further used for sending a second driving command when the multiple obtained by dividing the signal redundancy of the three-time interpolation image by the signal redundancy of the morphological processing image is not over limit;
the bus type single chip microcomputer is respectively connected with the command extraction equipment and the cubic interpolation equipment and is used for controlling the cubic interpolation equipment to perform image interpolation processing based on a cubic interpolation method on the cubic interpolation image again when the second driving command is received so as to obtain a corresponding image to be processed;
and the bus type single chip microcomputer is also used for outputting the three-time interpolation image as an image to be processed when receiving the first driving command.
Next, the detailed structure of the automated big data distribution platform of the present invention will be further described.
The automatic big data distribution platform can further comprise:
the signal analysis equipment is connected with the wired video recording equipment, arranged in an instrument box below the dining table and used for receiving the current video recording frame and analyzing the number of bytes occupied by the pixel value of each pixel point in the current video recording frame so as to obtain the number of reference bytes to be output;
and the pixel point counting equipment is used for receiving the current video recording frame and counting the total number of the pixel points in the current video recording frame so as to obtain a reference total number for outputting.
The automatic big data distribution platform can further comprise:
the number judgment device is respectively connected with the signal analysis device and the pixel point counting device and used for receiving the reference byte number and the reference total number and determining the data volume grade in direct proportion to the reference byte number and the reference total number based on the product of the reference byte number and the reference total number;
the embedded processing equipment is respectively connected with the quantity judging equipment and the field sharpening equipment and used for recovering power supply to the field sharpening equipment when the level of the received data volume exceeds the limit;
wherein the embedded processing device is further configured to cut off power to the field sharpening device when the received data volume level is not exceeded.
The automatic big data distribution platform can further comprise:
the field sharpening device is used for receiving the current video recording frame from the signal analysis device and executing smoothing processing operation on the current video recording frame so as to obtain and output a corresponding field sharpened image;
the median filtering device is connected with the field sharpening device and is used for receiving the field sharpened image and executing a median filtering operation on the field sharpened image to obtain a corresponding median filtered image;
and the channel value analysis equipment is connected with the median filtering equipment and is used for receiving the median filtering image and obtaining the saturation channel value, the brightness channel value and the hue channel value of each pixel point in the median filtering image.
The automatic big data distribution platform can further comprise:
the dynamic processing equipment is connected with the channel value analysis equipment and is used for executing image enhancement processing on a saturation pattern formed by each saturation channel value of each pixel point in the median filtered image to obtain a first enhancement pattern, executing image enhancement processing on a brightness pattern formed by each brightness channel value of each pixel point in the median filtered image to obtain a second enhancement pattern, and forming a tone pattern by each tone channel value of each pixel point in the median filtered image;
the data merging device is connected with the dynamic processing device and is used for merging the first enhancement pattern, the second enhancement pattern and the tone pattern to obtain a data merging image corresponding to the median filtering image;
the data merging device is further connected with the morphological processing device and is used for replacing the current video recording frame with the data merging image and sending the data merging image to the morphological processing device.
The automatic big data distribution method shown according to the embodiment of the invention comprises the following steps:
the method comprises the steps that wired video recording equipment is used and located above a dining table of a banquet hall and used for executing video recording actions on the position of the dining table to obtain a current video recording frame;
the large data end storage device is connected with the data acquisition device through a network and used for storing and sending the male imaging characteristics and the female imaging characteristics;
the data acquisition equipment is connected with the bus type single chip microcomputer and used for identifying the number of male personnel and the number of female personnel in the image to be processed based on male imaging characteristics and female imaging characteristics;
a signal mapping device, coupled to the data acquisition device, for determining the number of wine packages for the party based on the number of male persons and for determining the number of beverage packages for the party based on the number of female persons
The wireless uploading device is respectively connected with the signal mapping device and a server of a rear control room of the banquet hall and used for wirelessly uploading the number of the wine packages and the number of the beverage packages to the server of the rear control room of the banquet hall;
using morphology processing equipment, connecting with the wired video recording equipment, arranging in an instrument box below the dining table, and executing morphology processing on the received current video recording frame to obtain and output a corresponding morphology processing image;
the morphological processing equipment comprises signal corrosion sub-equipment and signal expansion sub-equipment, wherein the signal expansion sub-equipment is connected with the signal corrosion sub-equipment and sends a processed image to the signal corrosion sub-equipment;
using a cubic interpolation device, connected to the morphological processing device, for performing cubic interpolation-based image interpolation processing on the received morphologically processed image to obtain and output a cubic interpolation image;
using a redundancy analyzing device, connected to the cubic interpolating device, for receiving the cubic interpolating image and the morphologically processed image, analyzing the signal redundancy of the morphologically processed image based on the respective pixel values of the respective pixel points of the morphologically processed image, and analyzing the signal redundancy of the cubic interpolating image based on the respective pixel values of the respective pixel points of the cubic interpolating image;
using a command extraction device connected to the redundancy analysis device for issuing a first drive command when a multiple obtained by dividing the signal redundancy of the cubic interpolation image by the signal redundancy of the morphological processing image exceeds a limit;
the command extraction device is further used for sending a second driving command when the multiple obtained by dividing the signal redundancy of the three-time interpolation image by the signal redundancy of the morphological processing image is not over limit;
the bus type single chip microcomputer is respectively connected with the command extraction equipment and the cubic interpolation equipment and used for controlling the cubic interpolation equipment to perform image interpolation processing based on a cubic interpolation method on the cubic interpolation image again when the second driving command is received so as to obtain a corresponding image to be processed;
and the bus type single chip microcomputer is also used for outputting the three-time interpolation image as an image to be processed when receiving the first driving command.
Next, the detailed steps of the automated big data allocation method of the present invention will be further described.
The automatic big data distribution method can further comprise the following steps:
the signal analysis equipment is connected with the wired video recording equipment, is arranged in an instrument box below a dining table and is used for receiving the current video recording frame and analyzing the number of bytes occupied by the pixel value of each pixel point in the current video recording frame so as to obtain the number of reference bytes to be output;
and using pixel point counting equipment for receiving the current video recording frame and counting the total number of the pixel points in the current video recording frame to obtain reference total number output.
The automatic big data distribution method can further comprise the following steps:
the used number judgment device is respectively connected with the signal analysis device and the pixel point counting device and used for receiving the reference byte number and the reference total number and determining the data volume grade in direct proportion to the reference byte number and the reference total number based on the product of the reference byte number and the reference total number;
the method comprises the steps that an embedded processing device is used, and the embedded processing device is respectively connected with a quantity judging device and an on-site sharpening device and used for recovering power supply to the on-site sharpening device when the level of received data volume exceeds a limit;
wherein the embedded processing device is further configured to cut off power to the field sharpening device when the received data volume level is not exceeded.
The automatic big data distribution method can further comprise the following steps:
using a field sharpening device for receiving a current video frame from the signal analysis device, and performing a smoothing operation on the current video frame to obtain and output a corresponding field sharpened image;
using a median filtering device connected to the on-site sharpening device, for receiving the on-site sharpened image, and performing a median filtering operation on the on-site sharpened image to obtain a corresponding median filtered image;
and using a channel value analysis device, connected with the median filtering device, for receiving the median filtered image to obtain a saturation channel value, a brightness channel value and a hue channel value of each pixel point in the median filtered image.
The automatic big data distribution method can further comprise the following steps:
using a dynamic processing device connected to the channel value analyzing device, for performing image enhancement processing on a saturation pattern composed of each saturation channel value of each pixel point in the median filtered image to obtain a first enhancement pattern, performing image enhancement processing on a luminance pattern composed of each luminance channel value of each pixel point in the median filtered image to obtain a second enhancement pattern, wherein each hue channel value of each pixel point in the median filtered image constitutes a hue pattern;
using a data merging device connected with the dynamic processing device for merging the first enhancement pattern, the second enhancement pattern and the tone pattern to obtain a data merged image corresponding to the median filtered image;
the data merging device is further connected with the morphological processing device and is used for replacing the current video recording frame with the data merging image and sending the data merging image to the morphological processing device.
In addition, the wireless uploading device comprises a time division duplex communication interface. Time division duplexing is a duplexing method of a communication system for separating reception and transmission channels in a mobile communication system. Mobile communication is currently developing to the third generation, and china filed the third generation draft of mobile communication standards (TD-SCDMA) in 6 months 1997, and its features such as TDD mode and new technology of smart antenna are highly evaluated and become one of three main candidate standards. TDD mode has not been emphasized on the whole in FDD mode in first and second generation mobile communication systems. However, due to the need for new services and the development of new technologies, and many advantages of the TDD mode, the TDD mode will be increasingly emphasized.
The working principle of time division duplex is as follows: TDD is a duplex scheme of a communication system for separating a reception channel and a transmission channel (or uplink and downlink) in a mobile communication system. In the TDD mode mobile communication system, the receiving and transmitting are in different time slots of the same frequency channel, namely carrier, and the receiving and transmitting channels are separated by using the guaranteed time; in the FDD mode, the receiving and transmitting are performed on two separate symmetric frequency channels, and the receiving and transmitting channels are separated by a guaranteed frequency band.
The characteristics and communication benefits of mobile communication systems employing different duplex modes are different. The uplink and downlink channels in the TDD mode mobile communication system use the same frequency, and thus have reciprocity of the uplink and downlink channels, which brings many advantages to the TDD mode mobile communication system.
In TDD mode, the transmission of information in uplink and downlink can be performed on the same carrier frequency, i.e. the transmission of information in uplink and the transmission of information in downlink are realized by time division on the same carrier.
Finally, it should be noted that each functional device in the embodiments of the present invention may be integrated into one processing device, or each device may exist alone physically, or two or more devices may be integrated into one device.
The functions, if implemented in the form of software-enabled devices and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. An automated big data distribution platform, the platform comprising:
the wired video recording equipment is positioned above a dining table of the banquet hall and used for executing video recording action on the position of the dining table so as to obtain a current video recording frame;
the big data end storage device is connected with the data acquisition device through a network and is used for storing and sending the male imaging characteristics and the female imaging characteristics;
the data acquisition equipment is connected with the bus type single chip microcomputer and used for identifying the number of male personnel and the number of female personnel in the image to be processed based on male imaging characteristics and female imaging characteristics;
a signal mapping device connected to the data acquisition device for determining the number of wine packages served at the party based on the number of male persons and for determining the number of beverage packages served at the party based on the number of female persons
The wireless uploading device is respectively connected with the signal mapping device and a server of a rear control room of the banquet hall and is used for wirelessly uploading the number of the wine packages and the number of the beverage packages to the server of the rear control room of the banquet hall;
the morphological processing equipment is connected with the wired video recording equipment, arranged in an instrument box below the dining table and used for executing morphological processing on the received current video recording frame so as to obtain and output a corresponding morphological processing image;
the morphological processing equipment comprises signal corrosion sub-equipment and signal expansion sub-equipment, wherein the signal expansion sub-equipment is connected with the signal corrosion sub-equipment and sends a processed image to the signal corrosion sub-equipment;
a cubic interpolation device connected to the morphological processing device, for performing an image interpolation process based on a cubic interpolation method on the received morphologically processed image to obtain and output a cubic interpolation image;
a redundancy analyzing device connected to the cubic interpolating device, for receiving the cubic interpolation image and the morphologically processed image, analyzing the signal redundancy of the morphologically processed image based on each pixel value of each pixel point of the morphologically processed image, and analyzing the signal redundancy of the cubic interpolation image based on each pixel value of each pixel point of the cubic interpolation image;
the command extraction device is connected with the redundancy analysis device and used for sending a first driving command when the multiple obtained by dividing the signal redundancy of the three-time interpolation image by the signal redundancy of the morphological processing image exceeds the limit;
the command extraction device is further used for sending a second driving command when the multiple obtained by dividing the signal redundancy of the three-time interpolation image by the signal redundancy of the morphological processing image is not over limit;
the bus type single chip microcomputer is respectively connected with the command extraction equipment and the cubic interpolation equipment and is used for controlling the cubic interpolation equipment to perform image interpolation processing based on a cubic interpolation method on the cubic interpolation image again when the second driving command is received so as to obtain a corresponding image to be processed;
and the bus type single chip microcomputer is also used for outputting the three-time interpolation image as an image to be processed when receiving the first driving command.
2. The automated big data distribution platform of claim 1, wherein the platform further comprises:
the signal analysis equipment is connected with the wired video recording equipment, arranged in an instrument box below the dining table and used for receiving the current video recording frame and analyzing the number of bytes occupied by the pixel value of each pixel point in the current video recording frame so as to obtain the number of reference bytes to be output;
and the pixel point counting equipment is used for receiving the current video recording frame and counting the total number of the pixel points in the current video recording frame so as to obtain a reference total number for outputting.
3. The automated big data distribution platform of claim 2, wherein the platform further comprises:
the number judgment device is respectively connected with the signal analysis device and the pixel point counting device and used for receiving the reference byte number and the reference total number and determining the data volume grade in direct proportion to the reference byte number and the reference total number based on the product of the reference byte number and the reference total number;
the embedded processing equipment is respectively connected with the quantity judging equipment and the field sharpening equipment and used for recovering power supply to the field sharpening equipment when the level of the received data volume exceeds the limit;
wherein the embedded processing device is further configured to cut off power to the field sharpening device when the received data volume level is not exceeded.
4. The automated big data distribution platform of claim 3, wherein the platform further comprises:
the field sharpening device is used for receiving the current video recording frame from the signal analysis device and executing smoothing processing operation on the current video recording frame so as to obtain and output a corresponding field sharpened image;
the median filtering device is connected with the field sharpening device and is used for receiving the field sharpened image and executing a median filtering operation on the field sharpened image to obtain a corresponding median filtered image;
and the channel value analysis equipment is connected with the median filtering equipment and is used for receiving the median filtering image and obtaining the saturation channel value, the brightness channel value and the hue channel value of each pixel point in the median filtering image.
5. The automated big data distribution platform of claim 4, wherein the platform further comprises:
the dynamic processing equipment is connected with the channel value analysis equipment and is used for executing image enhancement processing on a saturation pattern formed by each saturation channel value of each pixel point in the median filtered image to obtain a first enhancement pattern, executing image enhancement processing on a brightness pattern formed by each brightness channel value of each pixel point in the median filtered image to obtain a second enhancement pattern, and forming a tone pattern by each tone channel value of each pixel point in the median filtered image;
the data merging device is connected with the dynamic processing device and is used for merging the first enhancement pattern, the second enhancement pattern and the tone pattern to obtain a data merging image corresponding to the median filtering image;
the data merging device is further connected with the morphological processing device and is used for replacing the current video recording frame with the data merging image and sending the data merging image to the morphological processing device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910396432.1A CN110991213A (en) | 2019-05-14 | 2019-05-14 | Automatic big data distribution platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910396432.1A CN110991213A (en) | 2019-05-14 | 2019-05-14 | Automatic big data distribution platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110991213A true CN110991213A (en) | 2020-04-10 |
Family
ID=70081610
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910396432.1A Pending CN110991213A (en) | 2019-05-14 | 2019-05-14 | Automatic big data distribution platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110991213A (en) |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101742339A (en) * | 2010-01-14 | 2010-06-16 | 中山大学 | Method for enhancing color image |
| CN202103704U (en) * | 2011-03-30 | 2012-01-04 | 郭小卫 | Intelligent ordering dishes terminal |
| CN104537628A (en) * | 2015-01-16 | 2015-04-22 | 厦门大学 | Animation image adaptation method with controllable redundancy |
| CN107392869A (en) * | 2017-07-21 | 2017-11-24 | 长安大学 | A kind of facial image filtering method based on holding edge filter device |
| CN108391052A (en) * | 2013-01-21 | 2018-08-10 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN108734678A (en) * | 2018-05-22 | 2018-11-02 | 任阿毛 | Dining table closure of openings control system |
| CN108765014A (en) * | 2018-05-30 | 2018-11-06 | 中海云智慧（北京）物联网科技有限公司 | A kind of intelligent advertisement put-on method based on access control system |
| CN109063635A (en) * | 2018-07-27 | 2018-12-21 | 平安科技（深圳）有限公司 | A kind of apparatus control method, terminal and computer-readable medium |
| CN109255755A (en) * | 2018-10-24 | 2019-01-22 | 上海大学 | Image super-resolution rebuilding method based on multiple row convolutional neural networks |
| CN109472188A (en) * | 2018-08-21 | 2019-03-15 | 李叶 | Dual imaging filtering method |
| CN109527758A (en) * | 2018-12-05 | 2019-03-29 | 宁波敖群电器有限公司 | Bed body form regulation system |
| CN109559003A (en) * | 2017-09-27 | 2019-04-02 | 重庆凯泽科技股份有限公司 | Catering system and method based on recognition of face |
| CN109581520A (en) * | 2018-12-05 | 2019-04-05 | 余姚德诚科技咨询有限公司 | Conveying type personnel's scanning system |
| CN109571555A (en) * | 2018-12-07 | 2019-04-05 | 宁波宝尼尔厨具电器有限公司 | Intelligent three hair styles remove Hu device |
| WO2019068261A1 (en) * | 2017-10-06 | 2019-04-11 | Huawei Technologies Co., Ltd. | Bidirectional intra prediction |
| CN109602303A (en) * | 2018-11-26 | 2019-04-12 | 余姚市腾翔电子科技有限公司 | Multi-functional wooden round bath bucket |
| CN109615575A (en) * | 2018-12-07 | 2019-04-12 | 宁波可凡电器有限公司 | Request of mowing by hand triggers platform |
| CN109720358A (en) * | 2018-08-30 | 2019-05-07 | 蒋丽英 | Intelligent track train method for adjusting height |
-
2019
- 2019-05-14 CN CN201910396432.1A patent/CN110991213A/en active Pending
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101742339A (en) * | 2010-01-14 | 2010-06-16 | 中山大学 | Method for enhancing color image |
| CN202103704U (en) * | 2011-03-30 | 2012-01-04 | 郭小卫 | Intelligent ordering dishes terminal |
| CN108391052A (en) * | 2013-01-21 | 2018-08-10 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN104537628A (en) * | 2015-01-16 | 2015-04-22 | 厦门大学 | Animation image adaptation method with controllable redundancy |
| CN107392869A (en) * | 2017-07-21 | 2017-11-24 | 长安大学 | A kind of facial image filtering method based on holding edge filter device |
| CN109559003A (en) * | 2017-09-27 | 2019-04-02 | 重庆凯泽科技股份有限公司 | Catering system and method based on recognition of face |
| WO2019068261A1 (en) * | 2017-10-06 | 2019-04-11 | Huawei Technologies Co., Ltd. | Bidirectional intra prediction |
| CN108734678A (en) * | 2018-05-22 | 2018-11-02 | 任阿毛 | Dining table closure of openings control system |
| CN108765014A (en) * | 2018-05-30 | 2018-11-06 | 中海云智慧（北京）物联网科技有限公司 | A kind of intelligent advertisement put-on method based on access control system |
| CN109063635A (en) * | 2018-07-27 | 2018-12-21 | 平安科技（深圳）有限公司 | A kind of apparatus control method, terminal and computer-readable medium |
| CN109472188A (en) * | 2018-08-21 | 2019-03-15 | 李叶 | Dual imaging filtering method |
| CN109720358A (en) * | 2018-08-30 | 2019-05-07 | 蒋丽英 | Intelligent track train method for adjusting height |
| CN109255755A (en) * | 2018-10-24 | 2019-01-22 | 上海大学 | Image super-resolution rebuilding method based on multiple row convolutional neural networks |
| CN109602303A (en) * | 2018-11-26 | 2019-04-12 | 余姚市腾翔电子科技有限公司 | Multi-functional wooden round bath bucket |
| CN109581520A (en) * | 2018-12-05 | 2019-04-05 | 余姚德诚科技咨询有限公司 | Conveying type personnel's scanning system |
| CN109527758A (en) * | 2018-12-05 | 2019-03-29 | 宁波敖群电器有限公司 | Bed body form regulation system |
| CN109571555A (en) * | 2018-12-07 | 2019-04-05 | 宁波宝尼尔厨具电器有限公司 | Intelligent three hair styles remove Hu device |
| CN109615575A (en) * | 2018-12-07 | 2019-04-12 | 宁波可凡电器有限公司 | Request of mowing by hand triggers platform |
Non-Patent Citations (4)
| Title |
|---|
| SANG-YONG LEE 等: "A Novel Approach for Compression of Images Captured using Bayer Color Filter Arrays", 《ARXIV:0903.2272V1》 * |
| 何新龙: "监控***图像中人脸图像提取与增强的研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
| 周燕 等: "《第三代移动通信技术》", 31 May 2013, 《中国铁道出版社》 * |
| 王一丁 等: "《数字图像处理》", 31 August 2015, 《西安电子科技大学出版社》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104238390B (en) | Meal cooking control method and terminal | |
| CN108075784A (en) | Electronic equipment and the method for sending its wireless signal | |
| EP2903168B1 (en) | Apparatus and method for providing communication | |
| CN105357405B (en) | A kind of method for switching network, device and terminal | |
| CN103971278A (en) | Refrigerator shopping list generating system and refrigerator with refrigerator shopping list generating system | |
| CN104146605A (en) | Intelligent control method for drinking equipment | |
| CN109114737A (en) | Intelligent control method, system, equipment and the medium of air-conditioning | |
| CN108319641A (en) | Dish information input method and device | |
| CN107270608A (en) | A kind of refrigerator system and a kind of refrigerator | |
| CN105117993A (en) | Order-grabbing call service system and method | |
| CN109539684A (en) | A kind of intelligence adjusts the method and apparatus of refrigerator temperature and humidity | |
| CN101950198A (en) | Electronic reader with wireless internet access function and resource saving method thereof | |
| CN108255109A (en) | A kind of intelligence hot pot table and its Intelligent control method | |
| CN110991213A (en) | Automatic big data distribution platform | |
| CN111950319A (en) | Automatic big data distribution method | |
| CN104200315A (en) | Intelligent tableware and personalized dining information management system and method based on tableware | |
| CN108810632A (en) | A kind of split type television system | |
| CN106780170A (en) | The method of ordering and system of a kind of speech recognition | |
| CN112364816A (en) | Kitchen wearing monitoring system and method based on image recognition | |
| CN107197372A (en) | Method and device for shearing batch vertical screen videos and electronic equipment | |
| CN108307101A (en) | A kind of image processing method and electronic equipment, server | |
| CN109241436A (en) | Dressing mode recommended method, device, equipment and storage medium | |
| CN107481163A (en) | A kind of food and drink terminal service intelligent management system | |
| CN113179499A (en) | Smart power grid data aggregation control method and device, base station terminal and medium | |
| CN107204784A (en) | Multi-functional communications equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200410 |