CN109118449B - Current carpet type identification system - Google Patents
Current carpet type identification system Download PDFInfo
- Publication number
- CN109118449B CN109118449B CN201810950955.1A CN201810950955A CN109118449B CN 109118449 B CN109118449 B CN 109118449B CN 201810950955 A CN201810950955 A CN 201810950955A CN 109118449 B CN109118449 B CN 109118449B
- Authority
- CN
- China
- Prior art keywords
- carpet
- image
- chest
- equipment
- current
- 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.)
- Active
Links
- 238000013500 data storage Methods 0.000 claims abstract description 9
- 238000001514 detection method Methods 0.000 claims abstract description 7
- 238000012163 sequencing technique Methods 0.000 claims description 12
- 230000011218 segmentation Effects 0.000 claims description 11
- 230000000875 corresponding effect Effects 0.000 claims description 9
- 230000008602 contraction Effects 0.000 claims description 7
- 238000000034 method Methods 0.000 claims description 7
- 239000007921 spray Substances 0.000 claims description 5
- 239000000203 mixture Substances 0.000 claims description 4
- 230000002596 correlated effect Effects 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 241000208340 Araliaceae Species 0.000 claims description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 claims description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims description 2
- 235000008434 ginseng Nutrition 0.000 claims description 2
- 238000005507 spraying Methods 0.000 claims description 2
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 210000004556 brain Anatomy 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 238000000465 moulding Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of current carpet type identification systems, comprising: the top of chest is arranged in start button, near the handle of chest, for receiving the pressing operation of user, to determine whether chest currently enters Power assisted control mode；Big data storage end, for carpet gray threshold range to be stored in advance, the carpet gray threshold range is made of carpet gray scale upper limit threshold and carpet gray scale lower threshold, and the value of the carpet gray scale upper limit threshold and the carpet gray scale lower threshold is all between 0-255；The top of chest is arranged in carpet capture apparatus, for carrying out instant image taking to the carpet near the chest, to obtain corresponding instant carpet image；The top of chest is arranged in dynamic range detection device, for receiving the instant carpet image, detects to the current dynamic range of the instant carpet image, to obtain the current dynamic range.By means of the invention it is possible to be effectively improved the performance for pushing away case.
Description
Technical field
The present invention relates to big data field of storage more particularly to a kind of current carpet type identification systems.
Background technique
Big data storage is commonly referred to as those enormous amounts, is difficult to the data set collected, handle, analyzed, and also refers to those
The data saved for a long time in traditional infrastructure.Here " big " has several layers of meanings, it can describe the size of tissue, and more
Importantly, it defines the scale of IT infrastructure in enterprise.Unlimited expectation-business has been expressed big data application in the industry
The more multivalence value of information accumulation is also bigger-only we need a method that these values are excavated.
Explosive with big data application increases, it has derived oneself unique framework, and directly pushes away
The development of storage, network and computing technique is moved.Processing this special demand of big data is a new challenge after all.Firmly
The development of part is final or is pushed by software requirement, and for this example, we are apparent to see that big data analysis is answered
The development of data storage infrastructure is being affected with demand.
On the other hand, this variation can't say that it is wrong a chance to storage manufacturer and other IT infrastructure manufacturers.
With the sustainable growth of structural data and unstructured data amount, and the diversification of analysis data source, storage before this is
The design of system can no longer meet the needs of big data application.Storage manufacturer has appreciated that this point, they start to modify base
In the architecture design of the storage system of block and file to adapt to these new requirements.
Summary of the invention
In order to solve the technical issues of chest push lacks power-assisted in the prior art, the present invention provides a kind of current carpets
Type identification system is improved the real-time and accuracy of data using big data storage end, is currently entering Power assisted control in chest
When mode and current carpet type are resistance type carpet, gas is sprayed rearward to push chest to Forward with angle on the lower side
It is dynamic, to accelerate the pushing speed and efficiency of chest；And in image procossing, by the noise class of the preceding preset quantity of serial number
The quantity of type determines the number of plies for carrying out signal segmentation based on the maximum noise quantity, by the height as maximum noise quantity
The quantity of various noise types in clear image is determined based on the reference noise quantity to wavelet systems as reference noise quantity
The percent value that number is reduced, realizes the specific aim image denoising of image content-based.
According to an aspect of the present invention, a kind of current carpet type identification system is provided, the system comprises:
The top of chest is arranged in start button, near the handle of chest, for receiving the pressing operation of user,
To determine whether chest currently enters Power assisted control mode；Big data storage end, for carpet gray threshold range to be stored in advance,
The carpet gray threshold range is made of carpet gray scale upper limit threshold and carpet gray scale lower threshold, the carpet gray scale upper limit
Threshold value and the value of the carpet gray scale lower threshold are all between 0-255；The top of chest is arranged in carpet capture apparatus,
For carrying out instant image taking to the carpet near the chest, to obtain corresponding instant carpet image, and described in output
Instant carpet image；The top of chest is arranged in dynamic range detection device, for receiving the instant carpet image, to institute
The current dynamic range for stating instant carpet image is detected, to obtain the current dynamic range；Dynamic range adjusts equipment,
It connect with the dynamic range detection device, for receiving the instant carpet image and the current dynamic range, and is based on
The current dynamic range carries out dynamic range adjustment to the instant carpet image, so that the instant carpet image is dynamic
State range expands to default dynamic range section, and the range after the dynamic range adjustment equipment output adjustment corrects image；It makes an uproar
Sound sequencing equipment is connect with dynamic range adjustment equipment, for receiving the range amendment image, is corrected to the range
Various noise types in image carry out sorting from large to small for maximum amplitude, by the noise type of the preceding preset quantity of serial number
Quantity as maximum noise quantity export；Quantity statistics equipment obtains the range for receiving the range amendment image
Correct image in various noise types quantity, and using the range correct image in various noise types quantity as
The output of reference noise quantity；The number of plies acquires equipment, connect with the noise sequencing equipment, for receiving the maximum noise number
Amount, and the number of plies for carrying out signal segmentation is determined based on the maximum noise quantity, wherein the maximum noise quantity is more, into
The number of plies of row signal segmentation is more, and the number of plies acquisition equipment is defeated as the target number of plies using the number of plies of determining progress signal segmentation
Out；Reference device is denoised, is connect with the quantity statistics equipment, for receiving the reference noise quantity, and is based on the ginseng
It examines amount of noise and determines the percent value reduced to wavelet coefficient, wherein the reference noise quantity is more, pair determined
The percent value that wavelet coefficient is reduced is smaller, and the denoising reference device will determine the percentage reduced to wavelet coefficient
Ratio is exported as target percentage value；Denoising executes equipment, sets respectively with the noise sequencing equipment and denoising reference
Standby connection, for receiving the range amendment image, the target number of plies and the target percentage value, using Haar wavelet transform base
The signal decomposition of the target number of plies is executed to range amendment image based on the target number of plies, with obtain from first layer to
Top each high frequency coefficient and top each low frequency coefficient, to from first layer to top each high frequency coefficient into
Numerical value of the row based on target percentage value is shunk, to obtain high frequency coefficient after from first layer to top each contraction, and base
High frequency coefficient and top each low frequency coefficient reconstruct the model after the first layer to top each contraction
Enclosing amendment, image is corresponding has executed image；Carpet identifies equipment, executes equipment with the denoising and connect, for described in receiving
Execute image, based on default carpet gray threshold range to it is described executed image and execute carpet pattern extract, and to extracting
Carpet image carry out type identification, to obtain and export corresponding current carpet type；Autoamtic boosting equipment is arranged in chest
Low side, connect respectively with the carpet capture apparatus and the start button, for being currently entering Power assisted control mould in chest
When formula and the current carpet type are resistance type carpet, gas is sprayed rearward to push chest forward with angle on the lower side
It is mobile；Wherein, the autoamtic boosting equipment is also used to when chest is currently entering non-Power assisted control mode, is stopped with angle on the lower side
Degree rearward sprays gas.
More specifically, in the current carpet type identification system: it includes that signal receives list that the denoising, which executes equipment,
Member, signal shrink unit and signal output unit.
More specifically, in the current carpet type identification system: the signal receiving unit is for receiving the model
Enclose amendment image, the target number of plies and the target percentage value.
More specifically, in the current carpet type identification system: being executed in equipment in the denoising, to the highest
Each low frequency coefficient of layer carries out data reservation process.
More specifically, in the current carpet type identification system: the signal shrink unit respectively with the signal
Receiving unit is connected with the signal output unit.
More specifically, in the current carpet type identification system: in the noise sequencing equipment, by serial number preceding
The quantity of noise type of preset quantity as the output of maximum noise quantity include: that the preset quantity and the range are corrected
The relationship that the resolution of image is positively correlated.
More specifically, in the current carpet type identification system: the autoamtic boosting equipment is also used to work as in chest
When to advance into Power assisted control mode and the current carpet type be non-resistance type carpet, stop with angle on the lower side rearward
Spray gas.
More specifically, in the current carpet type identification system: the start button continuously presses odd number in user
When secondary, enter Power assisted control mode from non-Power assisted control mode.
More specifically, in the current carpet type identification system: the start button continuously presses even number in user
When secondary, enter non-Power assisted control mode from Power assisted control mode.
Detailed description of the invention
Embodiment of the present invention is described below with reference to attached drawing, in which:
Fig. 1 is that the structure of the chest according to applied by the current carpet type identification system shown in embodiment of the present invention is shown
It is intended to.
Specific embodiment
The embodiment of current carpet type identification system of the invention is described in detail below with reference to accompanying drawings.
The difference that big data storage and traditional data store, one of big data application be mainly characterized by real-time or
Near real-time.
Similar, the application of a financial class can quickly excavate in the miscellaneous data of enormous amount for business personnel
Relevant information out can help them to lead over the decision that rival makes transaction.
Data are usually quickly increased sharply with the speed for increasing by 50% every year, especially unstructured data.With science and technology into
Step has more and more sensor acquisition data, mobile device, social multimedia etc., so data are only possible to continue to increase.
To sum up, big data needs very high-performance, the infrastructure device of high-throughput, large capacity.
In order to overcome above-mentioned deficiency, the present invention has built a kind of current carpet type identification system, can effectively solve the problem that phase
The technical issues of answering.
Fig. 1 is that the structure of the chest according to applied by the current carpet type identification system shown in embodiment of the present invention is shown
It is intended to.
The current carpet type identification system shown according to an embodiment of the present invention includes:
The top of chest is arranged in start button, near the handle of chest, for receiving the pressing operation of user,
To determine whether chest currently enters Power assisted control mode；
Big data storage end, for carpet gray threshold range to be stored in advance, the carpet gray threshold range is by carpet
Gray scale upper limit threshold and carpet gray scale lower threshold composition, the carpet gray scale upper limit threshold and the carpet gray scale lower threshold
Value all between 0-255；
The top of chest is arranged in carpet capture apparatus, for carrying out instant image bat to the carpet near the chest
It takes the photograph, to obtain corresponding instant carpet image, and exports the instant carpet image；
The top of chest is arranged in dynamic range detection device, for receiving the instant carpet image, to described instant
The current dynamic range of carpet image is detected, to obtain the current dynamic range；
Dynamic range adjusts equipment, connect with the dynamic range detection device, for receiving the instant carpet image
With the current dynamic range, and dynamic range adjustment is carried out to the instant carpet image based on the current dynamic range,
So that the dynamic range expansion of the instant carpet image is to default dynamic range section, it is defeated that the dynamic range adjusts equipment
Range adjusted corrects image out；
Noise sequencing equipment is connect with dynamic range adjustment equipment, for receiving the range amendment image, to institute
The various noise types stated in range amendment image carry out sorting from large to small for maximum amplitude, by the preceding preset quantity of serial number
Noise type quantity as maximum noise quantity export；
Quantity statistics equipment, for receiving range amendment image, obtain in the range amendment image various makes an uproar
The quantity of sound type, and the quantity that the range corrects the various noise types in image is exported as reference noise quantity；
The number of plies acquires equipment, connect with the noise sequencing equipment, for receiving the maximum noise quantity, and is based on institute
It states maximum noise quantity and determines the number of plies for carrying out signal segmentation, wherein the maximum noise quantity is more, carries out signal segmentation
The number of plies is more, and the number of plies acquisition equipment exports the number of plies of determining progress signal segmentation as the target number of plies；
Reference device is denoised, is connect with the quantity statistics equipment, for receiving the reference noise quantity, and is based on institute
It states reference noise quantity and determines the percent value reduced to wavelet coefficient, wherein the reference noise quantity is more, determines
Percent value that wavelet coefficient is reduced it is smaller, the denoising reference device, which will determine, reduces wavelet coefficient
Percent value is exported as target percentage value；
Denoising executes equipment, connect respectively with the noise sequencing equipment and the denoising reference device, for receiving
Range amendment image, the target number of plies and the target percentage value are stated, the target number of plies is based on using Haar wavelet transform base
The signal decomposition of the target number of plies is executed, to range amendment image to obtain from first layer to top each high frequency
Coefficient and top each low frequency coefficient, to being carried out from first layer to top each high frequency coefficient based on target percentage
The numerical value of value is shunk, to obtain high frequency coefficient after from first layer to top each contraction, and based on the first layer to most
It is corresponding to reconstruct the range amendment image for high frequency coefficient and top each low frequency coefficient after high-rise each contraction
Image is executed；
Carpet identifies equipment, executes equipment with the denoising and connect, for receive it is described executed image, based on presetting ground
Blanket gray threshold range executes carpet pattern extraction to the image that executed, and carries out type knowledge to the carpet image extracted
Not, to obtain and export corresponding current carpet type；
The low side of chest is arranged in autoamtic boosting equipment, connects respectively with the carpet capture apparatus and the start button
It connects, for when it is resistance type carpet that chest, which is currently entering Power assisted control mode and the current carpet type, on the lower side
Angle sprays gas rearward to push chest to move forward；
Wherein, the autoamtic boosting equipment is also used to when chest is currently entering non-Power assisted control mode, is stopped on the lower side
Angle rearward spray gas.
Then, continue that the specific structure of current carpet type identification system of the invention is further detailed.
In the current carpet type identification system: it includes signal receiving unit, signal receipts that the denoising, which executes equipment,
Contracting unit and signal output unit.
In the current carpet type identification system: the signal receiving unit is for receiving the range correction map
Picture, the target number of plies and the target percentage value.
In the current carpet type identification system: being executed in equipment in the denoising, to described top each
Low frequency coefficient carries out data reservation process.
In the current carpet type identification system: the signal shrink unit respectively with the signal receiving unit and
The signal output unit connection.
In the current carpet type identification system: in the noise sequencing equipment, by the preceding present count of serial number
The quantity of the noise type of amount is as the solution that the output of maximum noise quantity includes: that the preset quantity and the range correct image
The relationship that analysis degree is positively correlated.
In the current carpet type identification system: the autoamtic boosting equipment is also used to be currently entering power-assisted in chest
When control model and the current carpet type are non-resistance type carpet, stop rearward spraying gas with angle on the lower side.
In the current carpet type identification system: the start button is when user continuously presses odd-times, from non-
Power assisted control mode enters Power assisted control mode.
In the current carpet type identification system: the start button is when user continuously presses even-times, from helping
Force control mode enters non-Power assisted control mode.
In addition, the carpet identification equipment is realized by SOC chip.System on Chip, abbreviation SOC namely on piece
System.It is said from narrow sense angle, he is the integrated chip of information system core, is that system core component is integrated in chip piece
On；It is said from broadest scope, SoC is a mini system, if central processing unit (CPU) is brain, then SOC is exactly to wrap
The system for including brain, heart, eyes and hand.Domestic and international academia, which is generally inclined to, is defined as SOC by microprocessor, simulation IP
Core, digital IP kernel and memory (or piece external storage control interface) integrate on a single chip, he is usually customization, or
It is the standardized product towards special-purpose.
The basic content that SOC is defined is mainly both ways: one is his composition, the second is his forming process.It is system-level
The composition of chip can be system level chip control logic module, microprocessor/microcontroller CPU core module, digital signal
Processor DSP module, the memory module of insertion and the external interface module communicated, the AFE(analog front end) containing ADC/DAC
Module, power supply provides and power managed module, and SOC wireless for one there are also RF front-end module, user defines logic, and (he can
By FPGA or ASIC realization) and microelectron-mechanical module, it is often more important that a SOC chip is embedded with basic software
(RDOS or COS and other application software) module or the user software that can be loaded into etc..
Using current carpet type identification system of the invention, adaptive power-assisted can not be provided for case is pushed away in the prior art
The technical issues of, by introducing big data storage end, the real-time and accuracy of data are improved, is currently entering power-assisted control in chest
When molding formula and current carpet type are resistance type carpet, gas is sprayed rearward to push chest forward with angle on the lower side
It is mobile, to accelerate the pushing speed and efficiency of chest；And in image procossing, by the noise of the preceding preset quantity of serial number
The quantity of type determines the number of plies for carrying out signal segmentation based on the maximum noise quantity as maximum noise quantity, will be described
The quantity of various noise types in high-definition image is determined based on the reference noise quantity to small echo as reference noise quantity
The percent value that coefficient is reduced, realizes the specific aim image denoising of image content-based, to solve above-mentioned technology
Problem.
It is understood that although the present invention has been disclosed in the preferred embodiments as above, above-described embodiment not to
Limit the present invention.For any person skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications all are made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of variation.Therefore, anything that does not depart from the technical scheme of the invention are right according to the technical essence of the invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments still fall within the range of technical solution of the present invention protection
It is interior.
Claims (9)
1. a kind of current carpet type identification system, the system comprises:
The top of chest is arranged in start button, near the handle of chest, for receiving the pressing operation of user, with true
Determine whether chest currently enters Power assisted control mode；
Big data storage end, for carpet gray threshold range to be stored in advance, the carpet gray threshold range is by carpet gray scale
Upper limit threshold and carpet gray scale lower threshold composition, the carpet gray scale upper limit threshold and the carpet gray scale lower threshold take
Value is all between 0-255；
The top of chest is arranged in carpet capture apparatus, for carrying out instant image taking to the carpet near the chest, with
Corresponding instant carpet image is obtained, and exports the instant carpet image；
The top of chest is arranged in dynamic range detection device, for receiving the instant carpet image, to the instant carpet
The current dynamic range of image is detected, to obtain the current dynamic range；
Dynamic range adjusts equipment, connect with the dynamic range detection device, for receiving the instant carpet image and institute
Current dynamic range is stated, and dynamic range adjustment is carried out to the instant carpet image based on the current dynamic range, so that
The dynamic range expansion of the instant carpet image is obtained to default dynamic range section, the dynamic range adjustment equipment, which exports, to be adjusted
Range after whole corrects image；
Noise sequencing equipment is connect with dynamic range adjustment equipment, for receiving the range amendment image, to the model
The various noise types enclosed in amendment image carry out sorting from large to small for maximum amplitude, by making an uproar for the preceding preset quantity of serial number
The quantity of sound type is exported as maximum noise quantity；
Quantity statistics equipment obtains the various noise classes in the range amendment image for receiving the range amendment image
The quantity of type, and the quantity that the range corrects the various noise types in image is exported as reference noise quantity；
The number of plies acquires equipment, connect with the noise sequencing equipment, for receiving the maximum noise quantity, and based on described in most
Big amount of noise determines the number of plies for carrying out signal segmentation, wherein the maximum noise quantity is more, carries out the number of plies of signal segmentation
More, the number of plies acquisition equipment exports the number of plies of determining progress signal segmentation as the target number of plies；
Reference device is denoised, is connect with the quantity statistics equipment, for receiving the reference noise quantity, and is based on the ginseng
It examines amount of noise and determines the percent value reduced to wavelet coefficient, wherein the reference noise quantity is more, pair determined
The percent value that wavelet coefficient is reduced is smaller, and the denoising reference device will determine the percentage reduced to wavelet coefficient
Ratio is exported as target percentage value；
Denoising executes equipment, connect respectively with the noise sequencing equipment and the denoising reference device, for receiving the model
Amendment image, the target number of plies and the target percentage value are enclosed, the target number of plies is based on to institute using Haar wavelet transform base
The signal decomposition that range amendment image executes the target number of plies is stated, to obtain from first layer to top each high frequency coefficient
With top each low frequency coefficient, carry out to from first layer to top each high frequency coefficient based on target percentage value
Numerical value is shunk, to obtain high frequency coefficient after from first layer to top each contraction, and based on the first layer to top
Each contraction after high frequency coefficient and top each low frequency coefficient reconstruct the range amendment image be corresponding and held
Row image；
Carpet identifies equipment, executes equipment with the denoising and connect, for receive it is described executed image, it is grey based on carpet is preset
Degree threshold range executes carpet pattern extraction to the image that executed, and carries out type identification to the carpet image extracted,
To obtain and export corresponding current carpet type；
The low side of chest is arranged in autoamtic boosting equipment, connect respectively with the carpet capture apparatus and the start button, uses
In when it is resistance type carpet that chest, which is currently entering Power assisted control mode and the current carpet type, with angle on the lower side to
Gas is sprayed to push chest to move forward in rear；
Wherein, the autoamtic boosting equipment is also used to when chest is currently entering non-Power assisted control mode, is stopped with angle on the lower side
Degree rearward sprays gas.
2. current carpet type identification system as described in claim 1, it is characterised in that:
It includes signal receiving unit, signal contraction unit and signal output unit that the denoising, which executes equipment,.
3. current carpet type identification system as claimed in claim 2, it is characterised in that:
The signal receiving unit is for receiving the range amendment image, the target number of plies and the target percentage value.
4. current carpet type identification system as claimed in claim 3, it is characterised in that:
It is executed in equipment in the denoising, data reservation process is carried out to top each low frequency coefficient.
5. current carpet type identification system as claimed in claim 4, it is characterised in that:
The signal shrinks unit and connect respectively with the signal receiving unit and the signal output unit.
6. current carpet type identification system as claimed in claim 5, it is characterised in that:
In the noise sequencing equipment, using the quantity of the noise type of the preceding preset quantity of serial number as maximum noise quantity
Output includes: the preset quantity and the range corrects the relationship that the resolution of image is positively correlated.
7. current carpet type identification system as claimed in claim 6, it is characterised in that:
The autoamtic boosting equipment is also used to be currently entering Power assisted control mode in chest and the current carpet type is non-resistance
When power type carpet, stop rearward spraying gas with angle on the lower side.
8. current carpet type identification system as claimed in claim 7, it is characterised in that:
The start button enters Power assisted control mode when user continuously presses odd-times, from non-Power assisted control mode.
9. current carpet type identification system a method as claimed in any one of claims 1-8, it is characterised in that:
The start button enters non-Power assisted control mode when user continuously presses even-times, from Power assisted control mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810950955.1A CN109118449B (en) | 2018-08-21 | 2018-08-21 | Current carpet type identification system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810950955.1A CN109118449B (en) | 2018-08-21 | 2018-08-21 | Current carpet type identification system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109118449A CN109118449A (en) | 2019-01-01 |
| CN109118449B true CN109118449B (en) | 2019-10-18 |
Family
ID=64852503
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810950955.1A Active CN109118449B (en) | 2018-08-21 | 2018-08-21 | Current carpet type identification system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109118449B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109717838A (en) * | 2019-01-14 | 2019-05-07 | 于蓝 | Diagnostic device real-time servicing platform |
| CN110012567B (en) * | 2019-02-28 | 2022-03-18 | 武汉纺织大学 | Automatic electric blanket cloth paving device capable of recycling electric blanket templates |
| CN110012566B (en) * | 2019-02-28 | 2021-11-12 | 武汉纺织大学 | Automatic electric blanket production device capable of producing electric blankets of different models |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9789963B2 (en) * | 2012-02-14 | 2017-10-17 | C&D Zodiac, Inc. | Pivot bin assembly with minimal force required for closing |
| CN103853154B (en) * | 2012-12-05 | 2018-09-18 | 德国福维克控股公司 | The cleaning equipment that can be walked and the method for running this equipment |
| CN207411686U (en) * | 2017-09-26 | 2018-05-29 | 浙江师范大学 | A kind of intelligence power-assisted luggage case |
-
2018
- 2018-08-21 CN CN201810950955.1A patent/CN109118449B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109118449A (en) | 2019-01-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109118449B (en) | Current carpet type identification system | |
| CN105760851B (en) | The method and terminal of a kind of fingerprint recognition | |
| CN102662473B (en) | The device and method of man-machine information interaction is realized based on eye motion recognition | |
| CN106599028B (en) | Book content searching and matching method based on video image processing | |
| CN101593205B (en) | Video-based method for searching three-dimension model | |
| CN106846272A (en) | A kind of denoising compressing method of point cloud model | |
| CN110363800B (en) | Accurate rigid body registration method based on fusion of point set data and characteristic information | |
| CN105303173A (en) | Method and device for reducing misrecognition rate | |
| RU2009135635A (en) | DEVICE FOR PROCESSING IMAGES, METHOD FOR PROCESSING IMAGES AND PROGRAM | |
| CN105590319A (en) | Method for detecting image saliency region for deep learning | |
| CN108323206B (en) | Fingerprint data processing method and device and computer readable storage medium | |
| CN103955682A (en) | Behavior recognition method and device based on SURF interest points | |
| US20130022236A1 (en) | Apparatus Capable of Detecting Location of Object Contained in Image Data and Detection Method Thereof | |
| CN112287865B (en) | Human body posture recognition method and device | |
| CN110188639A (en) | Face image processing process and its system, computer equipment, readable storage medium storing program for executing | |
| CN111046825A (en) | Human body posture recognition method, device and system and computer readable storage medium | |
| CN113902785B (en) | Depth image processing method, system, device and computer storage medium | |
| CN106022227A (en) | Gesture identification method and apparatus | |
| CN103745209A (en) | Human face identification method and system | |
| CN107451444A (en) | Solve lock control method and Related product | |
| CN105243658A (en) | Plant depth feature recognition method based on Kinect sensor | |
| CN108133169A (en) | A kind of embark on journey processing method and its device for text image | |
| CN108932492A (en) | A kind of image fingerprint extracting method based on non-sampled shearing wave conversion | |
| CN105549746A (en) | Action identification method based on acceleration sensing chip | |
| CN107657230A (en) | A kind of bank self-help robot character recognition device |
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 | ||
| CB03 | Change of inventor or designer information |
Inventor after: Xu Jianqing Inventor after: Sun Yan Inventor before: Sun Yan |
|
| CB03 | Change of inventor or designer information | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190916 Address after: Room 1204, No. B07, Hubin South Road, Siming District, Xiamen City, Fujian Province, 361000 Applicant after: Xu Jian Qing Address before: 224003 No. 23 Xinyan Road, Xinyang Economic Zone, Tinghu District, Yancheng City, Jiangsu Province Applicant before: Sun Yan |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |