CN110895825B - Missing data detection system and method - Google Patents
Missing data detection system and method Download PDFInfo
- Publication number
- CN110895825B CN110895825B CN201911069991.8A CN201911069991A CN110895825B CN 110895825 B CN110895825 B CN 110895825B CN 201911069991 A CN201911069991 A CN 201911069991A CN 110895825 B CN110895825 B CN 110895825B
- Authority
- CN
- China
- Prior art keywords
- paint
- image
- equipment
- missing data
- detection system
- 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
- 238000001514 detection method Methods 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 18
- 239000003973 paint Substances 0.000 claims abstract description 76
- 238000013500 data storage Methods 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 claims description 28
- 238000001914 filtration Methods 0.000 claims description 27
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims description 18
- 230000009466 transformation Effects 0.000 claims description 18
- 230000007246 mechanism Effects 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 3
- 238000010422 painting Methods 0.000 abstract description 2
- 238000000576 coating method Methods 0.000 description 8
- 239000011248 coating agent Substances 0.000 description 7
- 239000000463 material Substances 0.000 description 6
- 239000000126 substance Substances 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000001444 catalytic combustion detection Methods 0.000 description 3
- 238000005034 decoration Methods 0.000 description 3
- 239000000945 filler Substances 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 230000010354 integration Effects 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 239000002904 solvent Substances 0.000 description 2
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 239000012752 auxiliary agent Substances 0.000 description 1
- 239000011449 brick Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000004927 clay Substances 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000012847 fine chemical Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 239000000049 pigment Substances 0.000 description 1
- 239000000843 powder Substances 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002966 varnish Substances 0.000 description 1
- 239000002023 wood Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
Abstract
The invention relates to a missing data detection system and a method, wherein the system comprises: the data storage device is arranged in the handheld measuring instrument and is used for pre-storing each building area of each wall of the room to be checked and accepted; the area identification device is used for calculating the sum of all building areas of all walls to serve as a first statistical area, receiving all paint areas of all paint objects, and calculating the sum of all paint areas of all paint objects to serve as a second statistical area; and the signal distribution equipment is used for sending out an insufficient painting signal when the first statistical area exceeds the second statistical area and reaches a preset value. The missing data detection system and the method are customized in structure and stable in operation. The total area of the paint in the room can be effectively estimated, so that whether paint is leaked or not in the current room can be determined, and a detection result of missing data can be quickly given.
Description
Technical Field
The invention relates to the field of wall surface detection, in particular to a missing data detection system and method.
Background
The surface of the wall is generally mentioned more in the indoor decoration. The wall decoration treatment is generally painting or wall paper sticking.
The exterior surface facing of the wall body is divided into an indoor wall surface and an outdoor wall surface. Wall finishing is an integral part of building design. The modern indoor wall surface beautifies the indoor environment and adjusts the illumination by using the change of color and texture, and various materials with easy cleaning and good physical properties are selected to meet the using functions in various aspects. The outdoor wall surface directly influences the appearance of a building and the appearance of a city, and materials with certain waterproof and weatherproof performance are selected according to the use requirements and technical and economic conditions of the building, so that the wall structure is protected, and the appearance is kept clean. The wall body built by clay bricks or natural stones with excellent quality has plain appearance and good weather resistance and pollution resistance, can not be used as a wall surface, and is called as a dry wall. The joint between the two ends of the dry wall is to be treated neatly and compactly to prevent rainwater from leaking. If a special template is selected for pouring the concrete wall, wood grains or various concave-convex geometric patterns and the like are left on the outer wall surface after the template is removed. Such walls are known as bare concrete walls.
Disclosure of Invention
In order to solve the related problems in the prior art, the invention provides a missing data detection system which can obtain the sum of the areas of all buildings of all walls in a room as a first statistical area, obtain the sum of the areas of all paint surfaces of all paint surface objects in an imaging image of the room as a second statistical area, and determine whether the paint in the room has a missing phenomenon or not based on the numerical relationship of the two areas; the method is particularly characterized in that the paint area of the paint object is calculated based on the number of all pixel points occupied by each paint object and the depth of field value corresponding to the paint object, so that valuable reference data are provided for subsequent analysis.
According to an aspect of the present invention, there is provided a missing data detection system, the system including:
and the data storage device is arranged in the handheld measuring instrument and is used for pre-storing each building area of each wall of the room to be checked and accepted.
More specifically, in the missing data detection system, the system further includes:
and the area identification device is connected with the data storage device and used for calculating the sum of all building areas of all walls to serve as a first statistical area, receiving all paint areas of all paint objects and calculating the sum of all paint areas of all paint objects to serve as a second statistical area.
More specifically, in the missing data detection system, the system further includes:
the signal distribution equipment is connected with the area identification equipment and is used for sending out a paint shortage signal when the first statistical area exceeds the second statistical area and reaches a preset value or sending out a paint sufficiency signal if the first statistical area does not exceed the second statistical area;
the fisheye collecting mechanism is arranged at the top end of the handheld measuring instrument, placed in a room to be checked and received, and used for collecting image data in the room under the manual operation of a user to obtain a panoramic collected image;
the edge-preserving filtering equipment is connected with the fisheye collecting mechanism and used for performing edge-preserving smooth filtering processing on the panoramic collected image based on the maximum noise amplitude in the received panoramic collected image so as to obtain a corresponding edge-preserving filtered image, wherein the larger the maximum noise amplitude is, the larger the amplitude of the edge-preserving smooth filtering processing on the panoramic collected image is;
the spatial domain enhancement processing equipment is connected with the edge-preserving filtering equipment and is used for executing image spatial domain enhancement processing on the received edge-preserving smooth filtering image so as to obtain a spatial domain enhancement processing image;
the affine transformation device is connected with the spatial domain enhancement processing device and used for executing affine transformation on the received spatial domain enhancement processing image to obtain an affine transformation image;
the color analysis equipment is arranged in the handheld measuring instrument, is connected with the affine transformation equipment and is used for identifying the number of pixel points occupied by each paint surface object from the affine transformation image based on the color characteristics of the paint in the preset type;
the depth of field measuring equipment is arranged in the handheld measuring instrument and is used for acquiring each depth of field value corresponding to each paint surface object in the affine transformation image;
and the parameter conversion equipment is respectively connected with the color analysis equipment, the depth of field measurement equipment and the area identification equipment and is used for calculating the paint area of each paint object based on the number of the pixel points occupied by each paint object and the depth of field value corresponding to each paint object.
According to another aspect of the present invention, there is also provided a missing data detection method, including: a missing data detection system is used to determine whether paint in the room is missing based on the sum of the individual building areas of the individual walls and the sum of the individual paint areas of the identified individual paint objects.
The missing data detection system and the method are customized in structure and stable in operation. The total area of the paint in the room can be effectively estimated, so that whether paint is leaked or not in the current room can be determined, and a detection result of missing data can be quickly given.
Therefore, the invention mainly has the following important invention points:
(1) acquiring the sum of the building areas of all walls in a room to serve as a first statistical area, acquiring the sum of the paint areas of all paint objects in an imaging image of the room to serve as a second statistical area, and determining whether paint in the room is omitted or not based on the numerical relationship between the first statistical area and the second statistical area;
(2) and calculating the paint area of the paint object based on the number of the pixel points occupied by each paint object and the depth of field value corresponding to the paint object, thereby providing valuable reference data for subsequent analysis.
Detailed Description
Embodiments of the missing data detection system and method of the present invention will be described in detail below.
Paint is a chemical mixture coating that can be firmly covered on the surface of an object for protection, decoration, marking and other special purposes. The book "coating technology" is defined as follows: the paint is a material which can be coated on the surface of an object by different construction processes to form a continuous solid film with firm adhesion and certain strength. The film thus formed is generally called a coating film, also called a paint film or a coating. "
The paint is generally composed of four parts, namely a film forming substance, a filler (pigment and filler), a solvent and an auxiliary agent. The composition may vary somewhat depending on the performance requirements, e.g., the varnish may be free of color filler and the powder coating may be free of solvent.
Belongs to organic chemical high molecular materials, and the formed coating belongs to a high molecular compound type. According to the modern popular classification of chemical products, the coating belongs to fine chemical products. Modern coatings are gradually becoming a multifunctional engineering material, an important industry in the chemical industry.
At present, some painters are in save material or lazy reason when applying paint with a brush the wall, and the japanning to the wall is incomplete, has the condition that the wall japanning was omitted, and in some paint finishing colour lighter's japanning scenes, it is difficult for the manual detection mode to discover which local wall japanning is omitted, consequently, needs a more accurate wall japanning to omit the mechanism, can be fast, automatically discernment exist in waiting to inspect the room whether the wall japanning is omitted the condition.
In order to overcome the defects, the invention builds the missing data detection system and the method thereof, and can effectively solve the corresponding technical problems.
A missing data detection system shown according to an embodiment of the present invention includes:
and the data storage device is arranged in the handheld measuring instrument and is used for pre-storing each building area of each wall of the room to be checked and accepted.
Next, a detailed description of the missing data detection system of the present invention will be further continued.
The missing data detection system may further include:
and the area identification device is connected with the data storage device and used for calculating the sum of all building areas of all walls to serve as a first statistical area, receiving all paint areas of all paint objects and calculating the sum of all paint areas of all paint objects to serve as a second statistical area.
The missing data detection system may further include:
the signal distribution equipment is connected with the area identification equipment and is used for sending out a paint shortage signal when the first statistical area exceeds the second statistical area and reaches a preset value or sending out a paint sufficiency signal if the first statistical area does not exceed the second statistical area;
the fisheye collecting mechanism is arranged at the top end of the handheld measuring instrument, placed in a room to be checked and received, and used for collecting image data in the room under the manual operation of a user to obtain a panoramic collected image;
the edge-preserving filtering equipment is connected with the fisheye collecting mechanism and used for performing edge-preserving smooth filtering processing on the panoramic collected image based on the maximum noise amplitude in the received panoramic collected image so as to obtain a corresponding edge-preserving filtered image, wherein the larger the maximum noise amplitude is, the larger the amplitude of the edge-preserving smooth filtering processing on the panoramic collected image is;
the spatial domain enhancement processing equipment is connected with the edge-preserving filtering equipment and is used for executing image spatial domain enhancement processing on the received edge-preserving smooth filtering image so as to obtain a spatial domain enhancement processing image;
the affine transformation device is connected with the spatial domain enhancement processing device and used for executing affine transformation on the received spatial domain enhancement processing image to obtain an affine transformation image;
the color analysis equipment is arranged in the handheld measuring instrument, is connected with the affine transformation equipment and is used for identifying the number of pixel points occupied by each paint surface object from the affine transformation image based on the color characteristics of the paint in the preset type;
the depth of field measuring equipment is arranged in the handheld measuring instrument and is used for acquiring each depth of field value corresponding to each paint surface object in the affine transformation image;
and the parameter conversion equipment is respectively connected with the color analysis equipment, the depth of field measurement equipment and the area identification equipment and is used for calculating the paint area of each paint object based on the number of the pixel points occupied by each paint object and the depth of field value corresponding to each paint object.
The missing data detection system may further include:
and the power detection equipment is used for detecting the maximum value of the historical power consumption of the current power utilization system to serve as the reference maximum power consumption output.
In the missing data detection system:
the fish-eye collecting mechanism comprises a plurality of CMOS sensors, a single DSP processor, a single gradient sharpening filter device and a single bilinear interpolation device, wherein the DSP processor is connected with the plurality of CMOS sensors and is used for splicing the sensing contents of the CMOS sensors in an open state to obtain and output an instant panoramic image.
In the missing data detection system:
the DSP is also connected with the power detection equipment and is used for receiving the reference maximum power consumption and determining the sensor opening number corresponding to the reference maximum power consumption, so that the CMOS sensors with the number consistent with the sensor opening number are selected from the plurality of CMOS sensors according to the sensor opening number and are controlled to enter an opening state.
In the missing data detection system:
the gradient sharpening filtering equipment is connected with the fisheye collecting mechanism and is used for executing gradient sharpening filtering processing on the received instant panoramic image so as to obtain a corresponding instant filtering image;
the bilinear interpolation device is connected with the gradient sharpening filtering device and is used for executing bilinear interpolation processing on the received instant filtering image so as to obtain a corresponding panoramic collected image.
In the missing data detection system:
receiving the reference maximum power consumption, and determining a number of sensors that are on corresponding to the reference maximum power consumption comprises: the number of sensors on is inversely proportional to the reference maximum power consumption;
wherein the power detection device, the gradient sharpening filtering device, the bilinear interpolation device, the plurality of CMOS sensors, and the DSP processor are all located within the current power utilization system.
Meanwhile, in order to overcome the defects, the invention also builds a missing data detection method, which comprises the following steps: a missing data detection system is used to determine whether paint in the room is missing based on the sum of the individual building areas of the individual walls and the sum of the individual paint areas of the identified individual paint objects.
In addition, a CMOS image sensor is a typical solid-state imaging sensor, and has a common historical source with a CCD. The CMOS image sensor generally comprises an image sensor cell array, a row driver, a column driver, a timing control logic, an AD converter, a data bus output interface, a control interface, etc., which are usually integrated on the same silicon chip. The working process can be generally divided into a reset part, a photoelectric conversion part, an integration part and a reading part.
Other digital signal processing circuits such as an AD converter, automatic exposure control, non-uniform compensation, white balance processing, black level control, gamma correction, etc. may be integrated on the CMOS image sensor chip, and even a DSP device having a programmable function may be integrated with the CMOS device for fast calculation, thereby forming a single-chip digital camera and an image processing system.
Morrison published a calculable sensor in 1963, which is a structure that can determine the position of a light spot by using a light guide effect, and became the beginning of the development of a CMOS image sensor. Low noise CMOS active pixel sensor monolithic digital cameras were successful in 1995.
CMOS image sensors have several advantages: 1) random window reading capability. Random window read operation is one aspect of CMOS image sensors that is functionally superior to CCDs, also referred to as region of interest selection. In addition, the high integration characteristics of the CMOS image sensor make it easy to implement a function of opening a plurality of tracking windows simultaneously. 2) And radiation resistance. In general, the potential radiation resistance of CMOS image sensors is significantly enhanced relative to CCD performance. 3) System complexity and reliability. The use of CMOS image sensors can greatly simplify the system hardware architecture. 4) And a non-destructive data reading method. 5) Optimized exposure control. It is noted that CMOS image sensors also have several disadvantages, mainly two indicators of noise and fill factor, due to the integration of multiple functional transistors in the pixel structure. In view of the relatively superior performance of the CMOS image sensor, the CMOS image sensor has been widely used in various fields.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (7)
1. A missing data detection system, comprising:
the data storage device is arranged in the handheld measuring instrument and is used for pre-storing each building area of each wall of the room to be checked and accepted;
the area identification device is connected with the data storage device and used for calculating the sum of all building areas of all walls to serve as a first statistical area, receiving all paint areas of all paint objects and calculating the sum of all paint areas of all paint objects to serve as a second statistical area;
the signal distribution equipment is connected with the area identification equipment and is used for sending out a paint shortage signal when the first statistical area exceeds the second statistical area and reaches a preset value or sending out a paint sufficiency signal if the first statistical area does not exceed the second statistical area;
the fisheye collecting mechanism is arranged at the top end of the handheld measuring instrument, placed in a room to be checked and received, and used for collecting image data in the room under the manual operation of a user to obtain a panoramic collected image;
the edge-preserving filtering equipment is connected with the fisheye collecting mechanism and used for performing edge-preserving smooth filtering processing on the panoramic collected image based on the maximum noise amplitude in the received panoramic collected image so as to obtain a corresponding edge-preserving filtered image, wherein the larger the maximum noise amplitude is, the larger the amplitude of the edge-preserving smooth filtering processing on the panoramic collected image is;
the spatial domain enhancement processing equipment is connected with the edge-preserving filtering equipment and is used for executing image spatial domain enhancement processing on the received edge-preserving smooth filtering image so as to obtain a spatial domain enhancement processing image;
the affine transformation device is connected with the spatial domain enhancement processing device and used for executing affine transformation on the received spatial domain enhancement processing image to obtain an affine transformation image;
the color analysis equipment is arranged in the handheld measuring instrument, is connected with the affine transformation equipment and is used for identifying the number of pixel points occupied by each paint surface object from the affine transformation image based on the color characteristics of the paint in the preset type;
the depth of field measuring equipment is arranged in the handheld measuring instrument and is used for acquiring each depth of field value corresponding to each paint surface object in the affine transformation image;
and the parameter conversion equipment is respectively connected with the color analysis equipment, the depth of field measurement equipment and the area identification equipment and is used for calculating the paint area of each paint object based on the number of the pixel points occupied by each paint object and the depth of field value corresponding to each paint object.
2. The missing data detection system of claim 1 wherein the system further comprises:
and the power detection equipment is used for detecting the maximum value of the historical power consumption of the current power utilization system to serve as the reference maximum power consumption output.
3. The missing data detection system of claim 2 wherein:
the fish-eye collecting mechanism comprises a plurality of CMOS sensors, a single DSP processor, a single gradient sharpening filter device and a single bilinear interpolation device, wherein the DSP processor is connected with the plurality of CMOS sensors and is used for splicing the sensing contents of the CMOS sensors in an open state to obtain and output an instant panoramic image.
4. The missing data detection system of claim 3 wherein:
the DSP is also connected with the power detection equipment and is used for receiving the reference maximum power consumption and determining the sensor opening number corresponding to the reference maximum power consumption, so that the CMOS sensors with the number consistent with the sensor opening number are selected from the plurality of CMOS sensors according to the sensor opening number and are controlled to enter an opening state.
5. The missing data detection system of claim 4 wherein:
the gradient sharpening filtering equipment is connected with the fisheye collecting mechanism and is used for executing gradient sharpening filtering processing on the received instant panoramic image so as to obtain a corresponding instant filtering image;
the bilinear interpolation device is connected with the gradient sharpening filtering device and is used for executing bilinear interpolation processing on the received instant filtering image so as to obtain a corresponding panoramic collected image.
6. The missing data detection system of claim 5 wherein:
receiving the reference maximum power consumption, and determining a number of sensors that are on corresponding to the reference maximum power consumption comprises: the number of sensors on is inversely proportional to the reference maximum power consumption;
wherein the power detection device, the gradient sharpening filtering device, the bilinear interpolation device, the plurality of CMOS sensors, and the DSP processor are all located within the current power utilization system.
7. A method for missing data detection, the method comprising: use of the missing data detection system of any of claims 1-6 to determine whether a missing phenomenon occurs in paint in a room based on the sum of the individual building areas of the individual walls and the sum of the individual paint areas of the individual paint objects identified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911069991.8A CN110895825B (en) | 2019-11-05 | 2019-11-05 | Missing data detection system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911069991.8A CN110895825B (en) | 2019-11-05 | 2019-11-05 | Missing data detection system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110895825A CN110895825A (en) | 2020-03-20 |
| CN110895825B true CN110895825B (en) | 2021-09-17 |
Family
ID=69786618
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911069991.8A Active CN110895825B (en) | 2019-11-05 | 2019-11-05 | Missing data detection system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110895825B (en) |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7044004B2 (en) * | 2003-03-24 | 2006-05-16 | Siemens Power Generation, Inc. | Apparatus and method for applying optical stripes for torsional detection |
| US9582899B2 (en) * | 2014-03-12 | 2017-02-28 | The Sherwin-Williams Company | Real-time digitally enhanced imaging for the prediction, application, and inspection of coatings |
| US9857888B2 (en) * | 2015-03-17 | 2018-01-02 | Behr Process Corporation | Paint your place application for optimizing digital painting of an image |
| CN107083128A (en) * | 2016-02-15 | 2017-08-22 | 河北嘉宝莉涂料有限公司 | A kind of environment-friendly interior wall coating of novel high-performance vinegar third and preparation method thereof |
| CN105739316A (en) * | 2016-02-26 | 2016-07-06 | 河南智业科技发展有限公司 | Intelligent household control method and device |
| CN107492125A (en) * | 2017-07-28 | 2017-12-19 | 哈尔滨工业大学深圳研究生院 | The processing method of automobile fish eye lens panoramic view picture |
| CN107563802A (en) * | 2017-08-24 | 2018-01-09 | 温州大学瓯江学院 | A kind of room finish budgeting system |
| CN107657611B (en) * | 2017-10-18 | 2020-04-28 | 京东方科技集团股份有限公司 | Poor gluing detection equipment, poor gluing detection method and calculation equipment |
| CN109840806A (en) * | 2019-01-30 | 2019-06-04 | 青梧桐有限责任公司 | It takes in a maidservant or a slave girl as a concubine measuring method and system |
-
2019
- 2019-11-05 CN CN201911069991.8A patent/CN110895825B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110895825A (en) | 2020-03-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6620477B2 (en) | Method and program for detecting cracks in concrete | |
| CN103416052B (en) | The method of the generation focus signal of auto focus control system | |
| US7280141B1 (en) | Fixed pattern noise subtraction in a digital image sensor | |
| CN101523897A (en) | Electronic image capture with reduced noise | |
| CN101305398A (en) | Method for forming synthesis image based on a plurality of image frames | |
| CN110895825B (en) | Missing data detection system and method | |
| JP2016540440A (en) | Picture processing method and apparatus | |
| WO2019112040A1 (en) | Inspection system, inspection method, program, and storage medium | |
| CN101132477B (en) | Digital image processing method and device thereof | |
| CN111951193A (en) | Method and apparatus for correcting horizontal distortion of image | |
| CN114078153B (en) | Light field coding camera shooting method and device for scattering scene | |
| CN103364404B (en) | Camera detection method and camera | |
| CN106950174B (en) | Thermal insulation material bond area based on image processing techniques is than disbonded test method | |
| CN107454388B (en) | Image processing method and apparatus using the same | |
| JP4921058B2 (en) | Imaging apparatus and control method thereof | |
| CN108898080B (en) | Ridge line neighborhood evaluation model-based crack connection method | |
| CN107333068A (en) | A kind of photographic method, device, equipment and medium | |
| JP4579570B2 (en) | Shading method | |
| JP2001242095A (en) | Corrosion detecting determining method for member having curved face | |
| CN104639842A (en) | Image processing device and exposure control method | |
| CN114998256A (en) | Method, device and equipment for detecting attachment granularity of material and storage medium | |
| CN112749448B (en) | Space measurement system and method based on parameter big data identification | |
| Lee et al. | Contaminated facade identification using convolutional neural network and image processing | |
| JP2945423B2 (en) | Color image signal evaluation method | |
| CN113129303B (en) | Automatic marking method and device for inspection pictures, storage medium and electronic 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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210524 Address after: 323000 Tianning Temple, Liandu District, Lishui, Zhejiang Applicant after: LISHUI XINYU MACHINERY MANUFACTURING Co.,Ltd. Address before: 225000 Room 101, building 6, baojunyuan, 99 Jiefang North Road, Guangling District, Yangzhou City, Jiangsu Province Applicant before: Fang Chunjiang |
|
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210902 Address after: 250000 room 2701, block a, east ring International Plaza, East 2nd Ring Road, Jinan, Shandong Applicant after: SHANDONG XINCHAO INFORMATION TECHNOLOGY Co.,Ltd. Address before: 323000 Tianning Temple, Liandu District, Lishui, Zhejiang Applicant before: LISHUI XINYU MACHINERY MANUFACTURING Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Missing data detection system and method Effective date of registration: 20211229 Granted publication date: 20210917 Pledgee: Branches of Jinan Rural Commercial Bank Co.,Ltd. Pledgor: SHANDONG XINCHAO INFORMATION TECHNOLOGY CO.,LTD. Registration number: Y2021980016723 |
|
| PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
| PC01 | Cancellation of the registration of the contract for pledge of patent right |
Date of cancellation: 20230104 Granted publication date: 20210917 Pledgee: Branches of Jinan Rural Commercial Bank Co.,Ltd. Pledgor: SHANDONG XINCHAO INFORMATION TECHNOLOGY CO.,LTD. Registration number: Y2021980016723 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Missing data detection system and method Effective date of registration: 20230214 Granted publication date: 20210917 Pledgee: Branches of Jinan Rural Commercial Bank Co.,Ltd. Pledgor: SHANDONG XINCHAO INFORMATION TECHNOLOGY CO.,LTD. Registration number: Y2023980032615 |