CN108376395A - Dynamic graph display platform based on image recognition - Google Patents
Dynamic graph display platform based on image recognition Download PDFInfo
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- CN108376395A CN108376395A CN201711221587.9A CN201711221587A CN108376395A CN 108376395 A CN108376395 A CN 108376395A CN 201711221587 A CN201711221587 A CN 201711221587A CN 108376395 A CN108376395 A CN 108376395A
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- 210000003454 tympanic membrane Anatomy 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims abstract description 14
- 238000012545 processing Methods 0.000 claims description 38
- 230000002708 enhancing effect Effects 0.000 claims description 28
- 230000006872 improvement Effects 0.000 claims description 16
- 230000003287 optical effect Effects 0.000 claims description 7
- 238000004891 communication Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 5
- 238000003384 imaging method Methods 0.000 claims 1
- 238000012360 testing method Methods 0.000 description 5
- 241000256844 Apis mellifera Species 0.000 description 4
- 230000007774 longterm Effects 0.000 description 4
- 230000007246 mechanism Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000000034 method Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000002093 peripheral effect Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 206010016717 Fistula Diseases 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 210000003027 ear inner Anatomy 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
- 210000002388 eustachian tube Anatomy 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000003890 fistula Effects 0.000 description 1
- 210000001165 lymph node Anatomy 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000002578 otoscopy Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000008961 swelling Effects 0.000 description 1
- 230000001720 vestibular Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/55—Depth or shape recovery from multiple images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20192—Edge enhancement; Edge preservation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
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- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of Dynamic Graph display platform based on image recognition, including：Scene shows equipment, is connect with object extraction equipment, and the ear-drum Dynamic Graph of object extraction equipment output is shown for receiving simultaneously scene；Picture pick-up device in ear is arranged inside patient's ear, for carrying out image taking to patient's ear inside scene, to obtain and export internal scene image；Quality estimation equipment, it is connect with picture pick-up device in the ear, for receiving internal scene image, the noise in the internal scene image is analyzed to obtain the amplitude of various noises, the credit rating of the internal scene image is determined based on the amplitude of various noises.By means of the invention it is possible to which medical staff is helped to understand patient's Er Nei state of an illness rapidly.
Description
Technical field
The present invention relates to field of image recognition more particularly to a kind of Dynamic Graph display platforms based on image recognition.
Background technology
Currently, for the detection generally use ear check method of environment in the ear of patient, this method include mainly otoscopy,
Eustachian tube function inspection, listening comprehension test, vestibular function examination, fistula test and other inspections.The size of general first observation auricle,
Position, whether there is or not whether deformity and both sides symmetrical, auricle and mastoidea and ear peripheral lymph node whether there is or not swelling, touch pain and tenderness.
Tool used in above-mentioned detection is optical tooling, and the mode of judgement is that doctor sentences by the artificial of personal experience
Disconnected, this testing mechanism is easy to cause testing result excessively static.Long-term follow can not be carried out to the environment of patient Er Nei, moved
State describes and analysis.
Invention content
To solve the above-mentioned problems, the present invention provides a kind of Dynamic Graph display platform based on image recognition, uses
Object extraction equipment receives image in multiple ears successively for chronologically-based, is all carried out to multiple images based on default ear
The matching operation of film benchmark image, to be obtained respectively from the multiple targets improvement image and be partitioned into multiple ear-drum subgraphs
Picture, and based on the ear-drum Dynamic Graph based on time change at multiple ear-drum subgraph draftings.
According to an aspect of the present invention, a kind of Dynamic Graph display platform based on image recognition, the platform packet are provided
It includes：
Scene shows equipment, is connect with object extraction equipment, and the output of object extraction equipment is shown for receiving simultaneously scene
Ear-drum Dynamic Graph；
Picture pick-up device in ear is arranged inside patient's ear, for carrying out image taking to patient's ear inside scene, with
It obtains and exports internal scene image；
Quality estimation equipment is connect with picture pick-up device in the ear, for receiving internal scene image, to the fields inside
Noise in scape image is analyzed to obtain the amplitude of various noises, and the internal scene is determined based on the amplitude of various noises
The credit rating of image；
Tactful switching equipment is connect with the quality estimation equipment, default for being less than or equal in the credit rating
When lower limit credit rating, selected depth processing equipment carries out corresponding image enhancement processing to obtain to the internal scene image
Enhancing processing image is additionally operable to, when the credit rating is higher than pre-determined lower limit credit rating, select primary processing equipment to institute
It states internal scene image and carries out corresponding image enhancement processing to obtain enhancing processing image；
Advanced treatment device is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving
Internal scene image is stated, based on the credit rating apart from the far and near by the internal scene graph of the pre-determined lower limit credit rating
Each piecemeal as being averagely divided into relevant block size, to each piecemeal, the pixel value variance selection based on the piecemeal corresponds to
Varying strength contrast enhancement processing to obtain enhancing piecemeal, each enhancing piecemeal of acquisition is combined to obtain in first
Between image, distance based on the credit rating apart from the pre-determined lower limit credit rating is by the first intermediate image average mark
It is cut into each piecemeal of corresponding block size, to each piecemeal, the pixel value variance selection based on the piecemeal is corresponding different strong
The edge enhancing processing of degree is combined each enhancing piecemeal of acquisition to obtain targets improvement image with obtaining enhancing piecemeal；
Primary processing equipment is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving
Internal scene image is stated, and to the internal scene image overall execution contrast enhancement processing to obtain the second intermediate image,
It is handled to the second intermediate image overall execution edge enhancing to obtain targets improvement image；
Object extraction equipment is connect with the advanced treatment device and the primary processing equipment respectively, when for being based on
Between sequence receive multiple targets improvement images successively, multiple targets improvement images are all carried out based on default ear-drum benchmark image
Matching operation, to obtain and be partitioned into multiple ear-drum subgraphs respectively from the multiple targets improvement image, and based on multiple
Ear-drum Dynamic Graph based on time change at ear-drum subgraph drafting.
The present invention at least has inventive point important at following two：
(1) total quality of input picture is assessed using quality estimation equipment, is selected when second-rate high-strength
The image-enhancing equipment of degree is to improve image enhancement quality, when quality is good, the enhancing of common disposed of in its entirety is selected to handle
Equipment is to reduce unnecessary equipment power dissipation, to realize targetedly image enhancement processing；
(2) the ear-drum Dynamic Graph based on time change that simultaneously scene shows patient is obtained, facilitates medical staff more fully
Understand the state of an illness in the ear of patient.
Description of the drawings
Embodiment of the present invention is described below with reference to attached drawing, wherein：
Fig. 1 is to be carried according to the object of Dynamic Graph display platform of the realization shown in embodiment of the present invention based on image recognition
The peripheral interface figure of the processor of taking equipment.
Fig. 2 is the structure box according to the Dynamic Graph display platform based on image recognition shown in embodiment of the present invention
Figure.
Specific implementation mode
The embodiment of the Dynamic Graph display platform based on image recognition of the present invention is carried out below with reference to accompanying drawings detailed
It describes in detail bright.
Testing mechanism lacks long-term, dynamic detection means in current ear.In order to overcome above-mentioned deficiency, the present invention to take
A kind of Dynamic Graph display platform based on image recognition is built, specific embodiment is as follows.
Fig. 1 is to be carried according to the object of Dynamic Graph display platform of the realization shown in embodiment of the present invention based on image recognition
The peripheral interface figure of the processor of taking equipment.
Fig. 2 is the structure box according to the Dynamic Graph display platform based on image recognition shown in embodiment of the present invention
Figure, the platform include：
Scene shows equipment, is connect with object extraction equipment, and the output of object extraction equipment is shown for receiving simultaneously scene
Ear-drum Dynamic Graph；
Picture pick-up device in ear is arranged inside patient's ear, for carrying out image taking to patient's ear inside scene, with
It obtains and exports internal scene image；
Quality estimation equipment is connect with picture pick-up device in the ear, for receiving internal scene image, to the fields inside
Noise in scape image is analyzed to obtain the amplitude of various noises, and the internal scene is determined based on the amplitude of various noises
The credit rating of image；
Tactful switching equipment is connect with the quality estimation equipment, default for being less than or equal in the credit rating
When lower limit credit rating, selected depth processing equipment carries out corresponding image enhancement processing to obtain to the internal scene image
Enhancing processing image is additionally operable to, when the credit rating is higher than pre-determined lower limit credit rating, select primary processing equipment to institute
It states internal scene image and carries out corresponding image enhancement processing to obtain enhancing processing image；
Advanced treatment device is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving
Internal scene image is stated, based on the credit rating apart from the far and near by the internal scene graph of the pre-determined lower limit credit rating
Each piecemeal as being averagely divided into relevant block size, to each piecemeal, the pixel value variance selection based on the piecemeal corresponds to
Varying strength contrast enhancement processing to obtain enhancing piecemeal, each enhancing piecemeal of acquisition is combined to obtain in first
Between image, distance based on the credit rating apart from the pre-determined lower limit credit rating is by the first intermediate image average mark
It is cut into each piecemeal of corresponding block size, to each piecemeal, the pixel value variance selection based on the piecemeal is corresponding different strong
The edge enhancing processing of degree is combined each enhancing piecemeal of acquisition to obtain targets improvement image with obtaining enhancing piecemeal；
Primary processing equipment is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving
Internal scene image is stated, and to the internal scene image overall execution contrast enhancement processing to obtain the second intermediate image,
It is handled to the second intermediate image overall execution edge enhancing to obtain targets improvement image；
Object extraction equipment is connect with the advanced treatment device and the primary processing equipment respectively, when for being based on
Between sequence receive multiple targets improvement images successively, multiple targets improvement images are all carried out based on default ear-drum benchmark image
Matching operation, to obtain and be partitioned into multiple ear-drum subgraphs respectively from the multiple targets improvement image, and based on multiple
Ear-drum Dynamic Graph based on time change at ear-drum subgraph drafting；
Wherein, further include inside picture pick-up device in the ear optical filter, optics convex lens combination, image sensing cell with
And camera support equipment, the optical filter are blue filter, are arranged on the front of the optics convex lens combination, the light
The front that convex lens combination is arranged on described image sensing unit is learned, the camera support equipment is for simultaneously to the optical filtering
Piece, optics convex lens combination and described image sensing unit provide instant support force.
Then, continue to carry out the concrete structure of the Dynamic Graph display platform based on image recognition of the present invention further
Explanation.
In the Dynamic Graph display platform based on image recognition：
In the advanced treatment device, the credit rating is closer apart from the pre-determined lower limit credit rating, will be described
The relevant block that internal scene image averaging is divided into is bigger.
In the Dynamic Graph display platform based on image recognition：
In the advanced treatment device, to each piecemeal, the pixel value variance of the piecemeal is bigger, the contrast of selection
The dynamics for enhancing processing is smaller, meanwhile, the dynamics of the edge enhancing processing of selection is smaller.
In the Dynamic Graph display platform based on image recognition：
In the advanced treatment device, the credit rating is closer apart from the pre-determined lower limit credit rating, will be described
The relevant block that first intermediate image is averagely divided into is bigger.
Can also include in the Dynamic Graph display platform based on image recognition：
Holder is imaged, picture pick-up device in the ear is used to support, picture pick-up device is located at the camera shooting holder in the ear
Top；
Wherein, the top of the camera shooting holder is located inside patient's ear.
In the Dynamic Graph display platform based on image recognition：
The scene shows that equipment is LED display or LCD display；
Wherein, the scene shows that equipment carries out two-way with the object extraction equipment by ZIGBEE communication links
Letter；
Wherein, the scene shows that equipment is embedded in the wall in ward.
In addition, ZigBee is the low-power consumption LAN protocol based on IEEE802.15.4 standards.It is provided according to international standard,
ZigBee technology is the wireless communication technique of a kind of short distance, low-power consumption.This title (also known as ZigBee protocol) derives from honeybee
Eight words dance, due to honeybee (bee) be by circle in the air and " drone " (zig) shake wing " dancing " come and companion transmission pollen
Place azimuth information, that is to say, that honeybee constitutes the communication network in group by such mode.Its main feature is that closely,
Low complex degree, self-organizing, low-power consumption, low data rate.It is mainly suitable for, for automatically controlling and remote control field, to be embedded in
Various equipment.In brief, ZigBee is exactly a kind of cheap, the near radio networking mechanics of communication of low-power consumption.ZigBee
It is a kind of wireless network protocol of low speed short-distance transmission.Zigbee protocol is respectively physical layer (PHY), media visit from top to bottom
Ask control layer (MAC), transport layer (TL), network layer (NWK), application layer (APL) etc..Wherein physical layer and MAC layer
Follow the regulation of IEEE 802.15.4 standards.
Dynamic Graph display platform using the present invention based on image recognition, for shortage dynamic ear inner ring in the prior art
It is the technical issues of border analysis mechanisms, right by using multiple targetedly customization image recognition apparatus and image capture devices
Patient's Er Nei environment carries out target identification and long-term follow, and based on above-mentioned target identification result and long-term follow as a result,
Environment analysis mechanisms in dynamic ear are established, the evolution so as to understand patient's state of an illness for medical staff provides important reference
Data.
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, every content without departing from technical solution of the present invention is 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 (6)
1. a kind of Dynamic Graph display platform based on image recognition, the platform include：
Scene shows equipment, is connect with object extraction equipment, and the ear-drum of object extraction equipment output is shown for receiving simultaneously scene
Dynamic Graph；
Picture pick-up device in ear is arranged inside patient's ear, for carrying out image taking to patient's ear inside scene, to obtain
And export internal scene image；
Quality estimation equipment is connect with picture pick-up device in the ear, for receiving internal scene image, to the internal scene graph
Noise as in is analyzed to obtain the amplitude of various noises, and the internal scene image is determined based on the amplitude of various noises
Credit rating；
Tactful switching equipment is connect with the quality estimation equipment, for being less than or equal to pre-determined lower limit in the credit rating
When credit rating, selected depth processing equipment carries out corresponding image enhancement processing to be enhanced to the internal scene image
Image is handled, is additionally operable to, when the credit rating is higher than pre-determined lower limit credit rating, select primary processing equipment to described interior
Portion's scene image carries out corresponding image enhancement processing to obtain enhancing processing image；
Advanced treatment device is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving in described
Portion's scene image is put down the internal scene image apart from the far and near of the pre-determined lower limit credit rating based on the credit rating
It is divided into each piecemeal of corresponding block size, to each piecemeal, the pixel value variance selection based on the piecemeal is corresponding not
With the contrast enhancement processing of intensity to obtain enhancing piecemeal, each enhancing piecemeal of acquisition is combined to obtain the first middle graph
First intermediate image is averagely divided by picture, the distance based on the credit rating apart from the pre-determined lower limit credit rating
Each piecemeal of corresponding block size, to each piecemeal, the pixel value variance based on the piecemeal selects corresponding varying strength
Edge enhancing processing is combined each enhancing piecemeal of acquisition to obtain targets improvement image with obtaining enhancing piecemeal；
Primary processing equipment is connect respectively with the quality estimation equipment and the tactful switching equipment, for receiving in described
Portion's scene image, and to the internal scene image overall execution contrast enhancement processing to obtain the second intermediate image, right
The second intermediate image overall execution edge enhancing processing is to obtain targets improvement image；
Object extraction equipment is connect with the advanced treatment device and the primary processing equipment respectively, for suitable based on the time
Sequence receives multiple targets improvement images successively, and the matching based on default ear-drum benchmark image is all carried out to multiple targets improvement images
Operation to obtain and be partitioned into multiple ear-drum subgraphs respectively from the multiple targets improvement image, and is based on multiple ear-drums
Ear-drum Dynamic Graph based on time change at subgraph drafting；
Wherein, further include optical filter inside picture pick-up device in the ear, optics convex lens combination, image sensing cell and take the photograph
As support equipment；
Wherein, the optical filter is blue filter, is arranged on the front of the optics convex lens combination, the optics convex lens
Microscope group closes the front for being arranged on described image sensing unit；
Wherein, the camera support equipment is for simultaneously passing the optical filter, optics convex lens combination and described image
Feel unit and instant support force is provided.
2. the Dynamic Graph display platform based on image recognition as described in claim 1, it is characterised in that：
In the advanced treatment device, the credit rating is closer apart from the pre-determined lower limit credit rating, by the inside
The relevant block that scene image is averagely divided into is bigger.
3. the Dynamic Graph display platform based on image recognition as claimed in claim 2, it is characterised in that：
In the advanced treatment device, to each piecemeal, the pixel value variance of the piecemeal is bigger, the contrast enhancing of selection
The dynamics of processing is smaller, meanwhile, the dynamics of the edge enhancing processing of selection is smaller.
4. the Dynamic Graph display platform based on image recognition as claimed in claim 3, it is characterised in that：
In the advanced treatment device, the credit rating is closer apart from the pre-determined lower limit credit rating, by described first
The relevant block that intermediate image is averagely divided into is bigger.
5. the Dynamic Graph display platform based on image recognition as claimed in claim 4, which is characterized in that further include：
Holder is imaged, picture pick-up device in the ear is used to support, picture pick-up device is located at the top for imaging holder in the ear；
Wherein, the top of the camera shooting holder is located inside patient's ear.
6. the Dynamic Graph display platform based on image recognition as claimed in claim 5, it is characterised in that：
The scene shows that equipment is LED display or LCD display；
Wherein, the scene shows that equipment carries out two-way communication with the object extraction equipment by ZIGBEE communication links；
Wherein, the scene shows that equipment is embedded in the wall in ward.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201711221587.9A CN108376395B (en) | 2017-11-23 | 2017-11-23 | Dynamic Graph display platform based on image recognition |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711221587.9A CN108376395B (en) | 2017-11-23 | 2017-11-23 | Dynamic Graph display platform based on image recognition |
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| CN108376395A true CN108376395A (en) | 2018-08-07 |
| CN108376395B CN108376395B (en) | 2019-01-18 |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109544521A (en) * | 2018-11-12 | 2019-03-29 | 北京航空航天大学 | The method for registering of passive millimeter wave image and visible images in a kind of human body safety check |
| CN109729320A (en) * | 2019-01-24 | 2019-05-07 | 孔清明 | Real-time objects identify monitoring platform |
| CN110636465A (en) * | 2019-04-03 | 2019-12-31 | 靳爱丛 | Local area network information sending platform |
| CN112580554A (en) * | 2020-12-25 | 2021-03-30 | 北京环境特性研究所 | CNN-based MSTAR data noise intensity control classification identification method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109544521A (en) * | 2018-11-12 | 2019-03-29 | 北京航空航天大学 | The method for registering of passive millimeter wave image and visible images in a kind of human body safety check |
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| CN112580554B (en) * | 2020-12-25 | 2024-01-05 | 北京环境特性研究所 | Classification recognition method for MSTAR data noise intensity control based on CNN |
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| CN108376395B (en) | 2019-01-18 |
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