CN107644425B - Target image choosing method, device, computer equipment and storage medium - Google Patents
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Abstract
A kind of target image choosing method, device, computer equipment and storage medium, the method for one embodiment include：Obtain each image of acquisition；Each described image of acquisition is analyzed respectively, is analyzed from each image of acquisition and determines the most intermediate objective image of the target for including；The image of the front and back predetermined number adjacent with the intermediate objective image is chosen, and calculates the clarity of each image of selection；The final goal image that the corresponding image of maximum clarity is determined as choosing.The embodiment of the present invention improves the efficiency and accuracy rate for choosing target image.
Description
Technical field
The present invention relates to field of computer technology, more particularly to a kind of target image choosing method, a kind of target image
Selecting device, a kind of computer equipment and storage medium.
Background technology
With the development of computer technology, increasingly hot topic is detected to target using computer image processing technology,
Target detection is also Objective extraction, is a kind of image segmentation based on target geometry and statistical nature.And with digital in recent years
The development of image processing techniques, the Techniques of Automatic Focusing based on image procossing obtains long-range development, therefore is carrying out target inspection
When survey, image where target is usually selected by Techniques of Automatic Focusing, and for the image chosen carry out target detection or
Objective extraction.However, in modern medicine field of image detection, real image is various and complicated, and usual mode needs to expend
Image where target can just be found for a long time, and accuracy rate is low.
Invention content
Based on this, a kind of target image choosing method of offer of the embodiment of the present invention, a kind of target image selecting device, one kind
Computer equipment and storage medium, to improve the efficiency and accuracy rate of choosing target image.
A kind of target image choosing method, including step：
Obtain each image of acquisition；
Each described image of acquisition is analyzed respectively, is analyzed from each image of acquisition and determines the target for including most
More intermediate objective images；
Choose the front and back predetermined number adjacent with the intermediate objective image image, and calculate selection each image it is clear
Clear degree；
The final goal image that the corresponding image of maximum clarity is determined as choosing.
A kind of target image selecting device, including：
Image analysis module, each image for obtaining acquisition；And each described image is analyzed respectively, from each described
The most intermediate objective image of the target for including is determined in analysis in image；
Sharpness computation module, the image for choosing the front and back predetermined number adjacent with the intermediate objective image, and
Calculate the clarity for each image chosen；
Module is chosen, for the corresponding image of maximum clarity to be chosen for final goal image.
A kind of computer equipment, including memory, processor and be stored on the memory and can be in the processing
The computer program run on device, the processor realize method as described above when executing the computer program.
A kind of computer storage media, is stored thereon with computer program, is realized when which is executed by processor as above
The method.
Based on the scheme in embodiment as described above, first each image of acquisition is analyzed, therefrom analysis determines
Go out the most intermediate objective image of the target for including, then chooses the figure of the front and back predetermined number adjacent with the intermediate objective image
Then picture chooses the corresponding image of maximum clarity so as to fast and efficiently find the section where target image
As final goal image, so that finally determining target image clarity highest, while improving selection target image
Efficiency and accuracy rate.
Description of the drawings
Fig. 1 is the flow diagram of the target image choosing method in one embodiment；
Fig. 2 is the schematic diagram behind label target region in one image in a concrete application example；
Fig. 3 is the structural schematic diagram of the target image selecting device in one embodiment.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention more comprehensible, with reference to the accompanying drawings and embodiments, to this
Invention is described in further detail.It should be appreciated that the present invention can realize in many different forms, however it is not limited to this
Literary described embodiment.Make understanding to the disclosure more on the contrary, purpose of providing these embodiments is
Thorough and comprehensive.
Unless otherwise defined, all of technologies and scientific terms used here by the article and belong to the technical field of the present invention
The normally understood meaning of technical staff is identical.Used term is intended merely to description tool in the description of the invention herein
The purpose of the embodiment of body, it is not intended that in the limitation present invention.Term as used herein " and/or " include one or more phases
Any and all combinations of the Listed Items of pass.
The target image choosing method of the embodiment of the present invention can be applied to various needs and choose one from multiple images
The various microscopy automations such as the technology application scenarios of target image, such as urine sediments analyzer, copra analysis instrument, gynaecology's analyzer
Instrument selection one of acquires image as target image to carry out various automated analysis etc..
The flow diagram of the target image choosing method of one embodiment is shown in Fig. 1, as shown in Figure 1, the implementation
The method of example includes step S101 to step S104.
Step S101：Obtain each image of acquisition.
It is appreciated that each image here is each image for waiting for therefrom selecting in the image set of target image.The image
Each image concentrated can refer to each image determined under sample catalogue, which is typically to give tacit consent to when acquiring each image
The store path for storing the image of acquisition can also be the separately specified path different from the store path of the acquiescence, as long as
It can determine targeted each image.
In one example, can be each image that acquisition is obtained from sample catalogue, each image here can be phase
Image capture device (such as CCD of urine sediments analyzer, copra analysis instrument, gynaecology's analyzer microscopy self-reacting device of pass
(Charge Coupled Device, charge coupled cell) camera etc.) collected each image, typically image capture device
The image of acquisition is acquired as unit of frame, these images constitute image sequence, and each image in image sequence there can be base
In acquisition order determine picture numbers, the picture numbers can as the image identification of the image, in some embodiments,
Can be using the acquisition time of image as the picture numbers of the image, as long as the priority that can distinguish the acquisition of each image is suitable
Sequence can make up image sequence.
Step S102：Each described image of acquisition is analyzed respectively, is analyzed from each image of acquisition and determines to wrap
The most intermediate objective image of the target that contains.
In one embodiment, each described image of acquisition is analyzed respectively, is analyzed from each image of acquisition true
When making the most intermediate objective image of the target for including, following manner progress may be used：
The foreground area of each image of acquisition is extracted respectively；
Calculate separately the area of the foreground area of each image of acquisition, and by the corresponding figure of the area of maximum foreground area
Picture is determined as the most intermediate objective image of the target for including.
In the foreground area of each image for extracting acquisition respectively, specific step may include：For the figure of each acquisition
The gray value of each pixel of the image is compared by picture with presetted pixel threshold value；And according to the gray value of each pixel with
The comparison result of presetted pixel threshold value is split the image, obtains the foreground area of the image of extraction.
Wherein, which is determined by following manner：
The gray value of each pixel of image is compared with pixel threshold undetermined, determines that the image waits for fixation based on this
The foreground pixel point and background pixel point of plain threshold value；
According to each foreground pixel point and each background pixel point, side between foreground class pixel and the class of background classes pixel is calculated
Difference；
The corresponding pixel threshold undetermined of maximum inter-class variance is determined as the presetted pixel threshold value.
In yet another embodiment, can also include step before extracting the foreground area of each image of acquisition respectively：
Each image of acquisition is smoothed respectively.Any possible side may be used in the mode being specifically smoothed
Formula carries out.
After the most intermediate objective image of the target for including is determined in analysis in above-mentioned each image from acquisition, may be used also
To further determine that the target area of the intermediate objective image, and rectangle mark, acquisition pair are carried out to determining target area
Intermediate objective image after the rectangle mark of target area.So as to intuitively be verified accordingly to accuracy.
Step S103：The image of the front and back predetermined number adjacent with the intermediate objective image is chosen, and calculates selection
The clarity of each image.
It is appreciated that here adjacent usually related with putting in order for each image, and putting in order for image can be
Corresponding with acquisition order, such put in order can be determined based on picture numbers as described above etc..The predetermined number
It can be set in conjunction with actual needs, in a specific example, which can be set as 20, so as to choose
Each 20 width of the intermediate objective image or so amounts to 41 width images as the image chosen.
When calculating the clarity for each image chosen, any possible mode may be used and calculated.Have at one
Can be the clear of the target area for each image for calculating selection when calculating the clarity for each image chosen in body example
Degree, and using the clarity of the target area of each image as the clarity of the image.
Step S104：The final goal image that the corresponding image of maximum clarity is determined as choosing.
Based on the scheme in embodiment as described above, first each image of acquisition is analyzed, therefrom analysis determines
Go out the most intermediate objective image of the target for including, then chooses the figure of the front and back predetermined number adjacent with the intermediate objective image
Then picture chooses the corresponding image of maximum clarity so as to fast and efficiently find the section where target image
As final goal image, so that finally determining target image clarity highest, while improving selection target image
Efficiency and accuracy rate.
Based on the target image choosing method in embodiment as described above, carried out below in conjunction with one of specific example
It is described in detail.
It collects and waits in the CCD by microscopies self-reacting devices such as urine sediments analyzer, copra analysis instrument, gynaecology's analyzers
After each image for detecting sample, collected each image is stored under corresponding sample catalogue, can be with frame when acquisition
Unit, which is acquired, obtains each image.The sample catalogue can only uniquely correspond to the catalogue of the sample to be detected, can also be
Corresponding multiple detection samples, in the case, the variant corresponding image of detection sample can be named by different images
Each subdirectory either is set to distinguish.
Then a target image can be chosen from the corresponding all images of the sample to be detected, with to the target image
Analysis is carried out to obtain the testing result for the sample to be detected.The present embodiments relate to be from the sample to be detected
The process of a target image is chosen in corresponding all images.
When choosing target image, first obtain under corresponding sample catalogue, the corresponding all images of the sample to be detected, it can
To understand, the corresponding all images of the sample to be monitored have the graphical arrangement determined based on acquisition order sequentially, to form
Image sequence, each image can have the picture numbers in the image sequence, the picture numbers that can be with acquisition time, adopt
Any possible modes such as collection number, acquisition order embody.
Then each image can be analyzed, the most intermediate objective image of the target for including is determined in therefrom analysis.
In the specific example, by the maximum image of foreground image areas area, as being the most image of target.Therefore, specific
When the target for including most intermediate objective image is determined in analysis, following manner progress can be used.
Each image is smoothed first, specific smoothing processing mode may be used any possible mode into
Row, to reduce the feature of the noise and extraction object of image.Then image segmentation is carried out to the image after smoothing processing, by right
Image after smoothing processing carries out image segmentation, divides the image into foreground area and background area two parts.
When segmentation, a pixel threshold k undetermined can be first set, and the gray value of each pixel of image is waited for into fixation with this
Plain threshold value is compared, and pixel is given two class of foreground pixel C0 and background pixel C1 according to comparison result.Wherein, foreground picture
Pixel-level residing for this kind of pixel of plain C0 is 0~k-1, and the Pixel-level residing for this kind of pixel of background pixel C1 is k~L-
1。
Based on each foreground pixel and background pixel of determining image, the overall average gray scale for determining the image can be calculated
GradeAnd calculate the total area ratio shared by all foreground pixel C0All background pixel C1 institutes
The total area ratio ω accounted for1=1- ω0；And then the average gray level u of all foreground pixel C0 can be calculated0=u0(k)/ω0, institute
The average gray level u of the pixel that has powerful connections C11=u1(k)/ω1.Wherein,
Then, you can calculate the inter-class variance between all foreground pixels and all background pixels：
δ2(k)=ω0(u-u0)2+ω1(u-u1)2。
At this point, the pixel threshold k undetermined separately set changes from 0~L-1, the inter-class variance δ under different k values is calculated2
(k), and by maximum δ2(k) corresponding k values set it to presetted pixel threshold value as most having as optimal value.
Then, be compared with the presetted pixel threshold value with the gray value of each pixel of image, obtain it is final it is each before
Scene element and background pixel, and finally obtained each foreground pixel is extracted, obtain the foreground area of image.And calculate each image
Maximum area is corresponded to image as intermediate objective image by the area of foreground area.
Then, relevant pretreatment is done to the foreground area of the intermediate objective image, pretreatment here includes：Smooth place
Then reason, Threshold segmentation, morphological change etc. further determine that the target area of pretreated intermediate objective image, and right
Determining target area is labeled, such as is indicated with rectangle, and the intermediate objective image after being marked to target area rectangle is obtained,
The schematic diagram after being labelled with target area with rectangle in one image in a specific example is shown in Fig. 2.By to mesh
Mark is labeled, and can intuitively be verified accordingly to accuracy.
Then the image for choosing the front and back predetermined number adjacent with intermediate objective image can in one concrete application example
Be choose image sequence in, the intermediate objective image it is adjacent before and after each 20 width image.
Then, the clarity of each image of selection is calculated.Can pass through calculating it is appreciated that when calculating clarity
The clarity of each target area in image, and by the sum of clarity of each target area of the image as the clear of the image
Degree.Lead to when calculating clarity, following formula may be used and calculate：
In above formula, Gx(x, y), Gy(x, y) is gradient magnitude, and F (I) is exactly the definition values for the image I being calculated.Its
In, the G of gradient magnitudex(x, y), GyThe calculating of (x, y) is eight neighborhood subgraph and the Sobel centered on (x, y) in image I
Gradient operator template carries out convolution acquisition, and Convolution Formula is：
Wherein, I8(x, y) indicates the eight neighborhood subgraph centered on (x, y) in image I, SxAnd SyIt is calculated for Sobel gradients
Son, operator template are respectively：
It is determined as selection after calculating the clarity of each image of selection, and by the corresponding image of maximum clarity
Final goal image.In one application example, the corresponding of the picture numbers of image and the clarity of the image can also be drawn out
The curve of relationship, and the corresponding image in peak of curve place is determined as final goal image.
After selected final goal image, you can analyze the target area in the final goal image, to most
The testing result to sample to be detected is obtained eventually.
It will appreciated by the skilled person that realizing all or part of flow in above-described embodiment method, being can
It is completed with instructing relevant hardware by computer program, the program can be stored in a non-volatile computer can
It reads in storage medium, in the embodiment of the present invention, which can be stored in the storage medium of computer system, and by the meter
At least one of calculation machine system processor executes, and includes the flow such as the embodiment of above-mentioned each method with realization.Wherein, described
Storage medium can be magnetic disc, CD, read-only memory (Read-Only Memory, ROM) or random access memory
(Random Access Memory, RAM) etc..
Accordingly, a kind of storage medium is also provided in one embodiment, is stored thereon with computer program, wherein the journey
It is realized such as any one target image choosing method in the various embodiments described above when sequence is executed by processor.
A kind of target image selecting device is also provided based on thought same as mentioned above, in one embodiment, Fig. 3 shows
The structural schematic diagram of the target image selecting device of one embodiment is gone out.As shown in figure 3, the device in the embodiment includes：
Image analysis module 301, sharpness computation module 302 and selection module 303.
Image analysis module 301, each image for obtaining acquisition；And each described image is analyzed respectively, from each
The most intermediate objective image of the target for including is determined in described image analysis.
It is appreciated that each image here is each image for waiting for therefrom selecting in the image set of target image.The image
Each image concentrated can refer to each image determined under sample catalogue, which is typically to give tacit consent to when acquiring each image
The store path for storing the image of acquisition can also be the separately specified path different from the store path of the acquiescence, as long as
It can determine targeted each image.
In one example, can be each image that acquisition is obtained from sample catalogue, each image here can be phase
Image capture device (such as CCD phases of urine sediments analyzer, copra analysis instrument, gynaecology's analyzer microscopy self-reacting device of pass
Machine etc.) collected each image, typically image capture device acquires the image of acquisition as unit of frame, these images constitute
Image sequence, each image in image sequence can have a picture numbers determined based on acquisition order, which can be with
As the image identification of the image, in some embodiments, it is also possible to be using the acquisition time of image as the image of the image
Serial number, as long as the sequencing of the acquisition of each image can be distinguished, can make up image sequence.
In one embodiment, image analysis module 301 respectively analyzes each described image of acquisition, from acquisition
When the target for including most intermediate objective image is determined in analysis in each image, following manner progress may be used：It carries respectively
Take the foreground area of each image of acquisition；Calculate separately the area of the foreground area of each image of acquisition, and by maximum foreground
The corresponding image of area in region is determined as the most intermediate objective image of the target for including.
In the foreground area of each image for extracting acquisition respectively, following manner progress specifically may be used：For respectively adopting
The gray value of each pixel of the image is compared by the image of collection with presetted pixel threshold value；And according to the ash of each pixel
The comparison result of angle value and presetted pixel threshold value is split the image, obtains the foreground area of the image of extraction.
Wherein, which is determined by following manner：By the gray value of each pixel of image and wait for fixation
Plain threshold value is compared, and determines foreground pixel point and background pixel point of the image based on the pixel threshold undetermined；Before each
Scene vegetarian refreshments and each background pixel point calculate the inter-class variance of foreground class pixel and background classes pixel；By side between maximum class
The corresponding pixel threshold undetermined of difference is determined as the presetted pixel threshold value.
On the other hand, image analysis module 301 can also further determine that the target area of the intermediate objective image, and
Rectangle mark is carried out to determining target area, obtains the intermediate objective image after being marked to target area rectangle.So as to
Intuitively accuracy is verified accordingly.
Sharpness computation module 302, the image for choosing the front and back predetermined number adjacent with the intermediate objective image,
And calculate the clarity of each image of selection.
It is appreciated that here adjacent usually related with putting in order for each image, and putting in order for image can be
Corresponding with acquisition order, such put in order can be determined based on picture numbers as described above etc..The predetermined number
It can be set in conjunction with actual needs, in a specific example, which can be set as 20, so as to choose
Each 20 width of the intermediate objective image or so amounts to 41 width images as the image chosen.
When calculating the clarity for each image chosen, any possible mode may be used and calculated.Have at one
Can be the clear of the target area for each image for calculating selection when calculating the clarity for each image chosen in body example
Degree, and using the clarity of the target area of each image as the clarity of the image.Module 303 is chosen, being used for will be maximum clear
The corresponding image of clear degree is chosen for final goal image.
It will be appreciated by those skilled in the art that device as described above can be arranged on a computing device, by computer equipment
It executes.Accordingly, a kind of computer equipment is also provided in one embodiment, the computer equipment include memory, processor and
Store the computer program that can be run on a memory and on a processor, wherein processor is realized such as when executing described program
Any one target image choosing method in the various embodiments described above.
Each technical characteristic of embodiment described above can be combined arbitrarily, to keep description succinct, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, it is all considered to be the range of this specification record.
Several embodiments of the invention above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the protection of the present invention
Range.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (9)
1. a kind of target image choosing method, which is characterized in that including step：
Obtain each image of acquisition；
Each described image of acquisition is analyzed respectively, the target that analysis is determined to include from each image of acquisition is most
Intermediate objective image；
Choose the front and back predetermined number adjacent with the intermediate objective image image, and calculate selection each image it is clear
Degree；The clarity of described image is the sum of the clarity of each target area of the image；
The final goal image that the corresponding image of maximum clarity is determined as choosing；
Wherein, described that each described image of acquisition is analyzed respectively, from each image of acquisition analysis determine include
The step of target most intermediate objective image includes：
The foreground area of each image of acquisition is extracted respectively；
Calculate separately the area of the foreground area of each image of acquisition, and by the corresponding image of the area of maximum foreground area,
It is determined as the most intermediate objective image of the target for including.
2. target image choosing method according to claim 1, which is characterized in that in each image for extracting acquisition respectively
Further include step before foreground area：
Each image of acquisition is smoothed respectively.
3. target image choosing method according to claim 1, which is characterized in that before each image for extracting acquisition respectively
The step of scene area includes：
For the image of each acquisition, the gray value of each pixel of the image is compared with presetted pixel threshold value；
The image is split according to the gray value of each pixel and the comparison result of presetted pixel threshold value, obtains being somebody's turn to do for extraction
The foreground area of image.
4. target image choosing method according to claim 3, which is characterized in that the presetted pixel threshold value passes through following
Mode determines：
The gray value of each pixel of image is compared with pixel threshold undetermined, determines that the image is based on the pixel threshold undetermined
The foreground pixel point and background pixel point of value；
According to each foreground pixel point and each background pixel point, the inter-class variance of foreground class pixel and background classes pixel is calculated；
The corresponding pixel threshold undetermined of maximum inter-class variance is determined as the presetted pixel threshold value.
5. target image choosing method according to claim 1, which is characterized in that analyzed in each image from acquisition true
After making the most intermediate objective image of the target for including, the front and back predetermined number adjacent with the intermediate objective image is chosen
Image before, further include step：
It determines the target area of the intermediate objective image, and rectangle mark is carried out to determining target area, obtain to target
Intermediate objective image after region rectangle mark.
6. target image choosing method according to claim 5, which is characterized in that calculate the clarity of each image of selection
Mode include：
The clarity of the target area for each image chosen is calculated, and using the clarity of the target area of each image as the image
Clarity.
7. a kind of target image selecting device, which is characterized in that including：
Image analysis module, each image for obtaining acquisition；And each described image is analyzed respectively, from each described image
The most intermediate objective image of the target for including is determined in middle analysis；
Sharpness computation module, the image for choosing the front and back predetermined number adjacent with the intermediate objective image, and calculate
The clarity for each image chosen；The clarity of described image is the sum of the clarity of each target area of the image；
Module is chosen, for the corresponding image of maximum clarity to be chosen for final goal image；
Wherein, the sharpness computation module is specifically used for extracting the foreground area of each image of acquisition respectively, and calculates separately
The area of the foreground area of each image of acquisition, and by the corresponding image of the area of maximum foreground area, be determined as include
The most intermediate objective image of target.
8. a kind of computer equipment, including memory, processor and it is stored on the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
Method described in 6 any one.
9. a kind of computer storage media, is stored thereon with computer program, which is characterized in that when the program is executed by processor
Realize the method as described in claim 1 to 6 any one.
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| CN110175980A (en) * | 2019-04-11 | 2019-08-27 | 平安科技（深圳）有限公司 | Image definition recognition methods, image definition identification device and terminal device |
| CN110781713A (en) * | 2019-06-21 | 2020-02-11 | 中云智慧（北京）科技有限公司 | Method and device for obtaining target image |
| CN110763679A (en) * | 2019-10-31 | 2020-02-07 | 湖南爱威医疗科技有限公司 | Image acquisition method and device, microscope system and computer readable storage medium |
| CN112734767B (en) * | 2020-12-28 | 2024-05-07 | 平安科技（深圳）有限公司 | Extraction method, device, equipment and medium based on pathological image tissue region |
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| CN103345756B (en) * | 2013-07-19 | 2016-08-10 | 浙江农林大学 | Microscopical Atomatic focusing method, device and electronic equipment in a kind of urine sediments analyzer |
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