CN110087063A - A kind of image processing method, device and electronic equipment - Google Patents
A kind of image processing method, device and electronic equipment Download PDFInfo
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- CN110087063A CN110087063A CN201910333197.3A CN201910333197A CN110087063A CN 110087063 A CN110087063 A CN 110087063A CN 201910333197 A CN201910333197 A CN 201910333197A CN 110087063 A CN110087063 A CN 110087063A
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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
- G06T7/136—Segmentation; Edge detection involving thresholding
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
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Abstract
The present embodiments relate to technical field of image processing, in particular to a kind of image processing method, device and electronic equipment.This method passes through the division to image to be processed progress image-region, and then independent process is carried out to each image-region that division obtains, the brightness value in each image-region obtained based on statistics calculates the binarization threshold of each image-region, then binary conversion treatment is carried out to the image in each image-region according to the binarization threshold of each image-region, finally each image-region for completing binary conversion treatment is spliced to obtain target image, so, it can be improved the accuracy of binary conversion treatment, and then realize the accurate positionin of visual field bevel edge.
Description
Technical field
The present embodiments relate to technical field of image processing, in particular to a kind of image processing method, device and
Electronic equipment.
Background technique
Camera module at present needs to carry out resolving power test before factory, can generally use the spatial frequency of black and white bevel edge
Response algorithm (spatial frequency response, SFR) is tested.When test using SFR algorithm,
Firstly the need of the positioning for carrying out each visual field bevel edge to SFR chart figure (oblique black and white chessboard trrellis diagram piece).But the prior art is difficult to
Realize the accurate positionin of visual field bevel edge.
Summary of the invention
In view of this, the present invention provides a kind of image processing method, device and electronic equipments.
The embodiment of the invention provides a kind of image processing methods, comprising:
Image to be processed is divided into multiple images region；
For each image-region divided in obtained multiple images region, the brightness value in the image-region is counted,
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains；Based on the binarization threshold to the image
Image in region carries out binary conversion treatment；
The each image-region for completing binary conversion treatment is spliced to obtain target image.
Optionally, the step of binarization threshold of the image-region being calculated according to the brightness value that statistics obtains, comprising:
The brightness value that statistics obtains is ranked up；
It calculates in the setting range of the first average value and sequence of the brightness value in forward setting range that sorts rearward
Brightness value the second average value；
The binarization threshold of the image-region is obtained according to first average value and second mean value calculation.
Optionally, the binaryzation threshold of the image-region is obtained according to first average value and second mean value calculation
The step of value, comprising:
Calculate binarization threshold of the average value of first average value and second average value as the image-region.
Optionally, the step of binary conversion treatment being carried out to the image in the image-region based on the binarization threshold, packet
It includes:
For each brightness value counted in the image-region, judge whether the brightness value reaches the binaryzation threshold
Value；
If the brightness value reaches the binarization threshold, the first setting is set by the color of the corresponding image of the brightness value
Color；
If the brightness value does not reach the binarization threshold, second is set by the color of the corresponding image of the brightness value
Setpoint color.
The embodiment of the invention also provides a kind of image processing apparatus, comprising:
Image-region division module, for image to be processed to be divided into multiple images region；
Binary processing module, for for each image-region divided in obtained multiple images region, statistics should
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains for brightness value in image-region；Based on institute
It states binarization threshold and binary conversion treatment is carried out to the image in the image-region；
Image mosaic module, for splicing each image-region for completing binary conversion treatment to obtain target figure
Picture.
Optionally, the figure is calculated according to the brightness value that statistics obtains in the following manner in the binary processing module
As the binarization threshold in region:
The brightness value that statistics obtains is ranked up；
It calculates in the setting range of the first average value and sequence of the brightness value in forward setting range that sorts rearward
Brightness value the second average value；
The binarization threshold of the image-region is obtained according to first average value and second mean value calculation.
Optionally, the binary processing module is averaged according to first average value and described second in the following manner
The binarization threshold of the image-region is calculated in value:
Calculate binarization threshold of the average value of first average value and second average value as the image-region.
Optionally, the binary processing module is based on the binarization threshold in the image-region in the following manner
Image carry out binary conversion treatment:
For each brightness value counted in the image-region, judge whether the brightness value reaches the binaryzation threshold
Value；
If the brightness value reaches the binarization threshold, the first setting is set by the color of the corresponding image of the brightness value
Color；
If the brightness value does not reach the binarization threshold, second is set by the color of the corresponding image of the brightness value
Setpoint color.
The embodiment of the invention also provides a kind of electronic equipment, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, the processor are realized when executing the computer program at above-mentioned image
Reason method.
The embodiment of the invention also provides a kind of computer readable storage medium, the readable storage medium storing program for executing includes computer
Program, the electronic equipment computer program controls the readable storage medium storing program for executing when running where execute above-mentioned image processing method
Method.
A kind of image processing method, device and electronic equipment provided in an embodiment of the present invention, by image to be processed into
Each of the division of row image-region, and then independent process is carried out to each image-region that division obtains, obtained based on statistics
Brightness value in image-region calculates the binarization threshold of each image-region, then according to the binaryzation threshold of each image-region
It is worth and binary conversion treatment is carried out to the image in each image-region, finally carries out each image-region for completing binary conversion treatment
Splicing so, it is possible the accuracy for improving binary conversion treatment to obtain target image, and then realize the accurate fixed of visual field bevel edge
Position.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is a kind of abnormal conditions caused by binary processing method common provided by the embodiment of the present invention.
Fig. 2 is another kind abnormal conditions caused by binary processing method common provided by the embodiment of the present invention.
Fig. 3 is the block diagram of a kind of electronic equipment 10 provided by the embodiment of the present invention.
Fig. 4 is a kind of flow chart of image processing method provided by the embodiment of the present invention.
Fig. 5 is a kind of schematic diagram that image-region divides provided by the embodiment of the present invention.
Fig. 6 is the schematic diagram for another sub-step that step S42 shown in Fig. 2 includes in one embodiment of the invention.
Fig. 7 is the schematic diagram for the another sub-step that step S42 shown in Fig. 2 includes in one embodiment of the invention.
Fig. 8 is a kind of schematic diagram of binary conversion treatment provided by the embodiment of the present invention.
Fig. 9 is a kind of schematic diagram of image mosaic provided by the embodiment of the present invention.
Figure 10 is a kind of module frame chart of image processing apparatus 20 provided by the embodiment of the present invention.
Icon:
10- electronic equipment；11- memory；12- processor；13- network module；
20- image processing apparatus；21- image-region division module；22- binary processing module；23- image mosaic mould
Block.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment only
It is a part of the embodiments of the present invention, instead of all the embodiments.The present invention being usually described and illustrated herein in the accompanying drawings
The component of embodiment can be arranged and be designed with a variety of different configurations.
Therefore, the detailed description of the embodiment of the present invention provided in the accompanying drawings is not intended to limit below claimed
The scope of the present invention, but be merely representative of selected embodiment of the invention.Based on the embodiments of the present invention, this field is common
Technical staff's every other embodiment obtained without creative efforts belongs to the model that the present invention protects
It encloses.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need that it is further defined and explained in subsequent attached drawing.
Inventor further investigation reveals that, the main reason for prior art is difficult to realize the accurate positionin of visual field bevel edge is binaryzation
The accuracy of processing is not high.In location technology, it is necessary first to carry out binaryzation to image and (i.e. gray level image, become non-black
I.e. white two kinds of color images), to extract black and white profile information.But the common binary processing method of the prior art is logical
A given fixed binarization threshold is crossed to carry out the binaryzation of image, this will lead to binary conversion treatment and large error occurs.
For example, due to the difference of ambient brightness and different type camera module, using fixed binarization threshold come into
The binaryzation of row image, which is easy to cause, grabs frame exception, further, since camera module itself has a dark angle of camera lens, among image and
The brightness of quadrangle has very big difference (intermediate brighter, quadrangle is than darker), in this way, occurring when will lead to binary conversion treatment intermediate
Cross the excessively black situation in white or quadrangle.
As shown in Figure 1, Fig. 1 shows a kind of abnormal conditions caused by common binary processing method, in such case
Under, since binarization threshold value is excessively high, cause image quadrangle excessively black.
As shown in Fig. 2, Fig. 2 shows another kind abnormal conditions caused by common binary processing method, in this feelings
Under condition, since binarization threshold value is too low, cause excessively white among image.
Defect present in the above scheme in the prior art, is that inventor is obtaining after practicing and carefully studying
As a result, therefore, the solution that the discovery procedure of the above problem and the hereinafter embodiment of the present invention are proposed regarding to the issue above
Scheme all should be the contribution that inventor makes the present invention in process of the present invention.
Based on the studies above, the embodiment of the invention provides a kind of image processing method, device and electronic equipment, Neng Gouti
The accuracy of high binary conversion treatment, and then realize the accurate positionin of visual field bevel edge.
Fig. 3 shows the block diagram of a kind of electronic equipment 10 provided by the embodiment of the present invention.The embodiment of the present invention
In electronic equipment 10 have data storage, transmission, processing function, as shown in figure 3, electronic equipment 10 include: memory 11, place
Manage device 12, network module 13 and image processing apparatus 20.
It is directly or indirectly electrically connected between memory 11, processor 12 and network module 13, to realize the biography of data
Defeated or interaction.It is electrically connected for example, these elements can be realized from each other by one or more communication bus or signal wire.
Image processing apparatus 20 is stored in memory 11, described image processing unit 20 includes at least one can be with software or firmware
(firmware) form is stored in the software function module in the memory 11, and the processor 12 is stored in by operation
The image processing apparatus 20 in software program and module, such as the embodiment of the present invention in memory 11, thereby executing various
Functional application and data processing, i.e. image processing method in the realization embodiment of the present invention.
Wherein, the memory 11 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only memory (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Wherein, memory 11 is for storing program, and the processor 12 executes described program after receiving and executing instruction.
The processor 12 may be a kind of IC chip, the processing capacity with data.Above-mentioned processor 12
It can be general processor, including central processing unit (Central Processing Unit, CPU), network processing unit
(Network Processor, NP) etc..It may be implemented or execute each method, step disclosed in the embodiment of the present invention and patrol
Collect block diagram.General processor can be microprocessor or the processor is also possible to any conventional processor etc..
Network module 13 is used to establish the communication connection between electronic equipment 10 and other communication terminal devices by network,
Realize the transmitting-receiving operation of network signal and data.Above-mentioned network signal may include wireless signal or wire signal.
It is appreciated that structure shown in Fig. 3 is only to illustrate, electronic equipment 10 may also include it is more than shown in Fig. 3 or
Less component, or with the configuration different from shown in Fig. 3.Each component shown in Fig. 3 can using hardware, software or its
Combination is realized.
The embodiment of the present invention also provides a kind of computer readable storage medium, and the readable storage medium storing program for executing includes computer journey
Sequence.Electronic equipment 10 computer program controls the readable storage medium storing program for executing when running where executes following image processing method
Method.
Fig. 4 shows a kind of flow chart of image processing method provided by the embodiment of the present invention.The method is related
Method and step defined in process is applied to electronic equipment 10, can be realized by the processor 12.It below will be to shown in Fig. 4
Detailed process is described in detail:
Image to be processed is divided into multiple images region by step S41.
As shown in figure 5, image to be processed is divided into multiple images region according to being sized.In the present embodiment, may be used
Image to be processed is divided into M*N image-region, for example, 7*6 image-region can be divided into, so divide, it can
Enough guarantee the accuracy of subsequent binary conversion treatment, and calculation amount can be reduced.
Step S42 is counted in the image-region for each image-region divided in obtained multiple images region
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains for brightness value, based on binarization threshold to this
Image in image-region carries out binary conversion treatment.
It please refers to Fig. 6, step S42 is listed by step S421, step S422 and step S423 in the present embodiment
One of implementation.
Step S421 counts the brightness value in the image-region.
For example, by taking i-th of image-region as an example, 0 < i≤42, i ∈ Z.Statistics obtains the brightness in i-th of image-region
The quantity of value is 100, wherein this 100 brightness values situation equal there may be part.
The brightness value that statistics obtains is ranked up by step S422.
For example, 100 brightness values in i-th of image-region are ranked up, wherein sequence can from high to low may be used
From low to high, it is not limited thereto.
Step S423 calculates the first average value and sequence the setting rearward of the brightness value in forward setting range that sorts
The second average value for determining the brightness value in range obtains the two of the image-region according to the first average value and the second mean value calculation
Value threshold value.
In the present embodiment, the first average value for calculating the brightness value in forward setting range that sorts can be understood as most
The average value of x% bright brightness value, wherein the x in setting range x% is not more than 50, and in the present embodiment, x is, for example, 30,
It so, it is possible to be balanced brightness value different in each image-region, caused by avoiding individual brightness values excessive or too small
Relatively large deviation.
In other words, the first average value be 30% most bright brightness value average value, that is to say, that if by brightness value by
High to Low sequence is ranked up 100 brightness values in i-th of image-region, and the first average value is forward 30 of sequence
The average value of brightness value.Correspondingly, the second average value for calculating the brightness value in the setting range of sequence rearward can be understood as
The average value of 30% most dark brightness value, correspondingly, if by the sequence of brightness value from high to low in i-th of image-region
100 brightness values are ranked up, and the second average value is the average value of 30 brightness values of sequence rearward.
In the present embodiment, the first average value is x1, and the second average value is x2, the binarization threshold of i-th of image-region
For the average value of x1 and x2.It so, it is possible that the binarization threshold of each image-region is set dynamically, and then avoid
Clean cut bring grabs frame exception.
It is appreciated that the sum of the brightness value in each image-region is different, sort using determined by setting range x%
The quantity of the brightness value of forward and sequence rearward is also different, determines by using setting range x% and sorts forward and sequence rearward
Brightness value quantity and it is indirect forward and sequence brightness value rearward the quantity that sorts is configured, can be improved first
The flexibility and convenience of average value and the second mean value calculation, and then improve and the binarization threshold of each image-region is arranged
Flexibility and convenience.
It please refers to Fig. 7, step S42 is listed by step S424, step S425 and step S426 in the present embodiment
Another implementation.
Step S424 judges whether the brightness value reaches two for each brightness value counted in the image-region
Value threshold value.
For example, judging whether the brightness value reaches i-th for each brightness value that statistics in i-th of image-region obtains
The binarization threshold of a image-region turns to step S425 if reaching, and otherwise, turns to step S426.
The color of the corresponding image of the brightness value is set the first setpoint color by step S425.
If j-th of brightness value in i-th of image-region reaches the binarization threshold of i-th of image-region, bright by j-th
The color of the corresponding image of angle value is set as the first setpoint color, and in the present embodiment, the first setpoint color can be white, such as
Shown in Fig. 8.Wherein, 0 < j≤100, j ∈ Z.
Wherein, the binarization threshold that j-th of brightness value in i-th of image-region reaches i-th of image-region can manage
Solution are as follows: j-th of brightness value in i-th of image-region is greater than or equal to the binarization threshold of i-th of image-region.
The color of the corresponding image of the brightness value is set the second setpoint color by step S426.
If k-th of brightness value in i-th of image-region does not reach the binarization threshold of i-th of image-region, by jth
The color of the corresponding image of a brightness value is set as the second setpoint color, and in the present embodiment, the second setpoint color can be black
Color, as shown in figure 8,0 < k≤100, k ≠ j, k ∈ Z.
Wherein, the binarization threshold that j-th of brightness value in i-th of image-region does not reach i-th of image-region can
To understand are as follows: the binarization threshold of j-th of brightness value in i-th of image-region less than i-th of image-region.
The independent binary conversion treatment that can be realized each image-region by step S424~step S426, to effectively keep away
The case where exempting from binary conversion treatment clean cut please refers to Fig. 1, and four angular brightness of Fig. 1 are relatively dark, can use step
The binarization threshold in the corresponding image-region in quadrangle can be set dynamically in S424~step S426, for example, using step
The binarization threshold in region corresponding to the quadrangle in Fig. 1 is calculated in rapid S424~step S426 may be lower, in another example,
The binarization threshold in region corresponding to the centre in Fig. 2 is calculated using step S424~step S426 may be higher,
It so, it is possible adaptive polo placement and adjustment that binarization threshold is carried out according to the intrinsic brilliance situation of each image-region.
Step S43 splices each image-region for completing binary conversion treatment to obtain target image.
For example, splicing 42 image-regions for completing binary conversion treatment according to the position before division to obtain mesh
Logo image, as shown in Figure 9.
Fig. 1, Fig. 2 and Fig. 9 are please referred to, Fig. 9 is significantly improved relative to the binary conversion treatment accuracy of Fig. 1 and Fig. 2, from
And it effectively prevents grabbing frame exception.
On the basis of the above, as shown in Figure 10, the embodiment of the invention provides a kind of module frames of image processing apparatus 20
Figure, described image processing unit 20 includes: image-region division module 21, binary processing module 22 and image mosaic module
23。
Image-region division module 21, for image to be processed to be divided into multiple images region.
Since image-region division module 21 is similar with the realization principle of step S41 in Fig. 4, do not say more herein
It is bright.
Binary processing module 22, for for each image-region divided in obtained multiple images region, statistics
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains for brightness value in the image-region；It is based on
The binarization threshold carries out binary conversion treatment to the image in the image-region.
Since binary processing module 22 is similar with the realization principle of step S42 in Fig. 4, do not say more herein
It is bright.
Image mosaic module 23, for splicing each image-region for completing binary conversion treatment to obtain target figure
Picture.
Since image mosaic module 23 is similar with the realization principle of step S43 in Fig. 4, do not illustrate more herein.
To sum up, a kind of image processing method, device provided by the embodiment of the present invention and electronic equipment, can be to be processed
Image carries out image-region division, and independently carries out binary conversion treatment for each image-region, so, it is possible to improve binaryzation
The accuracy of processing, and then realize the accurate positionin of visual field bevel edge.
In several embodiments provided by the embodiment of the present invention, it should be understood that disclosed device and method, it can also
To realize by another way.Device and method embodiment described above is only schematical, for example, in attached drawing
Flow chart and block diagram show that the devices of multiple embodiments according to the present invention, method and computer program product are able to achieve
Architecture, function and operation.In this regard, each box in flowchart or block diagram can represent module, a program
A part of section or code, a part of the module, section or code include that one or more is patrolled for realizing defined
Collect the executable instruction of function.It should also be noted that in some implementations as replacement, function marked in the box
It can occur in a different order than that indicated in the drawings.For example, two continuous boxes can actually be held substantially in parallel
Row, they can also be executed in the opposite order sometimes, and this depends on the function involved.It is also noted that block diagram and/or
The combination of each box in flow chart and the box in block diagram and or flow chart, can the function as defined in executing or dynamic
The dedicated hardware based system made is realized, or can be realized using a combination of dedicated hardware and computer instructions.
In addition, each functional module in each embodiment of the present invention can integrate one independent portion of formation together
Point, it is also possible to modules individualism, an independent part can also be integrated to form with two or more modules.
It, can be with if the function is realized and when sold or used as an independent product in the form of software function module
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, electronic equipment 10 or the network equipment etc.) execute all or part of step of each embodiment the method for the present invention
Suddenly.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), deposits at random
The various media that can store program code such as access to memory (RAM, Random Access Memory), magnetic or disk.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to the packet of nonexcludability
Contain, so that the process, method, article or equipment for including a series of elements not only includes those elements, but also including
Other elements that are not explicitly listed, or further include for elements inherent to such a process, method, article, or device.
In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including the element
Process, method, article or equipment in there is also other identical elements.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of image processing method characterized by comprising
Image to be processed is divided into multiple images region；
For each image-region divided in obtained multiple images region, the brightness value in the image-region is counted, according to
Count the binarization threshold that the image-region is calculated in obtained brightness value；Based on the binarization threshold to the image-region
Interior image carries out binary conversion treatment；
The each image-region for completing binary conversion treatment is spliced to obtain target image.
2. image processing method according to claim 1, which is characterized in that be calculated according to the brightness value that statistics obtains
The step of binarization threshold of the image-region, comprising:
The brightness value that statistics obtains is ranked up；
It calculates bright in the setting range of the first average value and sequence of the brightness value in forward setting range that sorts rearward
Second average value of angle value；
The binarization threshold of the image-region is obtained according to first average value and second mean value calculation.
3. image processing method according to claim 2, which is characterized in that according to first average value and described second
Mean value calculation obtains the step of binarization threshold of the image-region, comprising:
Calculate binarization threshold of the average value of first average value and second average value as the image-region.
4. image processing method according to claim 1, which is characterized in that based on the binarization threshold to the image district
The step of image in domain carries out binary conversion treatment, comprising:
For each brightness value counted in the image-region, judge whether the brightness value reaches the binarization threshold；
If the brightness value reaches the binarization threshold, the first setting face is set by the color of the corresponding image of the brightness value
Color；
If the brightness value does not reach the binarization threshold, the second setting is set by the color of the corresponding image of the brightness value
Color.
5. a kind of image processing apparatus characterized by comprising
Image-region division module, for image to be processed to be divided into multiple images region；
Binary processing module, for counting the image for each image-region divided in obtained multiple images region
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains for brightness value in region；Based on described two
Value threshold value carries out binary conversion treatment to the image in the image-region；
Image mosaic module, for splicing each image-region for completing binary conversion treatment to obtain target image.
6. image processing apparatus according to claim 5, which is characterized in that the binary processing module passes through with lower section
The binarization threshold of the image-region is calculated according to the brightness value that statistics obtains for formula:
The brightness value that statistics obtains is ranked up；
It calculates bright in the setting range of the first average value and sequence of the brightness value in forward setting range that sorts rearward
Second average value of angle value；
The binarization threshold of the image-region is obtained according to first average value and second mean value calculation.
7. image processing apparatus according to claim 6, which is characterized in that the binary processing module passes through with lower section
Formula obtains the binarization threshold of the image-region according to first average value and second mean value calculation:
Calculate binarization threshold of the average value of first average value and second average value as the image-region.
8. image processing apparatus according to claim 5, which is characterized in that the binary processing module passes through with lower section
Formula carries out binary conversion treatment to the image in the image-region based on the binarization threshold:
For each brightness value counted in the image-region, judge whether the brightness value reaches the binarization threshold；
If the brightness value reaches the binarization threshold, the first setting face is set by the color of the corresponding image of the brightness value
Color；
If the brightness value does not reach the binarization threshold, the second setting is set by the color of the corresponding image of the brightness value
Color.
9. a kind of electronic equipment, which is characterized in that on a memory and can be in processor including memory, processor and storage
The computer program of upper operation, the processor realize any one of the claims 1-4 institute when executing the computer program
The image processing method stated.
10. a kind of computer readable storage medium, which is characterized in that the readable storage medium storing program for executing includes computer program, described
Electronic equipment executes described in any one of the claims 1-4 computer program controls the readable storage medium storing program for executing when running where
Image processing method.
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| CN201910333197.3A Pending CN110087063A (en) | 2019-04-24 | 2019-04-24 | A kind of image processing method, device and electronic equipment |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110503605A (en) * | 2019-08-27 | 2019-11-26 | Oppo广东移动通信有限公司 | A kind of image processing method, device and storage medium |
| CN111366104A (en) * | 2020-03-26 | 2020-07-03 | 深圳市菲森科技有限公司 | Scanning method and device with automatic brightness adjusting function and electronic equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1790378A (en) * | 2005-12-21 | 2006-06-21 | 北大方正集团有限公司 | Binary method and system for image |
| CN104517089A (en) * | 2013-09-29 | 2015-04-15 | 北大方正集团有限公司 | Two-dimensional code decoding system and method |
| CN106096610A (en) * | 2016-06-13 | 2016-11-09 | 湖北工业大学 | A kind of file and picture binary coding method based on support vector machine |
| CN106157323A (en) * | 2016-08-30 | 2016-11-23 | 西安工程大学 | The insulator division and extracting method that a kind of dynamic division threshold value and block search combine |
| CN107808381A (en) * | 2017-09-25 | 2018-03-16 | 哈尔滨理工大学 | A kind of unicellular image partition method |
-
2019
- 2019-04-24 CN CN201910333197.3A patent/CN110087063A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1790378A (en) * | 2005-12-21 | 2006-06-21 | 北大方正集团有限公司 | Binary method and system for image |
| CN104517089A (en) * | 2013-09-29 | 2015-04-15 | 北大方正集团有限公司 | Two-dimensional code decoding system and method |
| CN106096610A (en) * | 2016-06-13 | 2016-11-09 | 湖北工业大学 | A kind of file and picture binary coding method based on support vector machine |
| CN106157323A (en) * | 2016-08-30 | 2016-11-23 | 西安工程大学 | The insulator division and extracting method that a kind of dynamic division threshold value and block search combine |
| CN107808381A (en) * | 2017-09-25 | 2018-03-16 | 哈尔滨理工大学 | A kind of unicellular image partition method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110503605A (en) * | 2019-08-27 | 2019-11-26 | Oppo广东移动通信有限公司 | A kind of image processing method, device and storage medium |
| CN110503605B (en) * | 2019-08-27 | 2023-03-24 | Oppo广东移动通信有限公司 | Image processing method, device and storage medium |
| CN111366104A (en) * | 2020-03-26 | 2020-07-03 | 深圳市菲森科技有限公司 | Scanning method and device with automatic brightness adjusting function and electronic equipment |
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