CN108600638A - Video camera automatic focusing system and method - Google Patents
Video camera automatic focusing system and method Download PDFInfo
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- CN108600638A CN108600638A CN201810652650.2A CN201810652650A CN108600638A CN 108600638 A CN108600638 A CN 108600638A CN 201810652650 A CN201810652650 A CN 201810652650A CN 108600638 A CN108600638 A CN 108600638A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/67—Focus control based on electronic image sensor signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
Abstract
The invention discloses a kind of video camera automatic focusing system and methods, are related to camcorder technology field.The method of the invention includes：Microprocessor receives video camera shooting current scene picture, the focusing position of several objects and background in picture is obtained by picture focus estimation module, these information of microprocessor processes obtain opposite focusing positional value, these values be transmitted to focusing control module carry out to focus motor control, often move a position, shoot a pictures, after all focal positions shooting of input is finished, all pictures are transmitted to image fusion processing module, finally obtain a high-resolution image, the preview on video camera display screen, or deposit memory chip.The defects of it is slow that the method for the invention can solve inaccurate, the other automatic focusing speed manually focused now, and efficiency is low, ideal high-definition picture is not immediately available in existing video camera.
Description
Technical field
The present invention relates to camcorder technology field more particularly to a kind of video camera automatic focusing system and methods.
Background technology
The focusing of camera is gradually replaced by automatic focusing system or module now initially by carrying out by hand,
And with the development of detector, technology of auto is in continuous improve.More and more video camera, DVs now
Deng all using technology of auto.To make most of automatic focusing problems also highlight, focusing accuracy is inadequate, Bu Nengzhun
True finds focusing position；The focusing time used is longer so that user to wait long time just and can obtain one it is satisfied
Image；Even if mixing up, object be unsharp, this wants technical staff's post-processing, can just obtain a height
The shortcomings that image of resolution ratio etc..And these problems then directly affect the experience of client.
Existing complete burnt imaging system, generally comprises three parts：High speed imaging part, high speed zoom lens part are high
Fast image processing circuit part.These are very high to technology requirement, so that the cost of production video camera is generally higher, accordingly
The higher that price also becomes therewith.This complete burnt imaging system also highlights unessential scenery so that the target to be shot
Scenery cannot well be shown.User cannot sometimes obtain oneself desired effect when watching picture.
Invention content
It is high the technical problem to be solved by the present invention is to how provide a kind of precision, it is efficient, it can automatically generate ideal
The video camera automatic focusing system and method for high-definition picture.
In order to solve the above technical problems, the technical solution used in the present invention is：A kind of video camera automatic focusing system,
It is characterized in that：Including microprocessor module, focusing control module is bi-directionally connected with the microprocessor, the control terminal for motor of focusing
It is connect with the control signal output of the focusing control module, microprocessor controls the tune by the focusing control module
Burnt motor action；The signal output end of position feedback module is connect with the signal input part of the focusing control module；Video camera
The control signal of shaking detection module is connect with the signal output end of the focusing control module, the DE Camera Shake detection
The output end of module is connect with the signal input part of the microprocessor；The signal output end of camera lens and the microprocessor
The signal input part of device connects；Camera shutter is bi-directionally connected with the microprocessor；The microprocessor respectively with focus
Estimation module and image co-registration module are bi-directionally connected, and picture focus estimation module is used for the coke to the picture of camera acquisition
Point is estimated that described image fusion treatment module is used to carry out fusion treatment to the image of camera acquisition.
Further technical solution is：The system also includes video camera display screen, the video camera display screen and institute
It states microprocessor to be bi-directionally connected, the data of the control for receiving microprocessor and display microprocessor output.
Further technical solution is：The system also includes memory chip, the memory chip and the microprocessor
Device is bi-directionally connected, the data after the program and microprocessor processes that are needed for storage microprocessor.
The invention also discloses a kind of video camera automatic focusing methods, it is characterised in that includes the following steps：
Camera lens acquire the image of current scene in focus original position, pass it through microprocessor control and are sent to
Picture focus estimation module；
Picture focusing module carries out focus estimation to picture, and the information of focus is sent to microprocessor and is handled；
It is big to calculate the focusing motor relative distance to be moved every time for range information size of the microprocessor according to focus
It is small, corresponding opposite focal length value is obtained, tune is sent to after these are sorted well according to certain rules with respect to focal length value
Burnt control module；
Focusing control module sends focusing order and gives focusing motor, the figure on control camera lens shooting specific focal point position successively
Piece, after sending order each time, whether position feedback module detection focusing motor arrived corresponding position, and send a signal to
Focusing control module, focusing control module send a signal to DE Camera Shake detection module, shaking detection mould after being connected to information
After block detects that video camera is in stable state, microprocessor is sent a signal to, microprocessor controls press camera shutter again,
The picture shot is kept in microprocessor, is so recycled, is once passed to microprocessor until focusing control module
Opposite focal length value is sent；
All pictures taken are all transmitted to image fusion processing module and handled by microprocessor, image co-registration processing
The image of fusion is then forwarded to microprocessor by module；
Image is included on the display screen of video camera, if it can, photographer presses OK keys, microprocessor by microprocessor
Device is by generated picture, there are on memory chip automatically；And microprocessor internal zeros data, focusing motor return to just
Beginning position is ready for shooting next time.
Further technical solution is that the method that the picture focusing module carries out picture focus estimation is as follows：
1) focal adjustments to initial origin position are shot present scene figure by the video camera for capableing of manual focusing with one
Then piece is focused successively, find the optimal imaging position of each target object, and records the required focusing of each object scene
Distance constitutes picture；
2) image data collection is trained using VGG-16 neural networks.
3) finally mapping piece is treated using trained model to be differentiated, and export each object scene in picture to be measured
Focal length.
Further technical solution is that the method that the VGG-16 neural networks parameters calculate is as follows：
1) calculation formula of convolutional layer is as follows：
Wherein,Indicate j-th of Feature Mapping of l convolution,Indicate the ith feature mapping of l-1 convolution, Mj
Indicate the set of input feature vector mapping,Indicate convolution kernel,Indicate bias term.
2) mode that pond layer is taken is maximum value pond, and calculation formula is as follows：
3) three full articulamentum sizes are 4096,4096,1000 respectively.Wherein the last one full articulamentum should be by 1000
The categorical measure 120 for being changed to input data set is used for classifying；
4) method that the Gaussian Profile directly proposed using VGG team generates weights at random carrys out initiation parameter；
5) penalty coefficient L2, since data set is smaller, so the value that uses of the present invention is 0.0001；
6) momentum is the physical parameter being arranged for accelerating stochastic gradient descent, and the present invention is using improved
Nesterov momentum methods, and momentum is set as 0.9.
Further technical solution is, microprocessor by all pictures taken be transmitted to image fusion processing module into
The method of row processing is as follows：
Original multiple images are divided into the block of b*b sizes, use Ai,Bi,Ci... respectively represent image A, B, C... image
I-th piece；
Quality assessment parameter λ is calculated to each block of every piece image, is denoted as respectively
CompareIt incites somebody to action the maximum in wherein same area and is denoted as 1；
Morphological operation will be carried out labeled as 1 image, is merged later using different fusion rules.
It is using advantageous effect caused by above-mentioned technical proposal：The present invention can solve existing focusing artificial in the art
Inaccurate, other automatic focusing speed it is slow, efficiency is low, the problems such as ideal high-definition picture is not immediately available.It is described
System and method focusing accuracies is high, speed is fast, efficient, can be instantly available ideal high-definition picture.
Description of the drawings
The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
Fig. 1 is the functional block diagram of system described in the embodiment of the present invention；
Fig. 2 is the process chart of focus estimation module in the method for the embodiment of the present invention；
The network structure of VGG-16 in Fig. 3 the methods of the embodiment of the present invention；
Fig. 4 is the multifocal image co-registration flow chart of quality evaluation and Wavelet Fusion in inventive embodiments the method.
Specific implementation mode
With reference to the attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground describes, it is clear that described embodiment is only a part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Many details are elaborated in the following description to facilitate a thorough understanding of the present invention, still the present invention can be with
Implemented different from other manner described here using other, those skilled in the art can be without prejudice to intension of the present invention
In the case of do similar popularization, therefore the present invention is not limited by following public specific embodiment.
As shown in Figure 1, the embodiment of the invention discloses a kind of video camera automatic focusing system, including microprocessor module,
Preferably, microprocessor module uses DSP；Focusing control module is bi-directionally connected with the microprocessor, the control for motor of focusing
The control signal output with the focusing control module is held to connect, microprocessor passes through described in focusing control module control
Focusing motor action；The signal output end of position feedback module is connect with the signal input part of the focusing control module；Camera shooting
The control signal of machine shaking detection module is connect with the signal output end of the focusing control module, the DE Camera Shake inspection
The output end for surveying module is connect with the signal input part of the microprocessor；The signal output end of camera lens and micro- place
Manage the signal input part connection of device；Camera shutter is bi-directionally connected with the microprocessor；The microprocessor respectively with coke
Point estimation module and image co-registration module are bi-directionally connected, and picture focus estimation module is used for the picture of camera acquisition
Focus is estimated that described image fusion treatment module is used to carry out fusion treatment to the image of camera acquisition.
The high-definition picture that the video camera display screen being connected with DSP can be obtained with preview, and being confirmed by operator should
Whether high-definition picture meets the requirements.
The DE Camera Shake detection module being connected with DSP, whether video camera is in after can detecting focusing motor rotation
Stable state sends out signal if stablized, and notice DSP can press shutter.The DE Camera Shake detection module packet
Sensor containing shaking detection, the data provided by shaking detection sensor judge whether camera is stablized.
The focusing control module being connected with DSP receives the focus relative distance value sended over from dsp chip, and
Focusing motor can be controlled successively to turn on corresponding position, can also receive the information that position feedback module is fed back,
Judge whether motor is moved to the location of corresponding position, and current focusing motor, and controls DE Camera Shake detection module
Work.
The invention also discloses a kind of video camera automatic focusing methods, include the following steps：
Step 1：Camera lens acquire the image of current scene in focus original position, pass it through DSP controls and send
Give picture focus estimation module.
Step 2：Picture focusing module carries out focus estimation to picture, and the information of focus is sent to DSP processing.
With reference to figure 2, the processing method of focus estimation module is as follows：
(1) focal adjustments to initial origin position can be shot into present scene figure with the video camera of manual focusing with one
Then piece is focused successively, find the optimal imaging position of each target object, and records the required focusing of each object scene
Distance.So successively acquisition same target scenery same distance and different distance picture, different target scenery it is identical away from
From the picture with different distance.It is cloudy and in sun Gao Zhao, it is sampled respectively under the ambient conditions such as cloudy day.One is divided into 12 groups, often
About 100 photos of group, and every photo, needed for the pixel region of different readabilities (being at most divided into 10 kinds of difference clarity)
The distance to be focused is classified and is marked.
(2) image data collection is trained using VGG-16 neural networks.With reference to Fig. 3, white represents convolutional layer
(convolution) and active coating (ReLU), Dark grey represent full articulamentum (fully connected) and active coating
(ReLU).The neural network by 13 extraction features convolutional layer formed with 3 full articulamentums, between convolutional layer also 5 most
Great Chiization layer.In addition to the last one full articulamentum, all use ReLU as activation unit after all hidden layers.Due to data set ratio
It is smaller, so closing Dropout.
The VGG-16 neural networks parameters calculate step and further comprise：
The calculation formula of convolutional layer is as follows：
Wherein,Indicate j-th of Feature Mapping of l convolution,Indicate the ith feature mapping of l-1 convolution, Mj
Indicate the set of input feature vector mapping,Indicate convolution kernel,Indicate bias term.
The mode that pond layer is taken is maximum value pond, and calculation formula is as follows：
Three full articulamentum sizes are 4096,4096,1000 respectively.Wherein the last one full articulamentum should change 1000
It is used for classifying for the categorical measure 120 of input data set.
The method that the Gaussian Profile directly proposed using VGG team generates weights at random carrys out initiation parameter.
Penalty coefficient L2, since data set is smaller, so the value that uses of the present invention is 0.0001.
Momentum is the physical parameter being arranged for accelerating stochastic gradient descent, and the present invention is using improved
Nesterov momentum methods, and momentum is set as 0.9.
It is trained with the above parameter, the training result than former VGG-16 promotes very much, the best accuracy rate of former VGG-16
It is 90% or so, it is 95% or so to have done the best accuracy rate after finely tuning.
(3) finally mapping piece is treated using trained model to be differentiated, and export each target scape in picture to be measured
The focal length of object.Final accuracy rate maintains 93% or so.
Step 3：Range information size of the dsp chip according to focus, calculate that focusing motor every time to be moved it is opposite away from
From size, corresponding opposite focal length value is obtained, is sent after these are sorted well according to certain rules with respect to focal length value
Give focusing control module.
Step 4：Focusing control module sends focusing order and gives focusing motor, control camera lens shooting specific focal point position successively
The picture set, after sending order each time, position feedback module detects whether to arrived corresponding position, and sends a signal to
Focusing control module, focusing control module signal to DE Camera Shake detection module, shaking detection module after being connected to information
After detecting that video camera is in stable state, dsp chip is signaled to, dsp chip presses camera shutter in control, will shoot
Good picture is kept on dsp chip.So cycle, until the opposite focus that dsp chip is once passed to by focusing control module
Distance value is sent.
Step 5：All pictures taken are all transmitted to image fusion processing module by dsp chip, by the image of fusion
It is sent to DSP.With reference to figure 4, it is explained further quality evaluation and the step of Wavelet Fusion carries out multifocal image co-registration is as follows：
Original multiple images are divided into the block of b*b sizes, use Ai,Bi,Ci... respectively represent image A, B, C... image
I-th piece.
Quality assessment parameter λ is calculated to each block of every piece image, is denoted as respectively
CompareIt incites somebody to action the maximum in wherein same area and is denoted as 1.
Morphological operation will be carried out labeled as 1 image, is merged later using different fusion rules.
Step 6：Dsp chip by image include on the display screen of video camera, if it can, photographer presses OK keys,
Dsp chip is by generated picture, there are on memory chip automatically.And DSP internal datas are reset, and focusing motor returns to just
Beginning position is ready for shooting next time.
Claims (7)
1. a kind of video camera automatic focusing system, it is characterised in that：Including microprocessor module, focusing control module with it is described micro-
Processor is bi-directionally connected, and the control terminal for motor of focusing is connect with the control signal output of the focusing control module, microprocessor
Device controls the focusing motor action by the focusing control module；The signal output end of position feedback module and the focusing
The signal input part of control module connects；The letter of the control signal of DE Camera Shake detection module and the focusing control module
The connection of number output end, the output end of the DE Camera Shake detection module are connect with the signal input part of the microprocessor；It takes the photograph
The signal output end of camera lens is connect with the signal input part of the microprocessor；Camera shutter is double with the microprocessor
To connection；The microprocessor is bi-directionally connected with focus estimation module and image co-registration module respectively, and picture focus is estimated
Focus of the meter module for the picture to camera acquisition estimates that described image fusion treatment module is for adopting video camera
The image of collection carries out fusion treatment.
2. video camera automatic focusing system as described in claim 1, it is characterised in that：The system also includes video cameras to show
Screen, the video camera display screen are bi-directionally connected with the microprocessor, and the control for receiving microprocessor simultaneously shows microprocessor
The data of device output.
3. video camera automatic focusing system as described in claim 1, it is characterised in that：The system also includes memory chip,
The memory chip is bi-directionally connected with the microprocessor, the program and microprocessor processes needed for storage microprocessor
Data afterwards.
4. a kind of video camera automatic focusing method, it is characterised in that include the following steps：
Camera lens acquire the image of current scene in focus original position, pass it through microprocessor control and are sent to picture
Focus estimation module；
Picture focusing module carries out focus estimation to picture, and the information of focus is sent to microprocessor and is handled；
Range information size of the microprocessor according to focus calculates the focusing motor relative distance size to be moved every time, obtains
To corresponding opposite focal length value, focusing control is sent to after these are sorted well according to certain rules with respect to focal length value
Module；
Focusing control module sends focusing order and gives focusing motor successively, controls the picture on camera lens shooting specific focal point position,
After sending order each time, whether position feedback module detection focusing motor arrived corresponding position, and send a signal to tune
Burnt control module, focusing control module send a signal to DE Camera Shake detection module, shaking detection module after being connected to information
After detecting that video camera is in stable state, microprocessor is sent a signal to, microprocessor controls again presses camera shutter, will
The picture shot is kept in microprocessor, is so recycled, until the phase that microprocessor is once passed to by focusing control module
Focus point distance value is sent；
All pictures taken are all transmitted to image fusion processing module and handled by microprocessor, image fusion processing module
The image of fusion is then forwarded to microprocessor；
Image is included on the display screen of video camera by microprocessor, if it can, photographer presses OK keys, microprocessor will
Automatically generated picture, there are on memory chip；And microprocessor internal zeros data, focusing motor return to initial bit
It sets, is ready for shooting next time.
5. video camera automatic focusing method as claimed in claim 4, which is characterized in that the picture focusing module to picture into
The method of row focus estimation is as follows：
1) focal adjustments to initial origin position are shot present scene picture, so by the video camera for capableing of manual focusing with one
It focuses successively afterwards, finds the optimal imaging position of each target object, and record the required focussing distance of each object scene,
Constitute picture；
2) image data collection is trained using VGG-16 neural networks.
3) finally mapping piece is treated using trained model to be differentiated, and export the coke of each object scene in picture to be measured
Point distance.
6. video camera automatic focusing method as claimed in claim 5, which is characterized in that each ginseng of VGG-16 neural networks
The method that number calculates is as follows：
1) calculation formula of convolutional layer is as follows：
Wherein,Indicate j-th of Feature Mapping of l convolution,Indicate the ith feature mapping of l-1 convolution, MjIt indicates
The set of input feature vector mapping,Indicate convolution kernel,Indicate bias term.
2) mode that pond layer is taken is maximum value pond, and calculation formula is as follows：
3) three full articulamentum sizes are 4096,4096,1000 respectively.Wherein the last one full articulamentum should be changed to 1000
The categorical measure 120 of input data set is used for classifying；
4) method that the Gaussian Profile directly proposed using VGG team generates weights at random carrys out initiation parameter；
5) penalty coefficient L2, since data set is smaller, so the value that uses of the present invention is 0.0001；
6) momentum is the physical parameter being arranged for accelerating stochastic gradient descent, and the present invention is using improved Nesterov
Momentum method, and momentum is set as 0.9.
7. video camera automatic focusing method as claimed in claim 5, which is characterized in that microprocessor is by all figures taken
It is as follows that piece is transmitted to the method that image fusion processing module is handled：
Original multiple images are divided into the block of b*b sizes, use Ai,Bi,Ci... respectively represent i-th of image A, B, C... image
Block；
Quality assessment parameter λ is calculated to each block of every piece image, is denoted as respectively
CompareIt incites somebody to action the maximum in wherein same area and is denoted as 1；
Morphological operation will be carried out labeled as 1 image, is merged later using different fusion rules.
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| CN112363309A (en) * | 2020-11-13 | 2021-02-12 | 杭州医派智能科技有限公司 | Automatic focusing method and system for pathological image under microscope |
| CN112469984A (en) * | 2019-12-31 | 2021-03-09 | 深圳迈瑞生物医疗电子股份有限公司 | Image analysis device and imaging method thereof |
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