CN108805894A - Image analysis method and its system - Google Patents
Image analysis method and its system Download PDFInfo
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- CN108805894A CN108805894A CN201810630975.0A CN201810630975A CN108805894A CN 108805894 A CN108805894 A CN 108805894A CN 201810630975 A CN201810630975 A CN 201810630975A CN 108805894 A CN108805894 A CN 108805894A
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- 238000003703 image analysis method Methods 0.000 title claims abstract description 16
- 238000012545 processing Methods 0.000 claims abstract description 120
- 239000011159 matrix material Substances 0.000 claims abstract description 29
- 238000004458 analytical method Methods 0.000 claims abstract description 20
- 230000009467 reduction Effects 0.000 claims abstract description 20
- 238000007781 pre-processing Methods 0.000 claims abstract description 17
- 238000010191 image analysis Methods 0.000 claims abstract description 12
- 238000006243 chemical reaction Methods 0.000 claims abstract description 7
- 230000011218 segmentation Effects 0.000 claims description 13
- 238000003709 image segmentation Methods 0.000 claims description 11
- 239000003086 colorant Substances 0.000 claims description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 238000011946 reduction process Methods 0.000 claims description 6
- 230000004075 alteration Effects 0.000 claims description 5
- 238000000034 method Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000012805 post-processing Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- Color Image Communication Systems (AREA)
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Abstract
The invention discloses a kind of image analysis method and its systems, and this approach includes the following steps：S1, acquisition image is inputted by the external world；S2, image is pre-processed；S3, RGB color processing generation color vector matrix is carried out to image；S4, by image gray processing and binary conversion treatment；S5, processing is split to the image after binaryzation and is analyzed.The invention also discloses a kind of image analysis systems, including acquisition module, preprocessing module, RGB processing modules, processing module, respond module and main control MCU.The present invention carries out gray processing and binaryzation by carrying out RGB color processing after carrying out pre-processing to image to the image after color processing, is split to image after treatment and is compared with the image after noise reduction analysis is identified, and improves and analyzes precision.
Description
Technical field
The present invention relates to technical field of image processing, specifically a kind of image analysis method and its system.
Background technology
More and more image applications have intervened the life of the mankind, working and learning, it is apparent that mobile phone photograph work(
Can raising as the amusement of various brands mobile phone fast sale, and the raising of photographing function of mobile phone is as the term suggests be exactly cell phone system to scheming
The promotion of the processing analytical technology of picture.General traditional image analysis method is to the more demanding in order to which the later stage schemes of original image
When as analysis obtained result is relatively sharp accurate, and generally use is to directly segmentation and to being divided into after image simple process
Image is handled and is analyzed, the advantage is that reduce analyst coverage reduce power consumption, but its segmentation after again to image at
Reason and analysis, it may appear that caused by segmentation image information lose due to impact analysis result the problem of.
Invention content
The purpose of the present invention is to provide a kind of image analysis method and its systems, to solve to propose in above-mentioned background technology
Traditional images analytical technology can because segmentation cause image information lose due to impact analysis result the problem of.
To achieve the above object, the present invention provides the following technical solutions：
A kind of image analysis method, this approach includes the following steps：
S1, acquisition image is inputted by the external world；
S2, image is pre-processed；
S3, RGB color processing generation color vector matrix is carried out to image；
S4, by image gray processing and binary conversion treatment；
S5, processing is split to the image after binaryzation and is analyzed.
Preferably, the S2 includes carrying out noise reduction process and analysis pixel to image to the pretreatment of image.
Preferably, it includes carrying out RGB to image that the S3 generates color vector matrix to the RGB color processing of image
Primary colors handles and is defined according to image aberration the rgb value of each pixel of image, and rgb value is generated color vector matrix.
Preferably, the S4 handles the value after the gray processing of image according to following computational algorithm：
RAfter gray processing=GAfter gray processing=BAfter gray processing=RBefore gray processing×0.3+GBefore gray processing×0.59+BBefore gray processing× 0.11,
The S4 carries out the binary conversion treatment of image according to the comparison of value and threshold value after gray processing, the threshold size root
It is calculated according to the average value of each pixel gray value after gray processing, the computational algorithm is as follows：
Or
Or
Preferably, the S5 to image segmentation and analyze include according to demand the image after gray processing is split and incite somebody to action
The purpose image being divided into is identified.
The invention also discloses a kind of image analysis systems, including：
Acquisition module, for obtaining pending image；
Preprocessing module pre-processes image；
RGB processing modules, for carrying out RGB color processing to image and generating color vector matrix；
Processing module carries out gray processing and binaryzation to image；
Respond module for segmentation object image and is analyzed, and respond module includes image segmentation unit, image comparing unit
And image identification unit；And
Main control MCU；
Wherein, acquisition module and RGB processing modules, the processing module difference is electrically connected in the preprocessing module
It is electrically connected RGB processing modules and respond module, the preprocessing module, RGB processing modules and processing module electrically connects respectively
Main control MCU is connect, described image cutting unit is electrically connected main control MCU and processing module, and described image comparing unit is electrically connected
Image segmentation unit, preprocessing module and main control MCU, described image recognition unit are electrically connected image comparing unit and master control
MCU。
Preferably, the acquisition module includes one kind in usb interface unit, wireless transmission unit and network download unit
Or it is a variety of, the preprocessing module includes pixel acquisition unit and noise reduction unit, and pixel acquisition unit and noise reduction unit are electric respectively
Property connection acquisition module be used to carry out pixel size reading to the image information of acquisition and noise reduction process, noise reduction list carried out to image
Member is electrically connected main control MCU and image comparing unit for the comparison before and after image noise reduction and image procossing.
Preferably, the RGB processing modules include color processing unit, matrix generation unit and numerical value reading unit, coloured silk
Color processing unit is electrically connected noise reduction unit and main control MCU is used to carry out RGB color processing to the image after noise reduction, and matrix generates
Unit is electrically connected pixel acquisition unit, color processing unit and main control MCU are used for RGB color treated image according to picture
Vegetarian refreshments and image aberration establish color vector matrix, and numerical value reading unit is electrically connected matrix generation unit for obtaining image
Rgb value.
Preferably, the processing module includes gray processing unit and binarization unit, and gray processing unit is electrically connected master control
MCU, color processing unit and numerical value reading unit are used to carry out gray processing according to primary colors numerical value to RGB treated images, and two
Main control MCU is electrically connected in value unit and gray processing unit is used to carry out binaryzation, binaryzation list according to gray value of image
First electric connection figure cutting unit to image before and after the processing for being carried out at the same time Target Segmentation.
Compared with prior art, the beneficial effects of the invention are as follows：
1) present invention carries out primary colors analysis by RGB color treatment technology to image, and color is generated to the image after analysis
Vector matrix, subsequent analysis are based on color vector matrix progress, reduce the power consumption and step of image analysis method and system,
Improve image analysis efficiency；
2) present invention is compared point after being split to the image after binaryzation and gray processing by image segmentation unit
Analysis evades the image data information loss caused by segmentation post-processing is analyzed again and the problem of analysis mistake is caused to occur, realizes and scheme
As the raising of analysis precision.
Description of the drawings
Fig. 1 is the flow chart of image analysis method of the present invention；
Fig. 2 is the flow diagram of image analysis system of the present invention；
Fig. 3 is the structure diagram of image analysis system of the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments 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.
Please refer to Fig.1-3
As shown in Figure 1, a kind of image analysis method, this approach includes the following steps：
S1, acquisition image is inputted by the external world.
S2, image is pre-processed, the pretreatment to image includes carrying out noise reduction process and analysis pixel to image.
S3, RGB color processing generation color vector matrix is carried out to image, color is generated to the RGB color processing of image
Vector matrix includes the rgb value for carrying out the processing of RGB primary colors to image and defining each pixel of image according to image aberration, will
Rgb value generates color vector matrix.
S4, by image gray processing and binary conversion treatment, the value after the gray processing of image is carried out according to following computational algorithm
Processing：
RAfter gray processing=GAfter gray processing=BAfter gray processing=RBefore gray processing×0.3+GBefore gray processing×0.59+BBefore gray processing× 0.11,
The binary conversion treatment of image is carried out according to the comparison of value and threshold value after gray processing, the threshold size is according to gray scale
The average value of each pixel gray value is calculated after change, and the computational algorithm is as follows：
Or
Or
S5, processing is split to the image after binaryzation and is analyzed, to image segmentation and analyzed including right according to demand
Image after gray processing is split and identification is compared in the purpose image being divided into.
As shown in Fig. 2, the invention also discloses a kind of image analysis systems, including：
Acquisition module, for obtaining pending image；
Preprocessing module pre-processes image；
RGB processing modules, for carrying out RGB color processing to image and generating color vector matrix；
Processing module carries out gray processing and binaryzation to image；
Respond module for segmentation object image and is analyzed, and respond module includes image segmentation unit, image comparing unit
And image identification unit；And
Main control MCU；
Wherein, acquisition module and RGB processing modules, the processing module difference is electrically connected in the preprocessing module
It is electrically connected RGB processing modules and respond module, the preprocessing module, RGB processing modules and processing module electrically connects respectively
Main control MCU is connect, described image cutting unit is electrically connected main control MCU and processing module, and described image comparing unit is electrically connected
Image segmentation unit, preprocessing module and main control MCU, described image recognition unit are electrically connected image comparing unit and master control
MCU。
As shown in figure 3, image comparing unit is electrically connected image segmentation unit and main control MCU for comparing segmentation post-processing
Front and back image, image identification unit is electrically connected image comparing unit and main control MCU is used to describe target according to comparison result
Information.
Acquisition module include it is one or more in usb interface unit, wireless transmission unit and network download unit, it is described
Preprocessing module includes pixel acquisition unit and noise reduction unit, and acquisition mould is electrically connected in pixel acquisition unit and noise reduction unit
Block is used to carry out pixel size reading to the image information of acquisition and carries out noise reduction process to image, and noise reduction unit is electrically connected master
MCU and image comparing unit are controlled for the comparison before and after image noise reduction and image procossing.
RGB processing modules include color processing unit, matrix generation unit and numerical value reading unit, color processing unit electricity
Property connection noise reduction unit and main control MCU be used for after noise reduction image carry out RGB color processing, matrix generation unit be electrically connected
Pixel acquisition unit, color processing unit and main control MCU are used for RGB color treated image according to pixel and pattern colour
Difference establishes color vector matrix, and numerical value reading unit is electrically connected the rgb value that matrix generation unit is used to obtain image.
Processing module includes gray processing unit and binarization unit, and gray processing unit is electrically connected main control MCU, color processing
Unit and numerical value reading unit are used for that treated that image carries out gray processing, binarization unit difference according to primary colors numerical value to RGB
It is electrically connected main control MCU and gray processing unit is used to carry out binaryzation according to gray value of image, binarization unit is electrically connected figure
Cutting unit to image before and after the processing for being carried out at the same time Target Segmentation.
Primary colors analysis is carried out to image by RGB color treatment technology, color vector matrix is generated to the image after analysis,
Subsequent analysis is based on color vector matrix progress, reduces the power consumption and step of image analysis method and system, improves figure
As analysis efficiency.And be compared after being split to the image after binaryzation and gray processing by image segmentation unit,
Artwork after treated image and noise reduction is compared, it is ensured that treated image and artwork are in and agree to analysis layer
Face reduces error rate, evades the image data information caused by segmentation post-processing is analyzed again and loses the problem for causing analysis mistake
Occur, realizes the raising of image analysis precision.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
Understanding without departing from the principles and spirit of the present invention can carry out these embodiments a variety of variations, modification, replace
And modification, the scope of the present invention is defined by the appended.
Claims (9)
1. a kind of image analysis method, which is characterized in that this approach includes the following steps：
S1, acquisition image is inputted by the external world；
S2, image is pre-processed；
S3, RGB color processing generation color vector matrix is carried out to image；
S4, by image gray processing and binary conversion treatment；
S5, processing is split to the image after binaryzation and is analyzed.
2. a kind of image analysis method according to claim 1, which is characterized in that the S2 includes to the pretreatment of image
Noise reduction process and analysis pixel are carried out to image.
3. a kind of image analysis method according to claim 1, which is characterized in that the S3 to the RGB color of image at
It includes carrying out the processing of RGB primary colors to image and defining each pixel of image according to image aberration that reason, which generates color vector matrix,
Rgb value, by rgb value generate color vector matrix.
4. a kind of image analysis method according to claim 1, which is characterized in that after the S4 is to the gray processing of image
Value is handled according to following computational algorithm：
RAfter gray processing=GAfter gray processing=BAfter gray processing=RBefore gray processing×0.3+GBefore gray processing×0.59+BBefore gray processing× 0.11,
The S4 carries out the binary conversion treatment of image according to the comparison of value and threshold value after gray processing, and the threshold size is according to ash
The average value of each pixel gray value is calculated after degreeization, and the computational algorithm is as follows：
Or
Or
5. a kind of image analysis method according to claim 1, which is characterized in that the S5 is to image segmentation and analysis bag
It includes and the image after gray processing is split according to demand and the purpose image being divided into is identified.
6. a kind of image analysis system, which is characterized in that including：
Acquisition module, for obtaining pending image；
Preprocessing module pre-processes image；
RGB processing modules, for carrying out RGB color processing to image and generating color vector matrix；
Processing module carries out gray processing and binaryzation to image；
Respond module for segmentation object image and is analyzed, and respond module includes image segmentation unit, image comparing unit and figure
As recognition unit；And
Main control MCU；
Wherein, acquisition module and RGB processing modules is electrically connected in the preprocessing module, and the processing module difference is electrical
Master is electrically connected in connection RGB processing modules and respond module, the preprocessing module, RGB processing modules and processing module
MCU is controlled, described image cutting unit is electrically connected main control MCU and processing module, and described image comparing unit is electrically connected image
Cutting unit, preprocessing module and main control MCU, described image recognition unit are electrically connected image comparing unit and main control MCU.
7. a kind of image analysis system according to claim 6, which is characterized in that the acquisition module includes USB interface
One or more in unit, wireless transmission unit and network download unit, the preprocessing module includes pixel acquisition unit
And acquisition module is electrically connected for the image information progress to acquisition in noise reduction unit, pixel acquisition unit and noise reduction unit
Pixel size reads and carries out noise reduction process to image, and noise reduction unit is electrically connected main control MCU and image comparing unit for scheming
As the comparison before and after noise reduction and image procossing.
8. a kind of image analysis system according to claim 6, which is characterized in that the RGB processing modules include colour
Processing unit, matrix generation unit and numerical value reading unit, color processing unit is electrically connected noise reduction unit and main control MCU is used for
To after noise reduction image carry out RGB color processing, matrix generation unit be electrically connected pixel acquisition unit, color processing unit and
Main control MCU is used to RGB color treated image establishing color vector matrix according to pixel and image aberration, and numerical value is read
Unit is electrically connected the rgb value that matrix generation unit is used to obtain image.
9. a kind of image analysis system according to claim 6, which is characterized in that the processing module includes gray processing list
Member and binarization unit, gray processing unit are electrically connected main control MCU, color processing unit and numerical value reading unit and are used for RGB
Treated, and image carries out gray processing according to primary colors numerical value, and main control MCU and gray processing unit is electrically connected in binarization unit
For carrying out binaryzation according to gray value of image, binarization unit is electrically connected figure cutting unit and is used for image before and after the processing
It is carried out at the same time Target Segmentation.
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