CN106960224A - " Tujia " picture weaving in silk organization type decision method, device and electronic equipment - Google Patents
" Tujia " picture weaving in silk organization type decision method, device and electronic equipment Download PDFInfo
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Abstract
The present invention provides a kind of " Tujia " picture weaving in silk organization type decision method, device and electronic equipment, for judging " Tujia " picture weaving in silk organization type.The " Tujia " picture weaving in silk organization type decision method includes：The image of picture-weaving in silk tissue to be identified is pre-processed, gray-scale map needed for generation.Gray-scale map is designated as the first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray level co-occurrence matrixes respectively in the normalized gray level co-occurrence matrixes in 0 °, 45 °, 90 ° and 135 ° direction needed for calculating.According to the contrast of the first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray level co-occurrence matrixes, the type of picture-weaving in silk tissue to be identified is judged." Tujia " picture weaving in silk organization type is judged using the " Tujia " picture weaving in silk organization type decision method, compared to manual identified, fast with speed, low cost is affected by human factors smaller, the characteristics of accuracy rate is high, can be widely used for industrial identification.
Description
Technical field
The present invention relates to technical field of image processing, in particular to a kind of " Tujia " picture weaving in silk organization type decision method,
Device and electronic equipment.
Background technology
" Tujia " picture weaving in silk is among the people to be referred to as " turk ", and Tujia's language is referred to as " Tujia brocade ", and history is of long standing and well established.Its method for weaving
It is that on ancient wooden waist formula machine, the back of the hand soon, hand knits front, chooses to knit using the method for " stimulate the menstrual flow staplings " and form.Xi Lanka
It is general be derived from history culture from Tujia people out, but during development, all melt from technique or grain pattern
Enter the advanced culture factor of various nationalities, carry forward the national characteristics of Chinese nation's diversification.From modern textile angle,
Fabric tissue is made up of plain weave, three kinds of elementary organizations of twill and satin weave.Tujia brocade has the fabric structure of complexity, but base
Originally changed from plain weave and twill Liang Zhong elementary organizations.And in current " Tujia " picture weaving in silk industry, generally rely on and manually enter
The identification of row picture-weaving in silk tissue, recognition result is easily influenceed by human factor such as operator is tired out, careless etc., and reliability is relatively low, and effect
Rate is extremely inefficient.
The content of the invention
In view of this, it is an object of the invention to provide a kind of " Tujia " picture weaving in silk organization type decision method, device and electronics
Equipment, to solve the above problems.
To achieve the above object, the present invention provides following technical scheme：
A kind of " Tujia " picture weaving in silk organization type decision method, methods described includes：
The image of picture-weaving in silk tissue to be identified is pre-processed, gray-scale map needed for generation；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 0 ° of direction, the first gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 45 ° of directions, the second gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 90 ° of directions, the 3rd gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 135 ° of directions, the 4th gray scale symbiosis square is designated as
Battle array；
According to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray scale
The contrast of co-occurrence matrix, judges the type of the picture-weaving in silk tissue to be identified.
Alternatively, the image to picture-weaving in silk tissue to be identified is pre-processed, and is included needed for generation the step of gray-scale map：
Gray processing is carried out to the image of the picture-weaving in silk tissue to be identified, gray-scale map is generated；
Medium filtering is carried out to the image of the picture-weaving in silk tissue to be identified of gray processing, filtered gray-scale map is obtained；
Binary conversion treatment, gray-scale map needed for generation are carried out to the filtered gray-scale map.
Alternatively, it is described according to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes
Include with the contrast of the 4th gray level co-occurrence matrixes, the step of the type for judging the picture-weaving in silk tissue to be identified：
The contrast of first gray level co-occurrence matrixes is calculated, the first contrast is designated as；
The contrast of second gray level co-occurrence matrixes is calculated, the second contrast is designated as；
The contrast of the 3rd gray level co-occurrence matrixes is calculated, the 3rd contrast is designated as；
The contrast of the 4th gray level co-occurrence matrixes is calculated, the 4th contrast is designated as；
3rd contrast and first contrast, the second contrast and the 4th contrast are made the difference respectively, obtained
Three differences；
If three differences have one to be more than or equal to 0, judge the type of the picture-weaving in silk tissue to be identified as twill；
If three differences are respectively less than 0, first contrast, the second contrast, the 3rd contrast and are calculated
The average and standard deviation of four contrasts, if the difference of the average and the 3rd contrast is less than the standard deviation, judge
The type of the picture-weaving in silk tissue to be identified is twill；
If three differences are respectively less than 0, first contrast, the second contrast, the 3rd contrast and are calculated
The average and standard deviation of four contrasts, if the difference of the average and the 3rd contrast is more than or equal to the standard deviation,
Then judge the type of the picture-weaving in silk tissue to be identified as plain weave.
Alternatively, the step of image to the picture-weaving in silk tissue to be identified carries out gray processing, generation gray-scale map includes：
The average value of tri- components of R, G, B of each pixel in the image of the picture-weaving in silk tissue to be identified is obtained, by this
Average value assigns the gray value of the pixel.
Alternatively, it is described that binary conversion treatment is carried out to the filtered gray-scale map, wrapped needed for generation the step of gray-scale map
Include：
Binary-state threshold is found using histogram method.
Alternatively, methods described also includes：
Gather the image that weft yarn keeps the picture-weaving in silk tissue to be identified of level.
A kind of " Tujia " picture weaving in silk organization type decision maker, including：
Pretreatment module, is pre-processed for the image to picture-weaving in silk tissue to be identified, gray-scale map needed for generation；
Gray level co-occurrence matrixes computing module, for calculating normalized gray scale symbiosis of the required gray-scale map in 0 ° of direction
Matrix is simultaneously designated as the first gray level co-occurrence matrixes, calculates normalized gray level co-occurrence matrixes of the required gray-scale map in 45 ° of directions
And the second gray level co-occurrence matrixes are designated as, the required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 90 ° of directions and is remembered
For the 3rd gray level co-occurrence matrixes, and calculating gray-scale map needed for described are in the normalized gray level co-occurrence matrixes in 135 ° of directions and remember
For the 4th gray level co-occurrence matrixes；
Determination module, for according to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray scale symbiosis square
The contrast of battle array and the 4th gray level co-occurrence matrixes, judges the type of the picture-weaving in silk tissue to be identified.
Alternatively, the pretreatment module includes：
Gray processing submodule, carries out gray processing for the image to the picture-weaving in silk tissue to be identified, generates gray-scale map；
Submodule is filtered, the image for the picture-weaving in silk tissue to be identified to gray processing carries out medium filtering, obtains after filtering
Gray-scale map；
Binaryzation submodule, for carrying out binary conversion treatment, gray-scale map needed for generation to the filtered gray-scale map.
Alternatively, the determination module includes：
Contrast calculating sub module, for calculating the contrast of first gray level co-occurrence matrixes and being designated as the first contrast
Degree, calculates the contrast of second gray level co-occurrence matrixes and is designated as the second contrast, calculate the 3rd gray level co-occurrence matrixes
Contrast and be designated as the 3rd contrast, and calculate the contrast of the 4th gray level co-occurrence matrixes and be designated as the 4th contrast
Degree；
Contrast difference calculating sub module, for by the 3rd contrast and first contrast, the second contrast
Made the difference respectively with the 4th contrast, obtain three differences；
Twill decision sub-module, for three differences have one be more than or equal to 0 when, judge described to be identified knit
The type of brocade tissue is twill；
The twill decision sub-module, is additionally operable to when three differences are respectively less than 0, calculating first contrast,
The average and standard deviation of second contrast, the 3rd contrast and the 4th contrast, in the average and the 3rd contrast
When difference is less than the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as twill；
Plain weave decision sub-module, for when three differences are respectively less than 0, calculate first contrast, second pair
It is big in the difference of the average and the 3rd contrast than the average and standard deviation of degree, the 3rd contrast and the 4th contrast
When the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as plain weave.
A kind of electronic equipment, including processor and memory and storage are on a memory and the meter that can run on a processor
Calculation machine program, following steps are realized described in the computing device during computer program：
The image of picture-weaving in silk tissue to be identified is pre-processed, gray-scale map needed for generation；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 0 ° of direction, the first gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 45 ° of directions, the second gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 90 ° of directions, the 3rd gray scale symbiosis square is designated as
Battle array；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 135 ° of directions, the 4th gray scale symbiosis square is designated as
Battle array；
According to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray scale
The contrast of co-occurrence matrix, judges the type of the picture-weaving in silk tissue to be identified.
" Tujia " picture weaving in silk organization type decision method provided in an embodiment of the present invention, device and electronic equipment, at image
Reason, according to the contrast of gray level co-occurrence matrixes, judges the type of " Tujia " picture weaving in silk tissue, fast with speed compared to manual identified,
Low cost, is affected by human factors smaller, the characteristics of accuracy rate is high, can be widely used for industrial identification.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be attached to what is used needed for embodiment
Figure is briefly described.It should be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore it is not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
The block diagram for a kind of electronic equipment that Fig. 1 provides for present pre-ferred embodiments.
A kind of flow chart for " Tujia " picture weaving in silk organization type decision method that Fig. 2 provides for present pre-ferred embodiments.
Fig. 3 is the flow chart of step S220 sub-step shown in Fig. 2 in an embodiment.
Fig. 3-1 be an embodiment in plain weave sample carry out gray processing after figure.
Fig. 3-2 be an embodiment in twill sample carry out gray processing after figure.
Fig. 3-3 be an embodiment in Fig. 3-1 carry out medium filtering after figure.
Fig. 3-4 be an embodiment in Fig. 3-2 carry out medium filtering after figure.
Fig. 3-5 be an embodiment in enter the figure after column hisgram binaryzation to Fig. 3-3.
Fig. 3-6 be an embodiment in enter the figure after column hisgram binaryzation to Fig. 3-4.
Fig. 4-1 is the flow chart of step S270 sub-step shown in Fig. 2 in an embodiment.
The flow chart for another sub-step that Fig. 4-2 is step S270 shown in Fig. 2 in an embodiment.
The flow chart for another sub-step that Fig. 4-3 is step S270 shown in Fig. 2 in an embodiment.
A kind of functional module frame for " Tujia " picture weaving in silk organization type decision maker that Fig. 5 provides for present pre-ferred embodiments
Figure.
The schematic diagram for the submodule that Fig. 6 includes for the pretreatment module shown in Fig. 5 in an embodiment.
The schematic diagram for the submodule that Fig. 7 includes for the determination module shown in Fig. 5 in an embodiment.
Icon：100- electronic equipments；110- memories；120- processors；130- mixed-media network modules mixed-medias；200- " Tujia " picture weaving in silk tissues
Type decision device；220- pretreatment modules；230- gray level co-occurrence matrixes computing modules；270- determination modules；221- gray processings
Submodule；223- filters submodule；225- binaryzation submodules；271- contrast calculating sub modules；275- contrast difference meters
Operator module；276- twill decision sub-modules；278- plain weave decision sub-modules.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described.Obviously, described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.It is logical
Often the component of the embodiment of the present invention here described and illustrated in accompanying drawing can be arranged and designed with a variety of configurations.
Therefore, the detailed description of embodiments of the invention below to providing in the accompanying drawings is not intended to limit claimed
The scope of the present invention, but be merely representative of the present invention selected embodiment.Based on embodiments of the invention, people in the art
The every other embodiment that member is obtained on the premise of creative work is not made, belongs to the scope of protection of the invention.
It should be noted that：Similar label and letter represents similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined in individual accompanying drawing, then it further need not be defined and explained in subsequent accompanying drawing.In description of the invention
In, term " first ", " second ", " the 3rd ", " the 4th " etc. are only used for distinguishing description, and it is not intended that being or implying relative
Importance.
Referring to Fig. 1, being the block diagram for a kind of electronic equipment 100 that present pre-ferred embodiments are provided.The present invention
Electronic equipment 100 in embodiment can possess the equipment of data-handling capacity for computer etc..As shown in figure 1, electronic equipment
100 include：Memory 110, processor 120 and mixed-media network modules mixed-media 130.
The memory 110, processor 120 and mixed-media network modules mixed-media 130 are directly or indirectly electrically connected with each other, with
Realize the transmission or interaction of data.For example, these elements each other can be real by one or more communication bus or signal wire
Now it is electrically connected with.Memory 110 can be stored in the storage including at least one in the form of software or firmware (firmware)
Software function module in device 110, the processor 120 is stored in software program and mould in memory 110 by operation
" Tujia " picture weaving in silk organization type decision maker 200 in block, such as embodiment of the present invention, so as to perform various function application and data
Processing, that is, realize the " Tujia " picture weaving in silk organization type decision method in the embodiment of the present invention.
Wherein, the memory 10 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only storage (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 10 is used for storage program, and processor 20 performs described program after execute instruction is received, and the present invention is implemented
The method of flow definition disclosed in example any embodiment can apply in processor 20, or be realized by processor 20.
Processor 20 can be a kind of IC chip, the disposal ability with signal.Processor 20 can be general
Processor, including central processing unit (Central Processing Unit, CPU), network processing unit (Network
Processor, NP) etc..Processor 20 can also be digital signal processor (DSP), application specific integrated circuit (ASIC), it is ready-made can
Program gate array (FPGA) and other PLDs, discrete gate or transistor logic, discrete hardware components.
It can realize or perform disclosed each method, step and the logic diagram in the embodiment of the present invention.General processor can be
Microprocessor or the processor 20 can also be any conventional processors etc..
Mixed-media network modules mixed-media 130 is used for the communication connection set up by network between electronic equipment 100 and external communications terminals, real
The transmitting-receiving operation of existing network signal and data.Above-mentioned network signal may include wireless signal or wire signal.
It is appreciated that the structure shown in Fig. 1 be only signal, electronic equipment 100 may also include it is more more than shown in Fig. 1 or
Less component, or with the configuration different from shown in Fig. 1.Each component shown in Fig. 1 can using hardware, software or its
Combination is realized.
Referring to Fig. 2, being a kind of flow for " Tujia " picture weaving in silk organization type decision method that present pre-ferred embodiments are provided
Figure.Method and step defined in the relevant flow of methods described can be realized by the processor 120.Below will be to shown in Fig. 2
Idiographic flow be described in detail.
Step S210, collection weft yarn keeps the image of the picture-weaving in silk tissue to be identified of level.
Wherein, the picture-weaving in silk to be identified is organized as " Tujia " picture weaving in silk tissue to be identified.Collection weft yarn holding level wait know
The image of other picture-weaving in silk tissue, can be the image for first gathering picture-weaving in silk tissue to be identified, then rotate the picture-weaving in silk tissue to be identified
Image, make its weft yarn level or, first rotate the image of the picture-weaving in silk tissue to be identified, make its weft yarn holding level, then
Collection.The purpose of this step is that contrast plain weave and twill are easy to manual identified, to verify soil provided in an embodiment of the present invention
The correctness of family's picture-weaving in silk organization type decision method, device and electronic equipment 100.Thus, step S210 is optional realization side
Case, when actually implementing, can not perform step S210, directly perform step S220.
Step S220, is pre-processed to the image of picture-weaving in silk tissue to be identified, gray-scale map needed for generation.
Referring to Fig. 3, step S220 can include sub-step S221, sub-step S223 and sub-step S225.
Sub-step S221, carries out gray processing to the image of the picture-weaving in silk tissue to be identified, generates gray-scale map.
The image of the picture-weaving in silk tissue to be identified is coloured image, is had much to the method that coloured image carries out gray processing.
For example, for RGB image, gray processing method main important method, maximum value process, mean value method and weighted mean method.Component method,
Some component of tri- components of R, G, B is used as the gray value of the point.It is maximum in maximum value process, i.e. tri- components of R, G, B
It is worth the gray value as the point.Mean value method, the i.e. average value of tri- components of R, G, B as the point gray value.Weighted average
Method, i.e. tri- components of R, G, B are multiplied by corresponding weight coefficient and summed again respectively.For HSV and HLS images, RGB can be first converted to
Image, then carry out gray processing.For YUV image, brightness Y can be regard as the gray value of the point, wherein brightness Y=0.3R+
0.59G+0.11B。
Alternatively, in the present embodiment, sub-step S221 carries out gray processing using mean value method, that is, obtains described to be identified
The average value of tri- components of R, G, B of each pixel, the average value is assigned the ash of the pixel in the image of picture-weaving in silk tissue
Angle value.The image of picture-weaving in silk tissue to be identified after gray processing is as shown in Fig. 3-1 and Fig. 3-2.Wherein, Fig. 3-1 is represented to plain weave sample
Figure after this progress gray processing, Fig. 3-2 represents to carry out twill sample in the figure after gray processing.
Sub-step S223, carries out medium filtering to the image of the picture-weaving in silk tissue to be identified of gray processing, obtains filtered ash
Degree figure.
Medium filtering is effectively to suppress the nonlinear signal processing technology of noise based on a kind of of sequencing statistical theory, in
The general principle of value filtering is the value any in digital picture or Serial No. with each point value in a neighborhood of the point
Value is replaced, the actual value for making the pixel value of surrounding close, so as to eliminate isolated noise spot.Filtered gray-scale map such as Fig. 3-3
With shown in Fig. 3-4.Wherein, Fig. 3-3 represents to carry out Fig. 3-1 in the figure after medium filtering, and Fig. 3-4 represents to carry out intermediate value to Fig. 3-2
Filtered figure.
Sub-step S225, binary conversion treatment, gray-scale map needed for generation are carried out to the filtered gray-scale map.
The binaryzation of image, is exactly set to 0 or 255, that is, will entirely scheme by the gray value of the pixel on image
Significantly there was only black and white visual effect as showing.Because warp thread is usually black, thus directly it can pass through binaryzation
To carry out image enhaucament.Binary-state threshold is found using histogram method.The method of binaryzation has a lot, alternatively in the present embodiment
In, binary-state threshold is found using histogram method.Histogram is the important speciality of image, histogram method selection binary-state threshold
Two highest peaks of image are mainly found, then the peak valley lowest part in threshold value value between the two peaks.Using Nogata
After figure binaryzation, the required gray-scale map of generation is as shown in Fig. 3-5 and Fig. 3-6.Wherein, Fig. 3-5 represents to enter column hisgram to Fig. 3-3
Figure after binaryzation, Fig. 3-6 represents the figure entered to Fig. 3-4 after column hisgram binaryzation.
Step S230, calculates normalized gray level co-occurrence matrixes of the required gray-scale map in 0 ° of direction, is designated as the first ash
Spend co-occurrence matrix.
Step S240, calculates normalized gray level co-occurrence matrixes of the required gray-scale map in 45 ° of directions, is designated as the second ash
Spend co-occurrence matrix.
Step S250, calculates normalized gray level co-occurrence matrixes of the required gray-scale map in 90 ° of directions, is designated as the 3rd ash
Spend co-occurrence matrix.
Step S260, calculates the required gray-scale map in the normalized gray level co-occurrence matrixes in 135 ° of directions, is designated as the 4th
Gray level co-occurrence matrixes.
According to the texture features of " Tujia " picture weaving in silk tissue, in step S230, step S240, step S250 and step S260,
Gray-scale map needed for calculating can be 8 in the step-length of the normalized gray level co-occurrence matrixes in 0 °, 45 °, 90 ° and 135 ° direction.
Step S270, according to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and
The contrast of 4th gray level co-occurrence matrixes, judges the type of the picture-weaving in silk tissue to be identified.
Step S270 includes sub-step S271, sub-step S272, sub-step S273, sub-step S274, sub-step S275, son
Step S276, sub-step S277 and sub-step S278.
Sub-step S271, calculates the contrast of first gray level co-occurrence matrixes, is designated as the first contrast.
Sub-step S272, calculates the contrast of second gray level co-occurrence matrixes, is designated as the second contrast.
Sub-step S273, calculates the contrast of the 3rd gray level co-occurrence matrixes, is designated as the 3rd contrast.
Sub-step S274, calculates the contrast of the 4th gray level co-occurrence matrixes, is designated as the 4th contrast.
Calculating the first gray scale symbiosis being related in sub-step S271, sub-step S272, sub-step S273 and sub-step S274
Matrix, the second gray level co-occurrence matrixes, the contrast computing formula of the 3rd gray level co-occurrence matrixes and the 4th gray level co-occurrence matrixes are：
Sub-step S275, by the 3rd contrast and first contrast, the second contrast and the 4th contrast point
Do not make the difference, obtain three differences, whether relatively more described three differences are respectively less than 0.
If three differences have one to be more than or equal to 0, sub-step S276 is performed, as shown in Fig. 4-1.If described three
Individual difference is respectively less than 0, then sub-step S277 is performed, as shown in Fig. 4-2 and Fig. 4-3.
Sub-step S276, judges the type of the picture-weaving in silk tissue to be identified as twill.
Sub-step S277, calculates the average of first contrast, the second contrast, the 3rd contrast and the 4th contrast
And standard deviation, whether compare the average with the difference of the 3rd contrast less than the standard deviation.
If the difference of the average and the 3rd contrast is less than the standard deviation, step S276, such as Fig. 4-2 are performed
It is shown.If the difference of the average and the 3rd contrast is more than or equal to the standard deviation, sub-step S278 is performed, such as
Shown in Fig. 4-3.
Sub-step S278, judges the type of the picture-weaving in silk tissue to be identified as plain weave.
As shown in the table, following table is Fig. 3-5 and Fig. 3-6 respectively through step S230, step S240, step S250 steps S260
The result table for being calculated and being judged with step S270.
On the basis of the above, as shown in figure 5, the embodiment of the present invention also provides a kind of " Tujia " picture weaving in silk organization type decision maker
200, including：Pretreatment module 220, gray level co-occurrence matrixes computing module 230 and determination module 270.
Wherein, pretreatment module 220 is used to pre-process the image of picture-weaving in silk tissue to be identified, gray scale needed for generation
Figure.Because pretreatment module 220 is similar with the realization principle of step S220 in Fig. 2, step S220 can include sub-step S221,
Sub-step S223 and sub-step S225, accordingly, referring to Fig. 6, the pretreatment module 220 includes：Gray processing submodule
221st, filtering submodule 223 and binaryzation submodule 225.
Gray processing submodule 221 is used to carry out gray processing to the image of the picture-weaving in silk tissue to be identified, generates gray-scale map.Ash
Spend beggar's module 221 similar with the realization principle of sub-step S221 in Fig. 3, therefore do not make more explanations herein.
Filtering submodule 223 is used to carry out medium filtering to the image of the picture-weaving in silk tissue to be identified of gray processing, is filtered
Gray-scale map afterwards.Filter submodule 223 similar with the realization principle of sub-step S223 in Fig. 3, therefore do not make more explanations herein.
Binaryzation submodule 225 is used to carry out binary conversion treatment, gray-scale map needed for generation to the filtered gray-scale map.
Binaryzation submodule 225 is similar with the realization principle of sub-step S225 in Fig. 3, therefore does not make more explanations herein.
Gray level co-occurrence matrixes computing module 230 is total to for calculating normalized gray scale of the required gray-scale map in 0 ° of direction
Raw matrix is simultaneously designated as the first gray level co-occurrence matrixes, calculates normalized gray scale symbiosis square of the required gray-scale map in 45 ° of directions
Battle array is simultaneously designated as the second gray level co-occurrence matrixes, calculate it is described needed for gray-scale map 90 ° of directions normalized gray level co-occurrence matrixes simultaneously
Be designated as the 3rd gray level co-occurrence matrixes, and calculate it is described needed for gray-scale map 135 ° of directions normalized gray level co-occurrence matrixes simultaneously
It is designated as the 4th gray level co-occurrence matrixes.Step S230, step S240, step S250 in gray level co-occurrence matrixes computing module 230 and Fig. 2
It is similar with step S260 realization principle, therefore do not make more explanations herein.
Determination module 270 is used for according to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray scale symbiosis
The contrast of matrix and the 4th gray level co-occurrence matrixes, judges the type of the picture-weaving in silk tissue to be identified.Determination module 270 and Fig. 2
Middle step S270 realization principle is similar, as shown in fig. 7, the determination module 270 includes contrast calculating sub module 271, right
Than degree mathematic interpolation submodule 275, twill decision sub-module 276 and plain weave decision sub-module 278.
Contrast calculating sub module 271 is used to calculate the contrast of first gray level co-occurrence matrixes and is designated as the first contrast
Degree, calculates the contrast of second gray level co-occurrence matrixes and is designated as the second contrast, calculate the 3rd gray level co-occurrence matrixes
Contrast and be designated as the 3rd contrast, and calculate the contrast of the 4th gray level co-occurrence matrixes and be designated as the 4th contrast
Degree.Sub-step S271, sub-step S272, sub-step S273 and son in contrast calculating sub module 271 and Fig. 4-1,4-2 and 4-3
Step S274 realization principle is similar, therefore does not make more explanations herein.
Contrast difference calculating sub module 275 is used for the 3rd contrast and first contrast, the 3rd contrast
Degree and the 4th contrast make the difference respectively, obtain three differences, and whether relatively more described three differences are respectively less than 0.Contrast difference meter
Operator module 275 is similar with the realization principle of middle sub-step S275 in Fig. 4-1,4-2 and 4-3, therefore does not make more explanations herein.
Twill decision sub-module 276 is used to, when three differences have one more than or equal to 0, judge described to be identified
The type of picture-weaving in silk tissue is twill.The twill decision sub-module 276, is additionally operable to when three differences are respectively less than 0, calculates
First contrast, the second contrast, the average and standard deviation of the 3rd contrast and the 4th contrast, in the average and institute
When the difference for stating the 3rd contrast is less than the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as twill.Twill is sentenced
Stator modules 276 are similar with the realization principle of sub-step S277 in Fig. 4-2 with sub-step S276 in Fig. 4-1, therefore do not make herein
More explanations.
Plain weave decision sub-module 278 is used for when three differences are respectively less than 0, calculates first contrast, second
The average and standard deviation of contrast, the 3rd contrast and the 4th contrast, in the average and the difference of the 3rd contrast
During more than or equal to the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as plain weave.The He of plain weave decision sub-module 278
Sub-step S278 realization principle is similar in Fig. 4-3, therefore does not make more explanations herein.
" Tujia " picture weaving in silk organization type decision method provided in an embodiment of the present invention, device and electronic equipment 100, pass through image
Processing, according to the contrast of gray level co-occurrence matrixes, judges the type of " Tujia " picture weaving in silk tissue, compared to manual identified, with speed
It hurry up, low cost is affected by human factors smaller, the characteristics of accuracy rate is high, can be widely used for industrial identification.
In several embodiments that the embodiment of the present invention is provided, it should be understood that disclosed apparatus and method, also may be used
To realize by another way.Apparatus and method embodiment described above is only schematical, for example, in accompanying drawing
Flow chart and block diagram show the device of multiple embodiments according to the present invention, the possibility of method and computer program product is realized
Architectural framework, function and operation.At this point, each square frame in flow chart or block diagram can represent module, a program
A part for section or code a, part for the module, program segment or code is used to realize defined patrol comprising one or more
Collect the executable instruction of function.It should also be noted that in some implementations as replacement, the function of being marked in square frame
Can be with different from the order marked in accompanying drawing generation.For example, two continuous square frames can essentially be held substantially in parallel
OK, they can also be performed in the opposite order sometimes, and this is depending on involved function.It is also noted that block diagram and/or
The combination of each square frame in flow chart and the square frame in block diagram and/or flow chart, can use function as defined in execution or dynamic
The special hardware based system made is realized, or can be realized with the combination of specialized hardware and computer instruction.
In addition, each functional module in each embodiment of the invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized using in the form of software function module and is used as independent production marketing or in use, can be with
It is stored in a computer read/write memory medium.Understood based on such, technical scheme is substantially in other words
The part contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are make it that a computer equipment (can be individual
People's computer, various electronic equipments, or network equipment etc.) perform all or part of each of the invention embodiment methods described
Step.And foregoing storage medium includes：It is USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), random
Access memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with Jie of store program codes
Matter.It should be noted that herein, term " comprising ", "comprising" or its any other variant are intended to nonexcludability
Include so that process, method, article or equipment including a series of key elements not only include those key elements, but also
Including other key elements being not expressly set out, or also include for this process, method, article or equipment intrinsic want
Element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that wanted including described
Also there is other identical element in process, method, article or the equipment of element.It the foregoing is only being preferable to carry out for the present invention
Example, is not intended to limit the invention, for a person skilled in the art, the present invention can have various changes and change
Change.Within the spirit and principles of the invention, any modifications, equivalent substitutions and improvements made etc., should be included in the present invention
Protection domain within.
Claims (10)
1. a kind of " Tujia " picture weaving in silk organization type decision method, it is characterised in that methods described includes：
The image of picture-weaving in silk tissue to be identified is pre-processed, gray-scale map needed for generation；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 0 ° of direction, the first gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 45 ° of directions, the second gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 90 ° of directions, the 3rd gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 135 ° of directions, the 4th gray level co-occurrence matrixes are designated as；
According to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray scale symbiosis
The contrast of matrix, judges the type of the picture-weaving in silk tissue to be identified.
2. " Tujia " picture weaving in silk organization type decision method according to claim 1, it is characterised in that described to picture-weaving in silk to be identified
The image of tissue is pre-processed, and is included needed for generation the step of gray-scale map：
Gray processing is carried out to the image of the picture-weaving in silk tissue to be identified, gray-scale map is generated；
Medium filtering is carried out to the image of the picture-weaving in silk tissue to be identified of gray processing, filtered gray-scale map is obtained；
Binary conversion treatment, gray-scale map needed for generation are carried out to the filtered gray-scale map.
3. " Tujia " picture weaving in silk organization type decision method according to claim 2, it is characterised in that described according to described first
Gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the contrast of the 3rd gray level co-occurrence matrixes and the 4th gray level co-occurrence matrixes, judge
The step of type of the picture-weaving in silk tissue to be identified, includes：
The contrast of first gray level co-occurrence matrixes is calculated, the first contrast is designated as；
The contrast of second gray level co-occurrence matrixes is calculated, the second contrast is designated as；
The contrast of the 3rd gray level co-occurrence matrixes is calculated, the 3rd contrast is designated as；
The contrast of the 4th gray level co-occurrence matrixes is calculated, the 4th contrast is designated as；
3rd contrast and first contrast, the second contrast and the 4th contrast are made the difference respectively, three are obtained
Difference；
If three differences have one to be more than or equal to 0, judge the type of the picture-weaving in silk tissue to be identified as twill；
If three differences are respectively less than 0, first contrast, the second contrast, the 3rd contrast and the 4th pair are calculated
Than the average and standard deviation of degree, if the difference of the average and the 3rd contrast is less than the standard deviation, judge described
The type of picture-weaving in silk tissue to be identified is twill；
If three differences are respectively less than 0, first contrast, the second contrast, the 3rd contrast and the 4th pair are calculated
Than the average and standard deviation of degree, if the difference of the average and the 3rd contrast is more than or equal to the standard deviation, sentence
The type of the fixed picture-weaving in silk tissue to be identified is plain weave.
4. " Tujia " picture weaving in silk organization type decision method according to claim 2, it is characterised in that described to described to be identified
The step of image of picture-weaving in silk tissue carries out gray processing, generation gray-scale map includes：
The average value of tri- components of R, G, B of each pixel in the image of the picture-weaving in silk tissue to be identified is obtained, this is averaged
Value assigns the gray value of the pixel.
5. " Tujia " picture weaving in silk organization type decision method according to claim 2, it is characterised in that it is described to the filtering after
Gray-scale map carry out binary conversion treatment, generation needed for gray-scale map the step of include：
Binary-state threshold is found using histogram method.
6. " Tujia " picture weaving in silk organization type decision method according to claim 1, it is characterised in that methods described also includes：
Gather the image that weft yarn keeps the picture-weaving in silk tissue to be identified of level.
7. a kind of " Tujia " picture weaving in silk organization type decision maker, it is characterised in that including：
Pretreatment module, is pre-processed for the image to picture-weaving in silk tissue to be identified, gray-scale map needed for generation；
Gray level co-occurrence matrixes computing module, for calculating normalized gray level co-occurrence matrixes of the required gray-scale map in 0 ° of direction
And the first gray level co-occurrence matrixes are designated as, the required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 45 ° of directions and is remembered
For the second gray level co-occurrence matrixes, calculate it is described needed for gray-scale map 90 ° of directions normalized gray level co-occurrence matrixes and be designated as the
Three gray level co-occurrence matrixes, and calculate it is described needed for gray-scale map 135 ° of directions normalized gray level co-occurrence matrixes and be designated as the
Four gray level co-occurrence matrixes；
Determination module, for according to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and
The contrast of 4th gray level co-occurrence matrixes, judges the type of the picture-weaving in silk tissue to be identified.
8. " Tujia " picture weaving in silk organization type decision maker according to claim 7, it is characterised in that the pretreatment module bag
Include：
Gray processing submodule, carries out gray processing for the image to the picture-weaving in silk tissue to be identified, generates gray-scale map；
Submodule is filtered, the image for the picture-weaving in silk tissue to be identified to gray processing carries out medium filtering, obtains filtered ash
Degree figure；
Binaryzation submodule, for carrying out binary conversion treatment, gray-scale map needed for generation to the filtered gray-scale map.
9. " Tujia " picture weaving in silk organization type decision maker according to claim 8, it is characterised in that the determination module bag
Include：
Contrast calculating sub module, for calculating the contrast of first gray level co-occurrence matrixes and being designated as the first contrast, meter
Calculate the contrast of second gray level co-occurrence matrixes and be designated as the second contrast, calculate the contrast of the 3rd gray level co-occurrence matrixes
Spend and be designated as the 3rd contrast, and calculate the contrast of the 4th gray level co-occurrence matrixes and be designated as the 4th contrast；
Contrast difference calculating sub module, for by the 3rd contrast and first contrast, the second contrast and the
Four contrasts make the difference respectively, obtain three differences；
Twill decision sub-module, for when three differences have one more than or equal to 0, judging the picture-weaving in silk group to be identified
The type knitted is twill；
The twill decision sub-module, is additionally operable to when three differences are respectively less than 0, calculates first contrast, second
The average and standard deviation of contrast, the 3rd contrast and the 4th contrast, in the average and the difference of the 3rd contrast
During less than the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as twill；
Plain weave decision sub-module, for when three differences are respectively less than 0, calculate first contrast, the second contrast,
The average and standard deviation of 3rd contrast and the 4th contrast, are more than or wait with the difference of the 3rd contrast in the average
When the standard deviation, judge the type of the picture-weaving in silk tissue to be identified as plain weave.
10. a kind of electronic equipment, it is characterised in that including processor and memory and store on a memory and can be in processor
The computer program of upper operation, following steps are realized described in the computing device during computer program：
The image of picture-weaving in silk tissue to be identified is pre-processed, gray-scale map needed for generation；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 0 ° of direction, the first gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 45 ° of directions, the second gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 90 ° of directions, the 3rd gray level co-occurrence matrixes are designated as；
The required gray-scale map is calculated in the normalized gray level co-occurrence matrixes in 135 ° of directions, the 4th gray level co-occurrence matrixes are designated as；
According to first gray level co-occurrence matrixes, the second gray level co-occurrence matrixes, the 3rd gray level co-occurrence matrixes and the 4th gray scale symbiosis
The contrast of matrix, judges the type of the picture-weaving in silk tissue to be identified.
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