CN103390080B - A kind of plant disease speckle color simulation method and device - Google Patents

A kind of plant disease speckle color simulation method and device Download PDF

Info

Publication number
CN103390080B
CN103390080B CN201310294388.6A CN201310294388A CN103390080B CN 103390080 B CN103390080 B CN 103390080B CN 201310294388 A CN201310294388 A CN 201310294388A CN 103390080 B CN103390080 B CN 103390080B
Authority
CN
China
Prior art keywords
specular reflectance
scab
reflectance excluded
excluded
texture
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201310294388.6A
Other languages
Chinese (zh)
Other versions
CN103390080A (en
Inventor
陈立平
郭新宇
苗腾
陆声链
温维亮
王传宇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Research Center for Information Technology in Agriculture
Original Assignee
Beijing Research Center for Information Technology in Agriculture
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Research Center for Information Technology in Agriculture filed Critical Beijing Research Center for Information Technology in Agriculture
Priority to CN201310294388.6A priority Critical patent/CN103390080B/en
Publication of CN103390080A publication Critical patent/CN103390080A/en
Application granted granted Critical
Publication of CN103390080B publication Critical patent/CN103390080B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Image Analysis (AREA)
  • Image Generation (AREA)

Abstract

The present invention discloses a kind of plant disease speckle color simulation method: scab Image semantic classification, extracts in scab and accumulates specular reflectance excluded, preserves the image accumulateing in scab and only containing specular reflectance excluded information; The specular reflectance excluded accumulate in image in the scab preserved is classified, the number of record classification; Determine the order that each specular reflectance excluded classified occurs in scab generation process, and each specular reflectance excluded is sorted; Each specular reflectance excluded after sequence is generated scab specular reflectance excluded texture; Determine the specular reflectance excluded of each point of blade. Meanwhile, the invention also discloses a kind of plant disease speckle color simulation device, comprise with lower module: scab image pre-processing module; Specular reflectance excluded sort module; Specular reflectance excluded order module; Scab specular reflectance excluded texture generation module; Blade each point specular reflectance excluded determination module. Use the method for the present invention and module, it is to increase scab color change process with true in the similarity of scab color change process.

Description

A kind of plant disease speckle color simulation method and device
Technical field
The present invention relates to computer graphics, truly feel the field of drafting, the combination of plant behavior simulation in real time, be specifically related to a kind of plant disease speckle color simulation method and device.
Background technology
Computer is played up and is referred to appliance computer figure software, generally comprises two dimension software, three-dimensional software and post-production software etc., in a computer by ready-made object, role etc., by renderer, plays up, reach the effect that we want to see.
In recent years, along with the development of IT application to agriculture technology, the rudimentary knowledge, FAQs and the professional technique method that utilize three-dimensional animation to show in agriculture production for peasant became a kind of important means. It is known that, disease and pest is phenomenon common in agriculture production, but do not have at present good method can truly the generation process of simulation disease and pest and its affect the apparent changing conditions of lower blade, so the apparent change of plant leaf becomes the application that agriculture field is needed badly when describing disease and pest.
Through development for many years, the research that blade plays up aspect makes some progress. Such as the method based on Bidirectional surface diffusion function and the method based on Bidirectional surface reflective function+Bidirectional surface projection functions. But the research major part drawn about the apparent true sense of blade in current research concentrates apparent texture modeling in normal state, and it mostly is the blade surface simulation of fixed time. But the apparent meeting of plant leaf produces significant change under disease and pest factor, there will be change or the cavity of color at blade surface, and whole process is a dynamic process simultaneously, these apparent features are all that existing method is difficult to simulation. Patent of invention [201210227153.0] is identical with the object of this patent, but this patent is a given artificially aging color in process scab color process, and aging color and leaf color are carried out interpolation and obtains result, this kind for the treatment of process has following problem: set suitable aging color more difficult;Carry out, by leaf color and aging color, the true colors that interpolation is difficult to accurately show scab change procedure simultaneously.
Summary of the invention
(1) technical problem solved
It is an object of the invention to overcome prior art can the problem of accurate simulation scab color change process.
(2) technical scheme
The present invention uses following technical scheme:
A kind of plant disease speckle color simulation method, comprises following step:
Scab Image semantic classification, extracts in scab and accumulates specular reflectance excluded, preserves the image accumulateing in scab and only containing specular reflectance excluded information;
The specular reflectance excluded accumulate in image in the scab preserved is classified, the number of record classification;
Determine the order that each specular reflectance excluded classified occurs in scab generation process, and each specular reflectance excluded is sorted;
Each specular reflectance excluded after sequence is generated scab specular reflectance excluded texture;
Determine the specular reflectance excluded of each point of blade.
Preferably, extracting the method accumulateing specular reflectance excluded in scab is that scab area image selected by interactive frame, it may also be useful to the image in this region is carried out illumination reflection and accumulates being separated of specular reflectance excluded with in scab by intensity of illumination threshold method.
Preferably, the method specular reflectance excluded accumulate in scab in image classified is, employing cluster algorithm carries out packet and classifies.
Further, described sorting technique is, obtains the mean value often organizing specular reflectance excluded set, and each cell mean obtained is the specular reflectance excluded eigenwert of the different stage of growth of scab.
Preferably, it is be taking texture image with reference to the interactive method of design carrying out scab position, manually sequence and automatically sequence: when specular reflectance excluded set number is less than or equal to 10, manually sort; When specular reflectance excluded set number is greater than 10, automatically sort.
Further, described auto ordering method is sort according to the size of specular reflectance excluded red component and the ratio of green component, and ratio is more little, and order is more forward, and time disease namely occur is more early.
Preferably, scab specular reflectance excluded texture is a dimension texture, forms scab diffuse-reflectance texture by texel.
Further, the method that described scab specular reflectance excluded texture generates is:
One dimension scab diffuse-reflectance texture value is set;
The quantity of texel in setting texture;
The group number of specular reflectance excluded is done the sliding-model control of texel corresponding in scab diffuse-reflectance texture number for several times, calculates the difference between adjacent texel, namely obtain the texel value in each scab diffuse-reflectance texture.
Preferably, it is determined that the method for the specular reflectance excluded of each point of blade is:
Setting degree of disease parameter;
The texture coordinate of setting scab specular reflectance excluded, the corresponding texture coordinate of any one pixel;
The scab texture coordinate value of this point is that disease hinders the pixel value of extent index value and this point and subtracts parameter constant value;
This specular reflectance excluded on blade is, wherein: scab texture coordinate value is t; The specular reflectance excluded of this point is L; Texel value is S, it may also be useful to
(1-t) * L+t*S
Formula calculate. A kind of plant disease speckle color simulation device, this device comprises with lower module:
Scab image pre-processing module, this module is accumulate specular reflectance excluded in scab for extracting and is preserved the image accumulateing in scab and only containing specular reflectance excluded information;
Specular reflectance excluded sort module, the specular reflectance excluded accumulate in image in the scab preserved is classified and is recorded the number of classification by this module;
Specular reflectance excluded order module, this module is for determining the order that each specular reflectance excluded classified occurs in scab generation process, and each specular reflectance excluded is sorted;
Scab specular reflectance excluded texture generation module, each specular reflectance excluded after sequence is generated scab specular reflectance excluded texture by this module;
Blade each point specular reflectance excluded determination module, this module is for determining the specular reflectance excluded of each point of blade.
(3) useful effect
Present invention employs following scheme: first use scab image pre-processing module, accumulate specular reflectance excluded in scab for extracting and preserve the image accumulateing in scab and only containing specular reflectance excluded information; Then use specular reflectance excluded sort module, the specular reflectance excluded accumulate in image is classified and record the number of classification in the scab preserved; Secondly use specular reflectance excluded order module, for determining the order that each specular reflectance excluded classified occurs in scab generation process, and each specular reflectance excluded is sorted; Then use scab specular reflectance excluded texture generation module, each specular reflectance excluded after sequence is generated scab specular reflectance excluded texture; Finally use blade each point specular reflectance excluded determination module, for determining the specular reflectance excluded of each point of blade. After adopting above scheme, it is to increase scab color change process with true in the similarity of scab color change process.
Accompanying drawing explanation
Fig. 1 is the schema of the plant disease speckle color simulation method of the present invention;
Fig. 2 be the present invention a kind of scab in accumulate reflectivity schematic diagram;
Fig. 3 is the illumination information schematic diagram of a kind of scab image of the present invention;
Fig. 4 is a kind of scab specular reflectance excluded texture schematic diagram that the present invention generates;
Fig. 5 is a kind of cell texture schematic diagram of the present invention;
Fig. 6 is that a kind of cucumber leaves scab using the present invention to generate generates effect demonstration schematic diagram.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described further. Following examples are only for illustration of the present invention, but are not used for limiting the scope of the invention.
As shown in Figure 1 be the schema of plant disease speckle color simulation method of the present invention, the embodiment of the present invention adopts the method flow shown in this figure to implement.
Specific embodiment
The plant disease speckle color simulation method of the present invention, such as Fig. 1, adopts and operates with the following method.
1, first use scab image pre-processing module, accumulate specular reflectance excluded in scab for extracting and preserve the image accumulateing in scab and only containing specular reflectance excluded information.
Extracting the method accumulateing specular reflectance excluded in scab is, scab area image selected by interactive frame, wherein accumulate the image of reflectivity in scab, as shown in Figure 2, the image of the illumination information of scab image, as shown in Figure 3, it may also be useful to the image in this region is carried out illumination reflection and accumulates being separated of specular reflectance excluded with in scab by intensity of illumination threshold method. When picture contrast is higher than set threshold value, can be judged as that this light is illumination information, when the contrast gradient of image is lower than set threshold value, can think that this light is scab emittance information.
2, then use specular reflectance excluded sort module, the specular reflectance excluded accumulate in image is classified and record the number of classification in the scab preserved.
The method specular reflectance excluded accumulate in scab in image classified is, employing cluster algorithm carries out packet and classifies. Adopting k-means algorithm to carry out clustering processing in the present invention, classification number is artificially given, is set to N number of, and in the present invention, N gets 9. N group specular reflectance excluded set can be obtained by this step.
Afterwards, obtain the mean value often organizing specular reflectance excluded set, it is the specular reflectance excluded eigenwert of the different stage of growth of scab by each cell mean obtained.
3, secondly use specular reflectance excluded order module, for determining the order that each specular reflectance excluded classified occurs in scab generation process, and each specular reflectance excluded is sorted.
It is be taking texture image with reference to the interactive method of design carrying out scab position, manually sequence and automatically sequence: when specular reflectance excluded set number is less than or equal to 10, manually sort; When specular reflectance excluded set number is greater than 10, automatically sort.
Automatically the theoretical foundation of sequence is, scab position reason that color change occurs mainly due to plant soma bad look gradually, the variable color that chlorophyll loss causes. Therefore in scab generation process, As time goes on the green component proportion of reflectivity can successively decrease gradually, therefore can sort according to the size of specular reflectance excluded red component and the ratio L of green component, and L is more little, order is more forward, namely appears at the early stage of disease.
4, then use scab specular reflectance excluded texture generation module, each specular reflectance excluded after sequence is generated scab specular reflectance excluded texture, as shown in Figure 4. Texture image shown in Fig. 4 should be line chart, but line chart is unfavorable for representing, therefore line chart is converted to orthographic plan and is beneficial to observe and understand.
Scab specular reflectance excluded texture is a dimension texture, forms scab diffuse-reflectance texture by texel.
The method that scab specular reflectance excluded texture generates is:
One dimension scab diffuse-reflectance texture value is set;
The quantity of texel in setting texture;
The group number of specular reflectance excluded is done the sliding-model control of texel corresponding in scab diffuse-reflectance texture number for several times, calculates the difference between adjacent texel, namely obtain the texel value in each scab diffuse-reflectance texture.
5, blade each point specular reflectance excluded determination module is finally used, for determining the specular reflectance excluded of each point of blade.
Germ there will be competition when infecting blade, and in the ideal situation, it is optimal situation that germ is evenly distributed on blade surface because germ can maximized infection blade, and the right domain of sense making independent germ self is maximum turns to. This present invention utilizes cell based function founder cell texture, as shown in Figure 5, in order to express the form of scab on blade and distribution.
The method of specular reflectance excluded determining each point of blade is:
Setting degree of disease parameter;
The texture coordinate of setting scab specular reflectance excluded, the corresponding texture coordinate of any one pixel;
The scab texture coordinate value of this point is that disease hinders the pixel value of extent index value and this point and subtracts parameter constant value;
This specular reflectance excluded on blade is, it may also be useful to 1 value subtracting speckle reason coordinate figure of preventing or cure a disease is multiplied by the sum of the product of product that the specular reflectance excluded of this point obtains and the scab texture coordinate value of this point and the texel value of this point.
The method being formulated said process is made to be:
For any point on blade, the specular reflectance excluded of this point, provides with the form of specular reflectance excluded texture, is set to L. Cell texture, in the pixel value of this point, is set to g, and span is in 0-1, and artificial setting degree of disease parameter, is set to v, and span is in 0-1. The formula (1) arranged by the present invention calculates, and its result carries out scab specular reflectance excluded texture texel value as texture coordinate, and the texel value that inquiry obtains is when degree of disease is v, the scab color changed the time.
T=max (0, v+g-1.0) (1)
Wherein max (0, v+g-1.0) expression gets its maximum value within the scope of from 0 to v+g-1.0. T is the texture coordinate of the scab specular reflectance excluded texture of this point.
Assume that texel value is S, then the formula (2) that the specular reflectance excluded of final this point of blade can be arranged according to the present invention calculates.
(1-t) * L+t*S(2)
According to method provided by the invention, a kind of cucumber leaves scab of generation generates effect, as shown in Figure 6, compared with traditional technology, it is to increase scab color change process with true in the similarity of scab color change process.
Mode of more than implementing is only for illustration of the present invention; and it is not limitation of the present invention; about the those of ordinary skill of technical field; without departing from the spirit and scope of the present invention; can also making a variety of changes and modification, therefore all equivalent technical schemes also belong to the protection category of the present invention.

Claims (8)

1. a plant disease speckle color simulation method, it is characterised in that, the method includes the steps of:
1) scab Image semantic classification, extracts in scab and accumulates specular reflectance excluded, preserves the image accumulateing in scab and only containing specular reflectance excluded information;
2) specular reflectance excluded accumulate in image in the scab preserved is classified, the number of record classification; Wherein, described step 2) in be adopt cluster algorithm to carry out packet and classify to the method that the specular reflectance excluded accumulate in scab in image is classified; Obtaining the mean value often organizing specular reflectance excluded set, each cell mean obtained is the specular reflectance excluded eigenwert of the different stage of growth of scab;
3) determine the order that each specular reflectance excluded eigenwert classified occurs in scab generation process, and each specular reflectance excluded eigenwert is sorted;
4) each specular reflectance excluded eigenwert after sequence is generated scab specular reflectance excluded texture;
5) specular reflectance excluded of each point of blade is determined.
2. a kind of plant disease speckle color simulation method according to claim 1, it is characterized in that, described step 1) in extraction scab in accumulate specular reflectance excluded method be, scab area image selected by interactive frame, it may also be useful to the image in this region is carried out illumination reflection and accumulates being separated of specular reflectance excluded with in scab by intensity of illumination threshold method.
3. a kind of plant disease speckle color simulation method according to claim 1, it is characterized in that, described step 3) in the sequence of each specular reflectance excluded eigenwert is comprised manually sequence and sequence automatically: when specular reflectance excluded set number is less than or equal to 10, manually sort; When specular reflectance excluded set number is greater than 10, automatically sort.
4. a kind of plant disease speckle color simulation method according to claim 3, it is characterized in that, described auto ordering method is sort according to the size of specular reflectance excluded red component and the ratio of green component, and ratio is more little, order is more forward, and time disease namely occur is more early.
5. a kind of plant disease speckle color simulation method according to claim 1, it is characterised in that, described step 4) in scab specular reflectance excluded texture be a dimension texture, form scab diffuse-reflectance texture by texel.
6. a kind of plant disease speckle color simulation method according to claim 5, it is characterised in that, the method that described scab specular reflectance excluded texture generates is:
One dimension scab diffuse-reflectance texture value is set;
The quantity of texel in setting texture;
The group number of specular reflectance excluded is done the sliding-model control of texel corresponding in scab diffuse-reflectance texture number for several times, calculates the difference between adjacent texel, namely obtain the texel value in each scab diffuse-reflectance texture.
7. a kind of plant disease speckle color simulation method according to claim 1, it is characterised in that, described step 5) in determine each point of blade the method for specular reflectance excluded be:
Setting degree of disease parameter;
The texture coordinate of setting scab specular reflectance excluded, the corresponding texture coordinate of any one pixel;
The scab texture coordinate value of this point is that disease hinders the pixel value of extent index value and this point and subtracts parameter constant value;
This specular reflectance excluded on blade is, wherein: scab texture coordinate value is t;The specular reflectance excluded of this point is L; Texel value is S, it may also be useful to
(1-t)*L+t*S
Formula calculate.
8. a plant disease speckle color simulation device, it is characterised in that, this device comprises with lower module:
Scab image pre-processing module, this module is accumulate specular reflectance excluded in scab for extracting and is preserved the image accumulateing in scab and only containing specular reflectance excluded information;
Specular reflectance excluded sort module, the specular reflectance excluded accumulate in image in the scab preserved is classified and is recorded the number of classification, described specular reflectance excluded sort module by this module, carries out packet specifically for adopting cluster algorithm and classifies; Obtaining the mean value often organizing specular reflectance excluded set, each cell mean obtained is the specular reflectance excluded eigenwert of the different stage of growth of scab;
Specular reflectance excluded order module, this module is for determining the order that each specular reflectance excluded eigenwert classified occurs in scab generation process, and each specular reflectance excluded eigenwert is sorted;
Scab specular reflectance excluded texture generation module, each specular reflectance excluded eigenwert after sequence is generated scab specular reflectance excluded texture by this module;
Blade each point specular reflectance excluded determination module, this module is for determining the specular reflectance excluded of each point of blade.
CN201310294388.6A 2013-07-12 2013-07-12 A kind of plant disease speckle color simulation method and device Active CN103390080B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201310294388.6A CN103390080B (en) 2013-07-12 2013-07-12 A kind of plant disease speckle color simulation method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310294388.6A CN103390080B (en) 2013-07-12 2013-07-12 A kind of plant disease speckle color simulation method and device

Publications (2)

Publication Number Publication Date
CN103390080A CN103390080A (en) 2013-11-13
CN103390080B true CN103390080B (en) 2016-06-08

Family

ID=49534349

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310294388.6A Active CN103390080B (en) 2013-07-12 2013-07-12 A kind of plant disease speckle color simulation method and device

Country Status (1)

Country Link
CN (1) CN103390080B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106650822A (en) * 2016-12-30 2017-05-10 深圳前海弘稼科技有限公司 Identification method and device for diseases and insect pests
CN108564649B (en) * 2018-04-24 2019-08-20 沈阳农业大学 A kind of plant leaf blade transmission Texture Generating Approach

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003228725A (en) * 2002-02-04 2003-08-15 Japan Science & Technology Corp 3d image processing system
CN102867325A (en) * 2012-06-29 2013-01-09 北京农业信息技术研究中心 Plant leaf scab rendering method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003228725A (en) * 2002-02-04 2003-08-15 Japan Science & Technology Corp 3d image processing system
CN102867325A (en) * 2012-06-29 2013-01-09 北京农业信息技术研究中心 Plant leaf scab rendering method

Also Published As

Publication number Publication date
CN103390080A (en) 2013-11-13

Similar Documents

Publication Publication Date Title
KR102485503B1 (en) Apparatus and method for recommending goods based on analysis of image database
CN105719327B (en) A kind of artistic style image processing method
CN108279238A (en) A kind of fruit maturity judgment method and device
CN104318596B (en) The generation method and generating means of a kind of dynamic picture
CN110479636B (en) Method and device for automatically sorting tobacco leaves based on neural network
CN104063890A (en) Method for cartooning human face and system thereof
CN108537239A (en) A kind of method of saliency target detection
CN104636759A (en) Method for obtaining picture recommending filter information and picture filter information recommending system
CN108388905B (en) A kind of Illuminant estimation method based on convolutional neural networks and neighbourhood context
WO2013106984A1 (en) Learning painting styles for painterly rendering
Li et al. Learning to reconstruct botanical trees from single images
CN103745497A (en) Plant growth modeling method and system
CN108961267A (en) Image processing method, picture processing unit and terminal device
CN109829868A (en) A kind of lightweight deep learning model image defogging method, electronic equipment and medium
CN109636764A (en) A kind of image style transfer method based on deep learning and conspicuousness detection
CN105956995A (en) Face appearance editing method based on real-time video proper decomposition
CN109978074A (en) Image aesthetic feeling and emotion joint classification method and system based on depth multi-task learning
CN108615229A (en) Collision detection optimization method based on curvature points cluster and decision tree
CN113255434A (en) Apple identification method fusing fruit features and deep convolutional neural network
CN103390080B (en) A kind of plant disease speckle color simulation method and device
CN107506362A (en) Image classification based on customer group optimization imitates brain storage method
Liu et al. Development of a machine vision algorithm for recognition of peach fruit in a natural scene
Song et al. Abstract art by shape classification
CN110319933A (en) A kind of light source light spectrum optimization method based on CAM02-UCS colored quantum noise
CN108805095A (en) image processing method, device, mobile terminal and computer readable storage medium

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant