CN201600330U - System for recognizing and locating mature pineapples - Google Patents
System for recognizing and locating mature pineapples Download PDFInfo
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- CN201600330U CN201600330U CN2009202461327U CN200920246132U CN201600330U CN 201600330 U CN201600330 U CN 201600330U CN 2009202461327 U CN2009202461327 U CN 2009202461327U CN 200920246132 U CN200920246132 U CN 200920246132U CN 201600330 U CN201600330 U CN 201600330U
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Abstract
The embodiment of the utility model provides a system for recognizing and locating mature pineapples, including two pick-up heads for collecting images of mature pineapples, wherein the pick-up heads are arranged on two sides of a binocular head respectively, and the binocular head is arranged on a tripod; an image processing device for processing images of the mature pineapples collected by the two pick-up heads so as to recognize and locate the mature pineapples, wherein the image processing device is connected with the pick-up heads. The system is capable of automatically recognizing and locating the mature pineapples by the image processing device so as to provide good condition for picking the mature pineapples by controlling the system, and greatly reducing labor coefficient and improving labor efficiency.
Description
Technical field
The utility model embodiment relates to computer Recognition and field of locating technology, relates in particular to a kind of ripe pineapple identification and positioning system.
Background technology
In recent years, a lot of experts and scholars both domestic and external had carried out a large amount of research to the fruits and vegetables robot that gathers.Wherein the fruits and vegetables effect that the vision system of robot promptly discerns with positioning system of gathering is that identification is treated the fruit picking vegetables and obtained its more specific location information, prepare against the subsequent control system according to positional information, driving device arm and end effector move to the position of harvesting, and fruits and vegetables are gathered.Therefore the identification of fruits and vegetables and positioning system are to realize gather a very important job of robotization of fruits and vegetables.
Pineapple is planted in China's southern area, and cultivated area is very wide, at the pineapple collecting season, people are faced with the weather sweltering heat, go in the field many ripe pineapple is discerned and locatees harvesting, its labour intensity is very big.If can design identification and the positioning system of the ripe pineapple of a cover, adopt the positional information of the ripe pineapple that existing control system obtains according to the location then, ripe pineapple is plucked, just can reduce people's labor capacity widely.Therefore, how the identification of ripe pineapple is become the technical matters that needs to be resolved hurrily with the location.
The utility model content
The utility model embodiment provides a kind of ripe pineapple identification and positioning system, in order to remedy the deficiencies in the prior art, can discern ripe pineapple automatically and carry out three-dimensional localization, help to reduce people's labor capacity effectively by the harvesting of control system realization to ripe pineapple.
The utility model embodiment provides a kind of ripe pineapple identification and positioning system, comprise: two cameras that are used for ripe pineapple is carried out image acquisition, described two cameras are provided with respectively in binocular The Cloud Terrace both sides, described binocular The Cloud Terrace is arranged on the tripod, also comprise be used for to described two camera collections to ripe pineapple image handle, with realize to described ripe pineapple discern and locate image processing equipment, described image processing equipment is connected with described two cameras.
Ripe pineapple identification and the positioning system of the utility model embodiment, by automatic identification and the location of realizing of image processing equipment to ripe pineapple, scheme by the utility model embodiment provides good condition for realizing by control system to the harvesting of ripe pineapple, significantly reduce people's labor capacity, improved efficiency.
Description of drawings
In order to be illustrated more clearly in the utility model embodiment or technical scheme of the prior art, to do one to the accompanying drawing of required use in embodiment or the description of the Prior Art below introduces simply, apparently, accompanying drawing in describing below is embodiment more of the present utility model, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
The ripe pineapple that Fig. 1 provides for the utility model embodiment discerns the structural representation with positioning system;
The ripe pineapple identification that Fig. 2 provides for the utility model embodiment and the structural representation of the image processing equipment of positioning system;
The ripe pineapple that Fig. 3 provides for the utility model embodiment discerns the performing step process flow diagram with positioning system.
Embodiment
For the purpose, technical scheme and the advantage that make the utility model embodiment clearer, below in conjunction with the accompanying drawing among the utility model embodiment, technical scheme among the utility model embodiment is clearly and completely described, obviously, described embodiment is the utility model part embodiment, rather than whole embodiment.Based on the embodiment in the utility model, those of ordinary skills are not making all other embodiment that obtained under the creative work prerequisite, all belong to the scope of the utility model protection.
Further specify the technical scheme of the utility model embodiment below in conjunction with the drawings and specific embodiments.
The ripe pineapple that Fig. 1 provides for the utility model embodiment discerns the structural representation with positioning system; As shown in Figure 1, comprise: two cameras 10 that are used for ripe pineapple is carried out image acquisition, two cameras 10 are provided with respectively in binocular The Cloud Terrace 11 both sides, binocular The Cloud Terrace 11 is arranged on the tripod 12, be used for to the ripe pineapple image that two cameras 10 collect handle, image processing equipment 13 to realize described ripe pineapple is discerned and locatees, image processing equipment 13 is connected with two cameras 10.
Present embodiment is in order to lower the cost of this maturation pineapple identification and positioning system, making this system to access widely promotes the use of, wherein two cameras 10 all adopt complementary metal oxide semiconductor (CMOS) (Complementary Metal Oxide Semiconductor, hereinafter to be referred as CMOS) camera, and because pineapple is the individual plant growth, it is big to have stature, characteristics such as the fruit eye is clear, the pixel of two cameras 10 here can not be higher than 1,300,000 pixels, just can accurately collect the image of ripe pineapple, the pixel that can choose two cameras 10 usually equates.
The ripe pineapple identification that Fig. 2 provides for the utility model embodiment and the structural representation of the image processing equipment of positioning system; As shown in Figure 2, the image processing equipment 13 in identification of the pineapple of present embodiment and the positioning system can specifically comprise: receiver module 131, pretreatment module 132, dividing processing module 133, conjugate impedance match module 134, locating module 135 and correction module 136.
Wherein: receiver module 131 is used to receive the described ripe pineapple image that two cameras 10 collect; It should be noted that and to gather ripe pineapple image for the first time, need carry out the parameter setting two cameras 10.
Pretreatment module 132 is used for the described ripe pineapple image that two cameras 10 collect is carried out pre-service, and the pre-service here comprises carries out medium filtering to described ripe pineapple image, and pre-service such as corrosion are with the removal of images noise;
Dividing processing module 133 is used for pretreated described ripe pineapple image is cut apart, realizes to the identification of ripe pineapple with to the extraction of described ripe pineapple fruit image, and the centre of form of calculating and the described ripe pineapple fruit image of mark;
Described ripe pineapple fruit image after conjugate impedance match module 134 is used for the described ripe pineapple image that two cameras 10 collect respectively cut apart carries out conjugate impedance match; Dividing processing module 133 is that the every two field picture to each camera processes, finally mark the centre of form of ripe pineapple fruit image, yet two cameras 10 are all constantly being gathered ripe pineapple image, need to determine two camera collections to ripe pineapple image whether be the image of same ripe pineapple, here adopt the method for conjugate impedance match, get access to the same ripe pineapple image that two cameras 10 refer to.
Locating module 135 is used for the centroid point according to the described ripe pineapple fruit image after the coupling, uses the range of triangle principle, obtains the three-dimensional information of the centroid point of described ripe pineapple fruit image; The ripe pineapple image that this module gets access to according to conjugate impedance match module 134, and the centre of form of the ripe pineapple fruit that calculates according to dividing processing module 133, use the range of triangle principle then, just can obtain the three-dimensional information in the space of the centroid point of ripe pineapple fruit image, i.e. volume coordinate.
Need to prove, also comprise demarcating module (not drawing among the figure) in the image processing equipment 13 in the present embodiment, be used for two demarcating modules that camera is demarcated that are provided with on the binocular The Cloud Terrace 11.
Need to prove, the pineapple identification of present embodiment and the dividing processing module 133 in the image processing equipment 13 in the positioning system, can comprise four unit (not drawing among the figure) particularly, wherein: first module is used for obtaining process described pineapple ripening fruits zone and through the differentiation line of the background area that comprises pineapple leafiness, soil from pretreated described ripe pineapple image; Promptly from the ripe pineapple image of pretreated elimination noise, choose a differentiation line through background areas such as post-mature pineapple fruit and pineapple leafiness, soil, buff dead leaves.
It is horizontal reference line that Unit second is used for described differentiation line, draws redness, green and the blue branch discharge curve of zone of pineapple ripening fruits described in the described ripe pineapple image and described background area respectively;
Particularly, the differentiation line that Unit second obtains with above-mentioned first module is as horizontal reference line, draws respectively through the ripe pineapple of distinguishing line and redness, green and the blue branch discharge curve of each background area.
Unit the 3rd be used for according to formula H (i, j)=10 * (r (and i, j)-g (i, j))/b (i j) obtains a line of correlation, and choose H (i, j)＞5﹠amp; H (i, j)＜40 extract with identification and to described ripe pineapple fruit image in the zone, H (i wherein, j) expression is an initial point with the left end point of horizontal reference line described in the described ripe pineapple image, and horizontal ordinate is i, and ordinate is the value of the described line of correlation correspondence of j; R (i, j) the expression horizontal ordinate is i, ordinate is the value of the red component curve correspondence of j, g (i, j) the expression horizontal ordinate is i, ordinate is the value of the green component curve correspondence of j, b (i, j) the expression horizontal ordinate is i, ordinate is the value of the blue component curve correspondence of j;
Particularly, at first in pretreated ripe pineapple image, be that the left end point of above-mentioned described differentiation line is an initial point with horizontal reference line, then according to formula H (i, j)=10 * (r (i, j)-g (i, j))/b (i, j) obtain a line of correlation, and choose H (i, j)＞5﹠amp; H (i, j)＜40 the zone just can recognize yellow ripe pineapple fruit image, has given prominence to ripe pineapple fruit zone, suppresses the background area, realizes the extraction to ripe pineapple fruit zone; The relational expression that can clear obtain ripe pineapple fruit of above-mentioned formula for ripe pineapple image is obtained through test of many times, if line of correlation H (i, j) H (i, j)＞5﹠amp; (i j)＜40 in the zone, does not observe ripe pineapple fruit image to H, illustrates that this position does not have ripe pineapple, may be that immature or this position of the pineapple of this position does not have pineapple at all.Wherein numeral 10 expressions are amplified ten times to the result, discern and extract with convenient.Here mainly utilize ripe pineapple to be yellow color, on color, very big difference is arranged with background colours such as leafiness, soils, find according to the difference of ripe pineapple color and background color and to be applicable to outstanding ripe pineapple image, R, the G of inhibition background area, the formula H that B divides discharge curve (i, j)=10 * (r (i, j)-g (i, j))/b (i, j), and be provided with threshold value H (i, j)＞5﹠amp; (i j)＜40 realizes the successful extraction to ripe pineapple to H.
Unit the 4th is used to calculate the centre of form with the described ripe pineapple fruit image of mark.The ripe pineapple fruit image that this unit extracts in mainly Unit the 3rd being done calculates its centre of form of mark, so that follow-up concrete location to ripe pineapple.
Ripe pineapple image can be discerned and locate to the pineapple identification and the positioning system of present embodiment automatically, help to have reduced the people's work amount widely by the harvesting work of control system realization to ripe pineapple; And this system is cheap by adopting the CMOS camera that is not higher than 1,300,000 pixels, has guaranteed the low cost of this system effectively, helps to promote and use.
Embodiment described above only is schematic, wherein said unit as the separating component explanation can or can not be physically to separate also, the parts that show as the unit can be or can not be physical locations also, promptly can be positioned at a place, perhaps also can be distributed on a plurality of network element.Can select wherein some or all of module to realize the purpose of present embodiment scheme according to the actual needs.Those of ordinary skills promptly can understand and implement under the situation of not paying performing creative labour.
Image processing equipment in the foregoing description can adopt computer entity to realize, particularly, the unit that comprises in each module in the image processing equipment and the module can be realized by correspondent computer software.
A kind of ripe pineapple that Fig. 3 provides for the utility model embodiment discerns the performing step process flow diagram with positioning system; As shown in Figure 3, adopt computing machine to realize that the function of image processing equipment is an example in the present embodiment, describe in detail and adopt identification and the position fixing process of the technical solution of the utility model realization ripe pineapple.
Particularly, two cameras 10 are separately positioned on the both sides of binocular The Cloud Terrace 11, two concrete cameras 10 can be the both sides that are arranged on binocular The Cloud Terrace 11 of symmetry, and binocular The Cloud Terrace 11 is arranged on the tripod 12; Image processing equipment 13 adopts a computer entity to realize, computing machine all has with two cameras 10 and is connected, to realize being identification and locate to ripe pineapple.The camera 10 here can adopt pixel not to be higher than 1,300,000 CMOS camera, and the market price guarantees the low cost of total system effectively about RMB is 100 yuan/, when under XP operating system, the camera 10 of present embodiment need not installed driving, and plug and play is very easy to use.
The demarcation of step 101, camera;
Particularly, adopt existing scaling method,, the gridiron pattern of making adopted respectively based on the automatic calibration method of C++ and Opencv 1.1 with based on two kinds of methods of Matlab calibration tool case tested at the image acquisition window.The image that discovery is taken for the CMOS camera based on the automatic calibration method of C++ and Opencv 1.1 has certain error, and the demarcation effect of Matlab calibration tool case is then better relatively.Therefore, the preferred Matlab calibration tool of present embodiment case is demarcated two cameras, realizes the function of the foregoing description demarcating module, can obtain each parameter of two cameras 10 after demarcating by this step, so that follow-up location to ripe pineapple.
The collection of step 102, ripe pineapple image;
Under the XP system, finished programmed environment based on Vc, call the binocular image acquisition of Opencv built-in function, and in opening the camera process, realized the selection setting of camera parameter.
The pre-service of step 103, ripe pineapple image;
Particularly, adopt image processing software, the pineapple image that two cameras 10 are collected carries out medium filtering, and pre-service such as corrosion to remove the noise in the image effectively, realize the function of pretreatment module 132.
Cutting apart of step 104, ripe pineapple fruit image;
Particularly, adopt image processing software to realize dividing processing module 133 and the function of four unit comprising here,,, do not repeat them here in detail with reference to the foregoing description with segmented extraction to ripe pineapple fruit image.After extracting ripe pineapple fruit image, need be to this fruit image calculation and the energy mark centre of form, so that follow-up location to ripe pineapple fruit.
The coupling of step 105, the ripe pineapple fruit image of conjugation;
The concrete processing of above-mentioned steps 103 and step 104 all is the image that arrives at one of them camera collection, to the location of ripe pineapple image, need carry out conjugate impedance match for exactly to the same ripe pineapple fruit image that expression in two cameras collects; Specifically conjugated image is carried out the computing of gray scale respectively, the fast detecting of image point of interest, the feature description of good point of interest peripheral region have been realized, then according to these features, to two camera collections to ripe POLO fruit image mate fast, realize the function of conjugate impedance match module 134.
The location of step 106, ripe pineapple fruit image;
Particularly, according to two camera collections to ripe pineapple fruit image carry out conjugate impedance match after, obtain the centre of form of the ripe pineapple fruit image of coupling, use the range of triangle principle then, formula below adopting calculates the three-dimensional information of the ripe pineapple fruit centre of form, promptly should the concrete coordinate x in maturation pineapple fruit centre of form space, y, z.
Wherein: x, y, z are expressed as the coordinate figure of the x direction on the space of the ripe pineapple fruit centre of form, the coordinate figure of y direction, the coordinate figure of z direction;
F, tx, ty, tz, r1, r2, r3, r4, r5, r6, r7, r8, r9 are respectively the inside and outside parameter of camera, when demarcating, all obtain by matrix form.
Wherein: f is the focal length of two cameras, and the utility model embodiment arranges the focal length approximately equal of two cameras, can get both mean value in the actual computation;
If is the initial point of world coordinate system with left camera, right camera has a translation matrix with respect to left camera, tx wherein, and ty, tz is respectively x, y, the translational movement on the z direction;
If is the initial point of world coordinate system with left camera, right camera is one 3 * 3 matrix with respect to the rotation matrix of left camera, r1 wherein, and r2, r3, r4, r5, r6, r7, r8, r9 represent 9 numerical value in the rotation matrix respectively; Because the parameter abovementioned steps in the above-mentioned formula all can access, just can obtain the centre of form coordinate of ripe pineapple fruit according to above-mentioned formula, the function of locating module 135 has been realized in preliminary location of realizing ripe pineapple fruit.
Particularly, a projected relationship that adopts a utilization artificial neural network training to obtain is usually proofreaied and correct, and the centre of form position position coordinates of the ripe pineapple fruit that calculates is proofreaied and correct.Described projected relationship is to obtain in the following manner: at the ripe pineapple fruit centre of form Coordinate Calculation value that repeatedly obtains by the range of triangle principle, the actual value of corresponding ripe pineapple fruit centre of form coordinate is obtained in on-the-spot respectively range finding, train by artificial neural network then, just obtain a projected relationship that is used for correction error.Like this, whenever obtain a ripe pineapple fruit centre of form Coordinate Calculation value later on, just can proofread and correct this calculated value, just can obtain the corrected value of a ripe more accurately pineapple fruit centre of form coordinate, realized the function of correction module 136 according to projected relationship.
Through the above description of the embodiments, those skilled in the art can be well understood to each embodiment and can realize by the mode that software adds essential general hardware platform.Based on such understanding, the part that technique scheme contributes to prior art in essence in other words can embody with the form of software product, this computer software product can be stored in the computer-readable recording medium, as ROM/RAM, magnetic disc, CD etc., comprise that some instructions are with so that a computer equipment (can be a personal computer, server, perhaps network equipment etc.) carry out the described method of some part of each embodiment or embodiment.
Module or unit in conjunction with each example of the disclosed embodiments description among the application, can realize with electronic hardware, computer software or the combination of the two, for the interchangeability of hardware and software clearly is described, the composition and the step of each example described prevailingly according to function in the above description.These functions still are that software mode is carried out with hardware actually, depend on the application-specific and the design constraint of technical scheme.The professional and technical personnel can use distinct methods to realize described function to each specific should being used for, but this realization should not thought and exceeds scope of the present utility model.
It should be noted that at last: above embodiment only in order to the explanation the technical solution of the utility model, is not intended to limit; Although the utility model is had been described in detail with reference to previous embodiment, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment put down in writing, and perhaps part technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the spirit and scope of each embodiment technical scheme of the utility model.
Claims (4)
1. a ripe pineapple discerns and positioning system, it is characterized in that, comprising:
Be used for ripe pineapple is carried out two cameras of image acquisition, described two cameras are separately positioned on binocular The Cloud Terrace both sides, and described binocular The Cloud Terrace is arranged on the tripod;
Be used for to described two camera collections to ripe pineapple image handle, image processing equipment to realize described ripe pineapple is discerned and locatees, described image processing equipment is connected with described two cameras.
2. ripe pineapple identification according to claim 1 and positioning system is characterized in that described two cameras all adopt the complementary metal oxide semiconductor (CMOS) camera.
3. ripe pineapple identification according to claim 1 and 2 and positioning system is characterized in that the pixel of described two cameras is not higher than 1,300,000 pixels.
4. ripe pineapple identification according to claim 3 and positioning system is characterized in that the pixel of described two cameras equates.
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| CN2009202461327U CN201600330U (en) | 2009-09-23 | 2009-09-23 | System for recognizing and locating mature pineapples |
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| CN2009202461327U CN201600330U (en) | 2009-09-23 | 2009-09-23 | System for recognizing and locating mature pineapples |
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| CN104704990A (en) * | 2015-04-08 | 2015-06-17 | 吴春光 | Electronic automatic picking method of pomegranate trees |
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| CN104794712A (en) * | 2015-04-16 | 2015-07-22 | 王爱云 | Single-pear-tree yield detecting system based on electronic identification |
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| CN105158254A (en) * | 2015-01-25 | 2015-12-16 | 无锡桑尼安科技有限公司 | Identification method of crop maturity |
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| CN108416814A (en) * | 2018-02-08 | 2018-08-17 | 广州大学 | Quick positioning and recognition methods and the system on a kind of pineapple head |
| CN109644674A (en) * | 2019-02-22 | 2019-04-19 | 北京工商大学 | A kind of automatic picking Machine for pineapple and automatic picking method |
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| CN105158254A (en) * | 2015-01-25 | 2015-12-16 | 无锡桑尼安科技有限公司 | Identification method of crop maturity |
| CN104732550A (en) * | 2015-04-08 | 2015-06-24 | 吴春光 | Electronic automatic picking platform for pomegranate trees |
| CN104704990A (en) * | 2015-04-08 | 2015-06-17 | 吴春光 | Electronic automatic picking method of pomegranate trees |
| CN104704990B (en) * | 2015-04-08 | 2016-09-14 | 南通市广益机电有限责任公司 | A kind of pomegranate tree electronization picking method automatically |
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| CN104794712A (en) * | 2015-04-16 | 2015-07-22 | 王爱云 | Single-pear-tree yield detecting system based on electronic identification |
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| CN105067618B (en) * | 2015-07-21 | 2018-07-24 | 仲恺农业工程学院 | Binocular vision monitoring system for growth of multiple plants |
| CN105067618A (en) * | 2015-07-21 | 2015-11-18 | 仲恺农业工程学院 | Binocular vision monitoring system for growth of multiple plants |
| CN105865345A (en) * | 2016-06-14 | 2016-08-17 | 南京大树智能科技股份有限公司 | Mushroom automatic picking detection control method |
| CN106778912A (en) * | 2017-01-13 | 2017-05-31 | 湖南理工学院 | A kind of full-automatic apparatus for baking and method for cake |
| CN107909615A (en) * | 2017-12-18 | 2018-04-13 | 广东广业开元科技有限公司 | A kind of fire monitor localization method based on binocular vision |
| CN108037520A (en) * | 2017-12-27 | 2018-05-15 | 中国人民解放军战略支援部队信息工程大学 | Direct deviations modification method based on neutral net under the conditions of array amplitude phase error |
| CN108416814A (en) * | 2018-02-08 | 2018-08-17 | 广州大学 | Quick positioning and recognition methods and the system on a kind of pineapple head |
| CN108416814B (en) * | 2018-02-08 | 2020-07-31 | 广州大学 | Method and system for quickly positioning and identifying pineapple head |
| CN109644674A (en) * | 2019-02-22 | 2019-04-19 | 北京工商大学 | A kind of automatic picking Machine for pineapple and automatic picking method |
| CN110999636A (en) * | 2019-11-12 | 2020-04-14 | 青岛大学 | Strawberry clamping scissors |
| CN116453111A (en) * | 2023-06-16 | 2023-07-18 | 广东海洋大学 | Pineapple maturity analysis method based on lightweight YOLOv4 |
| CN116453111B (en) * | 2023-06-16 | 2023-11-21 | 广东海洋大学 | Pineapple maturity analysis method based on lightweight YOLOv4 |
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