CN202267464U - Mobile phone based device for rapidly detecting blade area - Google Patents
Mobile phone based device for rapidly detecting blade area Download PDFInfo
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- CN202267464U CN202267464U CN2011204246712U CN201120424671U CN202267464U CN 202267464 U CN202267464 U CN 202267464U CN 2011204246712 U CN2011204246712 U CN 2011204246712U CN 201120424671 U CN201120424671 U CN 201120424671U CN 202267464 U CN202267464 U CN 202267464U
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Abstract
The utility model discloses a mobile phone based device for rapidly detecting a blade area. The mobile phone based device comprises a mobile phone (4), a background plate (1), a reference object (2) and a blade (3) to be tested, wherein the reference object (2) and the blade (3) to be tested are respectively placed at different positions on the background plate (1), the mobile phone is located above the background plate (1) vertically and has the functions of photographing, storing, image processing, statistical analyzing, human-machine interacting and displaying, the color of the front face of the background plate (1) is different from the color of the blade (3) to be tested and the color of the reference object (2), and the color of the reference object (2) is different from the color of the blade (3) to be tested. The device disclosed by the utility model not only is simple in structure and convenient to carry, but also is favorable for simplifying measurement steps, shortening detection time and increasing measurement precision.
Description
Technical Field
The utility model relates to a device of short-term test blade area based on cell-phone.
Background
The leaf area is a commonly used index in crop cultivation and breeding practice, is an evaluation index of the yield and quality of crops, is also an important index for breeding an ideal plant type and determining the damage loss of pests, can calculate the water consumption, transpiration, yield and the like of the crops by utilizing the parameters, can also analyze the growth condition of the plants, and establishes a plant growth model. The leaves are important organs of plants for photosynthesis to synthesize organic matters, and the size of the leaf area directly influences the yield of crops to a certain extent. Plant researchers often need to obtain the area of a plant leaf when looking at it in the field. Therefore, the method for measuring the leaf area is convenient and accurate to establish, and has positive significance for guiding agricultural production practice activities and making high-yield, high-quality and high-efficiency cultivation technical measures.
There are two general categories of methods currently in use: one is destructive blade area determination method, including the methods of the square method, the weighing method, the pixel scanning method and the like, which can not measure in vivo and can damage the blade; the second category is non-destructive leaf area measurement methods, including regression, image processing, and photoelectric methods. In the current image processing method, various imaging devices are used for collecting blade images into digital images, and the digital images are transmitted to a computer and then are subjected to area measurement by Matlab or self programming.
Disclosure of Invention
The utility model discloses aim at overcoming above-mentioned existing not enough of technique, provide a device based on cell-phone short-term test blade area. The utility model discloses a detection device is simple structure not only, portable, but also has simplified the measuring step, has shortened check-out time, has improved measurement accuracy.
A rapid leaf area detection device based on a mobile phone comprises the mobile phone, a background plate, a reference object and a detected leaf, wherein the reference object and the detected leaf are respectively arranged at different positions on the background plate; the front color of the background plate is different from the color of the detected blade and the color of the reference object; the color of the reference object is different from that of the detected leaf.
The utility model discloses short-term test blade area's based on cell-phone device's theory of operation:
a. selecting a pure-color opaque flat plate with the front side different from the color of the detected blade as a background plate, wherein the area of the background plate is larger than that of the blade, and the pure-color opaque flat plate is convenient to shoot and form an image in the background plate area during framing;
b. fixing an area S on the front surface of the background plateRThe color of the reference object is different from that of the background plate and the detected blade;
c. flattening and laying the measured blade on the front surface of the background plate, enabling the measured blade to be close to the position of the reference object, and shooting through a camera of a mobile phone to obtain a complete digital photo containing the measured blade and the reference object in the background plate area;
d. carrying out graying, filtering, geometric correction, binarization and region communication labeling on the photo, dividing the photo into three regions of a background, a reference object and a detected blade, and traversing photo data to obtain the total number of pixels of a background plate, the total number of pixels of the reference object and the total number of pixels of the detected blade;
e. and finally, the mobile phone gives the area of the reference object according to the obtained total number of the pixels of the reference object and the total number of the pixels of the detected blade, and according to the following formula:
and automatically calculating to obtain the area of the blade to be measured.
The specific method for identifying and counting the total number of the pixels occupied by the reference object and the detected blade is as follows: and preprocessing the photo, including filtering and geometric correction, and then carrying out graying and smoothing, image binarization and connected region labeling on the photo. After the above processing, the photograph is divided into three regions, i.e., a background plate, a reference object and a leaf to be measured. Finally, the total number of pixels of the background plate, the total number of pixels of the reference object and the total number of pixels of the leaf can be obtained by traversing the photo data. And obtaining the total number of the pixels of the reference object and the total number of the pixels of the leaf after the user interaction comparison.
The preprocessing of the picture in the above method includes graying, which is to convert a color image into a grayscale image. The graying of the picture in the method is realized by converting an RGB model of the picture color into an HIS model. The influence of the intensity component in the color information in the color image is eliminated. The HSI color model and the RGB color model can be converted into each other through nonlinear transformation:
with respect to the grayed-out grayscale image,f(x,y)coordinate of function point of(x,y)The gray value of the pixel point.
The pre-processing of the picture in the above method includes filtering, which can reduce and eliminate the "noise" in the picture to improve the picture quality. The method adopts a linear filtering method. The algorithm for linear filtering is as follows:
(1) sequentially traversing each pixel of the grayscale image from left to right and from top to bottomf(x,y)；
(2) Associating the center of the template operator with the input pixelf(x,y)Overlapping, performing convolution operation on the pixel and the template thereof, and taking the operation result value as the gray value of the corresponding pixel of the output image;
(3) if all pixels are processed, the algorithm ends, otherwise go to (1).
In the method, the binaryzation of the photo adopts an iterative threshold segmentation method. The binarization processing of the photo is to select a gray threshold value and convert the image into a black-white binary image, and the algorithm of the iterative threshold value segmentation method is as follows:
assume that the middle value of the photograph gray scale range is taken as the initial threshold valueT 0 Then its mathematical expression is:
wherein,Lis the number of the gray levels,is a gray value ofkThe number of the pixel points.
The specific implementation algorithm is as follows:
(1) determining the maximum gray-scale value of the imageZmax and minimum gray valueZmin, let initial thresholdT 0 =(Z max+Z min)/2；
(2) According to an initial thresholdValue ofT0An image is divided into a target and a background, and the average gray scale value of the target and the average gray scale value of the background are respectively obtainedZ1 andZ2；
(3) finding a new thresholdT=(Z1+Z2)/2；
(4) If it isT0≠THandle barTIs given toT0Turning to the step (2), and circularly iterating the calculation until the stepT0=TIs stopped at the moment to obtainTI.e. the optimal threshold. After the optimal threshold value is determined, binarization processing is carried out, and a transformation function expression is as follows:
in the method, a neighborhood pixel connection marking method is adopted for marking the picture connection area. The connected region mark is to assign the same label number to the adjacent pixel points with the same gray value in the binary image. The algorithm steps of the neighborhood pixel connected marking method are as follows:
(1) the photos are scanned from left to right, top to bottom. For each point of each row, if the gray value of a certain pixel point is 255, there are the following situations: if the upper dot and the left dot have one mark, the mark is copied. If two points have the same mark, the mark is copied. If the two points have different marks, copying the smaller mark of the two points, and writing the two marks into an equivalent table to be used as equivalent marks; otherwise, a new mark is distributed to the pixel point and the mark is written into the equivalent table.
(2) And (4) considering the next line, and repeating the step (2).
(3) And (5) scanning the image from top to bottom, and repeating the steps (2) and (3).
(4) In each equivalence set of the equivalence table, the lowest label in the equivalence set is found.
(5) Traversing the image, replacing each marker with the lowest marker in the equivalence table, and marking each connected region with a different color.
After the photo connected region is marked, the photo data is traversed to obtain the total number of pixels of the background plate, the total number of pixels of the reference object and the total number of pixels of the detected leaf. And obtaining the total number of the pixels of the reference object and the total number of the pixels of the measured leaf after the user interaction comparison. The area of the blade to be measured is calculated by the following formula
The utility model discloses a blade area short-term test method has mainly utilized the hardware platform and the software platform and the digital image processing technique of current cell-phone, the camera of calling the cell-phone through software acquires the complete photo that contains reference thing and surveyed the blade in the background board region, and then carries out image processing to the photo through the software on the cell-phone with Java language development, make up out the pixel total number that the reference thing and surveyed the blade shared in this digital photo, calculate the area that obtains the surveyed the blade according to the formula at last.
The utility model discloses a detection device is simple structure not only, portable, but also has simplified the measuring step, has shortened check-out time, has improved measurement accuracy.
Drawings
Fig. 1 is the structure schematic diagram of the device for rapidly detecting the blade area based on the mobile phone of the present invention.
Detailed Description
The present invention will be described in detail with reference to the following examples and accompanying drawings, which further illustrate the objects and features of the present invention, but the present invention is not limited thereto.
Example 1
As shown in fig. 1, the utility model discloses a device for rapidly detecting blade area based on mobile phone, including mobile phone 4, background board 1, reference object 2 and measured blade 3 respectively locate different positions on background board 1, mobile phone 4 be located the vertical top of background board 1; the mobile phone 4 has the functions of photographing, storing, image processing, statistical analysis, man-machine interaction and displaying; the front color of the background plate 1 is different from the color of the detected blade 3 and the color of the reference object 2; the color of the reference object 2 is different from that of the detected blade 3.
Claims (1)
1. The utility model provides a quick leaf area detection device based on cell-phone which characterized in that: the device comprises a mobile phone (4), a background plate (1), a reference object (2) and a detected blade (3), wherein the reference object (2) and the detected blade (3) are respectively arranged at different positions on the background plate (1);
the mobile phone (4) is positioned vertically above the background plate (1) and has the functions of photographing, storing, image processing, statistical analysis, man-machine interaction and displaying;
the front color of the background plate (1) is different from the color of the detected blade (3) and the color of the reference object (2);
the color of the reference object (2) is different from that of the detected blade (3).
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| Application Number | Priority Date | Filing Date | Title |
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| CN2011204246712U CN202267464U (en) | 2011-11-01 | 2011-11-01 | Mobile phone based device for rapidly detecting blade area |
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| Application Number | Priority Date | Filing Date | Title |
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| CN2011204246712U CN202267464U (en) | 2011-11-01 | 2011-11-01 | Mobile phone based device for rapidly detecting blade area |
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| CN202267464U true CN202267464U (en) | 2012-06-06 |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102506772A (en) * | 2011-11-01 | 2012-06-20 | 西北农林科技大学 | Method and device for quickly detecting area of leaf blade based on mobile phone |
| CN102865823A (en) * | 2012-10-12 | 2013-01-09 | 西安电子科技大学 | Length measuring method based on currency |
| CN105043271A (en) * | 2015-08-06 | 2015-11-11 | 宁波市北仑海伯精密机械制造有限公司 | Method and device for length measurement |
| CN106404070A (en) * | 2016-10-28 | 2017-02-15 | 浙江理工大学 | Android-based automatic printing and dyeing machine fabric parameter detection system |
| CN109191520A (en) * | 2018-09-30 | 2019-01-11 | 湖北工程学院 | A kind of Measurement Approach of Leaf Area and system based on color calibration |
| CN109520447A (en) * | 2018-11-29 | 2019-03-26 | 中国科学院南京地理与湖泊研究所 | A method of amendment image treating measures hydrilla verticillata blade area |
-
2011
- 2011-11-01 CN CN2011204246712U patent/CN202267464U/en not_active Expired - Fee Related
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102506772A (en) * | 2011-11-01 | 2012-06-20 | 西北农林科技大学 | Method and device for quickly detecting area of leaf blade based on mobile phone |
| CN102865823A (en) * | 2012-10-12 | 2013-01-09 | 西安电子科技大学 | Length measuring method based on currency |
| CN105043271A (en) * | 2015-08-06 | 2015-11-11 | 宁波市北仑海伯精密机械制造有限公司 | Method and device for length measurement |
| CN105043271B (en) * | 2015-08-06 | 2018-09-18 | 宁波市北仑海伯精密机械制造有限公司 | Length measurement method and device |
| CN106404070A (en) * | 2016-10-28 | 2017-02-15 | 浙江理工大学 | Android-based automatic printing and dyeing machine fabric parameter detection system |
| CN106404070B (en) * | 2016-10-28 | 2019-01-08 | 浙江理工大学 | A kind of dyeing machine fabric parameter automatic checkout system based on android |
| CN109191520A (en) * | 2018-09-30 | 2019-01-11 | 湖北工程学院 | A kind of Measurement Approach of Leaf Area and system based on color calibration |
| CN109520447A (en) * | 2018-11-29 | 2019-03-26 | 中国科学院南京地理与湖泊研究所 | A method of amendment image treating measures hydrilla verticillata blade area |
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Granted publication date: 20120606 Termination date: 20121101 |