CN101709951A - Method for measuring and recording phenotypic characters of scallop by computer - Google Patents
Method for measuring and recording phenotypic characters of scallop by computer Download PDFInfo
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- CN101709951A CN101709951A CN200910231574A CN200910231574A CN101709951A CN 101709951 A CN101709951 A CN 101709951A CN 200910231574 A CN200910231574 A CN 200910231574A CN 200910231574 A CN200910231574 A CN 200910231574A CN 101709951 A CN101709951 A CN 101709951A
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Abstract
The invention belongs to a measuring method for phenotypic characters of a scallop in the technical field of computer data processing, namely a method for measuring and recording the phenotypic characters of the scallop by a computer. The method comprises the following steps of: fixing a bracket on the outer side of a balance, fixing a camera on the bracket, connecting the camera and the balance to the computer through data wires, recognizing photos by using a computer image recognition technique, measuring the shell height, the shell length, the shell width and the body weight of the scallop in the photos, and simultaneously recording reading numbers of the balance; and putting two cameras on the top part and the lateral surface of an electronic balance respectively to record front views and side views of the scallop respectively, connecting the balance to the computer through the data wire, starting software, turning on the cameras, zeroing the balance, putting the scallop on the balance, pressing a printing key when the reading number of the balance is stable, and automatically reading an indicated number of the balance and taking pictures, and automatically measuring the shell height, the shell length, the shell width and the body weight. The method has the advantages of simple measuring device, safety, reliability, high automation degree and quick and accurate data processing, and is widely used for classifying and screening the scallops.
Description
Technical field:
The invention belongs to computer measurement and record data processing technology field, relate to the measuring technique method of a kind of phenotypic characters of scallop (be the shell height, shell is long, shell is wide, body weight etc.), particularly a kind of phenotypic characters of scallop by computer is measured and recording method.
Background technology:
Scallop occupies extremely important status as one of economic cultivated shellfish of China's seawater in the sea-farming industry.In the selection breeding process of scallop, to the measurement of the phenotypic character step that is absolutely necessary.At present the most frequently used measuring method be utilize vernier caliper to the shell height, shell is long, shell is wide measures, its shortcoming is to measure the shell height respectively, shell is long, shell is wide, speed is slow, reading can produce error when the different measuring person measured; Vernier caliper is damaged by marine denudation easily when scallop is lived in measurement; Body weight and shell size can not be measured simultaneously; As carrying out data analysis, need manual record data and input computer.Therefore the improvement to Chlamys farreri phenotypic character measuring method is the key that improves breeding efficiency and criterion data.Image recognition technology is meant uses computing machine, and by mathematical method, the image that a system front end is obtained is according to specific purpose, the method for handling especially.Existing image recognition comprises as the dynamic object identification in bar-code identification, the identification of biological characteristic proterties, the intelligent transportation, handwriting recognition etc.We can say that image recognition technology is exactly the extension of human vision cognition, is a key areas of artificial intelligence.Along with the development of computer technology and artificial intelligence technology, image recognition technology more and more becomes the basic technology of artificial intelligence.The also constantly development of its fundamental analysis method along with the continuous progress of mathematical tool.At present, adopt computing machine to marine product, particularly the apparent measurement of scallop profile and the application aspect the record also Shang Weijian report is arranged.
Summary of the invention:
The objective of the invention is to overcome the shortcoming that exists in the existing apparent profile situation of the manual measurement marine product technology, seeking to design provides a kind of computing machine that utilizes that the profile apparent situation of scallop is measured and record automatically, and and then its data are handled, realize the automatic measurement effect.
To achieve these goals, the present invention measures and record automatically to phenotypic characters of scallop, utilize image recognition technology in computer, scallop shell size proterties to be measured and handled, and be connected with electronic balance by serial ports of computers, the body weight of record scallop, DATA REASONING, record and typing computer are carried out data processing finish simultaneously, measuring process rapidly, has accurately improved the measurement and the writing speed of phenotypic characters of scallop.
Measurement of the present invention comprises image acquisition, image pre-service, profile identification, dimensional measurement, dimension conversion and deposits six steps of database in the record flow process; Adopt two high definition cameras to carry out image acquisition earlier, two cameras are fixed on the outer fixedly shelf of electronic balance cloche, one of them cam lens is over against the pallet of electronic balance, another camera has long handle, camera lens is aimed at the pallet of electronic balance from the side, utilize DirectX to start two cameras automatically and take pictures simultaneously, preserve the image of scallop front and side; Employing is based on C
#The two dimensional image recognition technology be divided into that original image is handled, key point is searched with three of range observations step by step; Original image is handled and to be divided into three sections of gray processing, binaryzation and denoisings again; Wherein gray processing is that the color information of image is all lost, and 24 message bit patterns are represented with 8, and gray-scale map has 256 grades of gray shade scales, just with 24 bitmaps a bit as (255,255,255) convert 255 to, so R, G, the coefficient that three values of B are taken advantage of and be 1; Binaryzation is that the gray level image of 256 brightness degrees is chosen the binary image that obtains still can reflect integral image and local feature by threshold values; Denoising is to carry out image denoising with wavelet analysis, and 3 steps are arranged: the one, picture intelligence is carried out wavelet decomposition; The 2nd, to carrying out threshold value quantizing through the high frequency coefficient after the Hiberarchy Decomposition; The 3rd, utilize 2-d wavelet reconstructed image signal; The searching of key point is divided into obtains edge contour and extracts key point; Range observation is the pixel count that directly calculates between the key point, becomes millimeter by default pixel with the ratiometric conversion of millimeter again; Thereby directly read the record that the balance data realize weight by serial ports.
The present invention is at balance outside fixed support, camera is fixed on the support, camera is connected on computers by data line with electronic balance, utilizes computer image recognition technology identification photo and measures in photo that shell height, the shell of scallop is long, shell is wide, simultaneously the recording balance reading; Place the top of electronic balance and the front figure that the side is write down scallop respectively respectively with two cameras during realization, and balance is linked to each other with computer by data line; After equipment sets up and finishes, start software, opening camera selects corresponding balance port and chooses the survey record option simultaneously of weighing, balance is returned to zero, put scallop, treat the printing key of the stable back of balance reading by balance, software will read the balance registration automatically and take pictures measure the shell height automatically, shell is long and shell is wide.
The present invention compared with prior art, it is simple, safe and reliable that it measures device therefor, measures and record automaticity height, quantity handles rapidly, accurately, the phenotypic character that can be widely used in the variety classes scallop is measured and record fast.
Description of drawings:
Fig. 1 is measurement of the present invention and recording process flow process and schematic block diagram.
Fig. 2 is image pre-service of the present invention and key point identification process synoptic diagram.
Embodiment:
Also be described further in conjunction with the accompanying drawings below by embodiment.
Embodiment:
The operational scheme of present embodiment comprises image acquisition, image pre-service, profile identification, dimensional measurement, dimension conversion and deposits six steps of database in; Adopt two high definition cameras to carry out image acquisition earlier, two cameras are fixed on the outer fixedly shelf of electronic balance cloche, one of them cam lens is over against the pallet of electronic balance, another camera has long handle, camera lens is aimed at the pallet of electronic balance from the side, utilize DirectX to start two cameras automatically and take pictures simultaneously, preserve the image of scallop front and side; Employing is based on C
#The two dimensional image recognition technology, be divided into that original image is handled, key point is searched with three of range observations step by step; Original image is handled and to be divided into three sections of gray processing, binaryzation and denoisings again; (1) gray processing: the color information of image is all lost, 24 message bit patterns are represented with 8, gray-scale map has 256 grades of gray shade scales, just with 24 bitmaps a bit as (255,255,255) convert 255 to, so R, G, the coefficient that three values of B are taken advantage of and be 1; (2) binaryzation: the gray level image of 256 brightness degrees is chosen the binary image that obtains still can reflect integral image and local feature by threshold values; (3) denoising: wavelet analysis carries out image denoising and mainly contains 3 steps: (a) picture intelligence is carried out wavelet decomposition; (b) to carrying out threshold value quantizing through the high frequency coefficient after the Hiberarchy Decomposition; (c) utilize 2-d wavelet reconstructed image signal.
The searching of the key point that present embodiment relates to is divided into obtains edge contour and extracts key point; Range observation is the distance of directly calculating between the key point (pixel count), becomes millimeter by default pixel with the ratiometric conversion of millimeter again; Thereby directly read the record that the balance data realize weight by serial ports.
Claims (1)
1. a phenotypic characters of scallop by computer is measured and recording method, it is characterized in that measuring with the record flow process comprising image acquisition, image pre-service, profile identification, dimensional measurement, dimension conversion and depositing six steps of database in; Adopt two high definition cameras to carry out image acquisition earlier, two cameras are fixed on the outer fixedly shelf of electronic balance cloche, one of them cam lens is over against the pallet of electronic balance, another camera has long handle, camera lens is aimed at the pallet of electronic balance from the side, utilize DirectX to start two cameras automatically and take pictures simultaneously, preserve the image of scallop front and side; Employing is based on C
#The two dimensional image recognition technology be divided into that original image is handled, key point is searched with three of range observations step by step; Original image is handled and to be divided into three sections of gray processing, binaryzation and denoisings again; Wherein gray processing is that the color information of image is all lost, and 24 message bit patterns are represented with 8, and gray-scale map has 256 grades of gray shade scales, with 24 bitmaps a bit as (255,255,255) convert 255 to, R, G, the coefficient that three values of B are taken advantage of and be 1; Binaryzation is that the gray level image of 256 brightness degrees is chosen the binary image that obtains to reflect integral image and local feature by threshold values; Denoising is to carry out image denoising with wavelet analysis, and 3 steps are arranged: the one, picture intelligence is carried out wavelet decomposition; The 2nd, to carrying out threshold value quantizing through the high frequency coefficient after the Hiberarchy Decomposition; The 3rd, utilize 2-d wavelet reconstructed image signal; The searching of key point is divided into obtains edge contour and extracts key point; Range observation is distance or the pixel count that directly calculates between the key point, becomes millimeter by default pixel with the ratiometric conversion of millimeter again; Directly read the record that the balance data realize weight by serial ports.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102374888A (en) * | 2010-08-17 | 2012-03-14 | 周大福珠宝金行（深圳）有限公司 | Method for automatically weighing ornaments and control device |
| CN102435278A (en) * | 2011-09-30 | 2012-05-02 | 常熟市佳衡天平仪器有限公司 | Balance with real object identifying function |
| CN103426164A (en) * | 2013-06-09 | 2013-12-04 | 大连海事大学 | Scallop dimension calculating method based on Opencv image analysis and scallop sorting system |
| CN103591887A (en) * | 2013-09-30 | 2014-02-19 | 北京林业大学 | Method for detecting regional phenotype of Arabidopsis |
| CN105066885A (en) * | 2015-07-11 | 2015-11-18 | 浙江大学宁波理工学院 | Fish body dimension and weight rapid acquisition apparatus and acquisition method |
| CN105486352A (en) * | 2016-01-14 | 2016-04-13 | 广东工业大学 | Comprehensive detecting device and comprehensive detecting method for equivalent characteristic information of shells |
| CN111521128A (en) * | 2020-04-15 | 2020-08-11 | 中国科学院海洋研究所 | Shellfish external form automatic measurement method based on optical projection |
| CN112634350A (en) * | 2020-12-26 | 2021-04-09 | 中国水产科学研究院黄海水产研究所 | Intelligent image measurement and analysis system, method, medium, equipment and application |
-
2009
- 2009-12-03 CN CN200910231574A patent/CN101709951A/en active Pending
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102374888A (en) * | 2010-08-17 | 2012-03-14 | 周大福珠宝金行（深圳）有限公司 | Method for automatically weighing ornaments and control device |
| CN102374888B (en) * | 2010-08-17 | 2013-04-10 | 周大福珠宝金行（深圳）有限公司 | Method for automatically weighing ornaments and control device |
| CN102435278A (en) * | 2011-09-30 | 2012-05-02 | 常熟市佳衡天平仪器有限公司 | Balance with real object identifying function |
| CN103426164A (en) * | 2013-06-09 | 2013-12-04 | 大连海事大学 | Scallop dimension calculating method based on Opencv image analysis and scallop sorting system |
| CN103426164B (en) * | 2013-06-09 | 2016-01-13 | 大连海事大学 | Based on scallop size computing method and the scallop sorting system of Opencv graphical analysis |
| CN103591887A (en) * | 2013-09-30 | 2014-02-19 | 北京林业大学 | Method for detecting regional phenotype of Arabidopsis |
| CN103591887B (en) * | 2013-09-30 | 2016-06-15 | 北京林业大学 | A kind of detection method of arabidopsis region phenotype |
| CN105066885A (en) * | 2015-07-11 | 2015-11-18 | 浙江大学宁波理工学院 | Fish body dimension and weight rapid acquisition apparatus and acquisition method |
| CN105486352A (en) * | 2016-01-14 | 2016-04-13 | 广东工业大学 | Comprehensive detecting device and comprehensive detecting method for equivalent characteristic information of shells |
| CN105486352B (en) * | 2016-01-14 | 2019-08-16 | 广东工业大学 | A kind of comprehensive detection device and method of shell equivalent features information |
| CN111521128A (en) * | 2020-04-15 | 2020-08-11 | 中国科学院海洋研究所 | Shellfish external form automatic measurement method based on optical projection |
| CN112634350A (en) * | 2020-12-26 | 2021-04-09 | 中国水产科学研究院黄海水产研究所 | Intelligent image measurement and analysis system, method, medium, equipment and application |
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Open date: 20100519 |