CN112871746A - Automatic red date screening method - Google Patents
Automatic red date screening method Download PDFInfo
- Publication number
- CN112871746A CN112871746A CN202110048903.7A CN202110048903A CN112871746A CN 112871746 A CN112871746 A CN 112871746A CN 202110048903 A CN202110048903 A CN 202110048903A CN 112871746 A CN112871746 A CN 112871746A
- Authority
- CN
- China
- Prior art keywords
- red dates
- image
- red
- gray value
- dates
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012216 screening Methods 0.000 title claims abstract description 27
- 230000007547 defect Effects 0.000 claims abstract description 10
- 239000000284 extract Substances 0.000 claims abstract description 3
- 230000037303 wrinkles Effects 0.000 claims description 8
- 230000009194 climbing Effects 0.000 claims description 6
- 239000000463 material Substances 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 3
- 230000000717 retained effect Effects 0.000 abstract 1
- 238000001514 detection method Methods 0.000 description 3
- 235000013399 edible fruits Nutrition 0.000 description 3
- 238000005286 illumination Methods 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 206010000496 acne Diseases 0.000 description 2
- 230000002950 deficient Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000003756 stirring Methods 0.000 description 2
- 240000008866 Ziziphus nummularia Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/04—Sorting according to size
- B07C5/10—Sorting according to size measured by light-responsive means
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
- B07C2501/009—Sorting of fruit
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/90—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in food processing or handling, e.g. food conservation
Landscapes
- Sorting Of Articles (AREA)
Abstract
The invention relates to the technical field of red date sorting, and discloses an automatic red date screening method, which comprises the following steps: s1, automatic feeding, S2, image acquisition, S3, image screening, S4 and sorting, wherein in the image screening, image processing software arranged in a computer extracts gray values of four images of the red dates in the circumferential direction, the gray values of the red dates in the four images, which are retained at the same position, are compared, the image with the gray value change within a set threshold value is marked as a normal red date, the image with the gray value change smaller than the set threshold value is marked as a broken opening, and the image with the gray value change larger than the set threshold value is marked as a skin deformation crack. The invention has the following advantages and effects: for the damaged and cracked parts of the red dates, the gray value change degree of the red dates is obviously different from the normal gray value change of the red dates, and the defect types of the red dates can be accurately judged through the gray value change difference.
Description
Technical Field
The invention relates to the technical field of red date sorting, in particular to an automatic red date screening method.
Background
The intelligent red date sorting machine is mainly used for classifying the defects and grade sizes of jun dates and ash dates, the detection technology of the fruit size sorting machine based on computer vision is mature, but the defect detection of the fruit surface is difficult for fruit classification, and the accurate and rapid determination of different defects such as blackheads, rotten losses, crevasses, cracks, deformation and the like on the surface of red dates is difficult.
Chinese patent with publication number CN 105268659B discloses a red date screening machine based on visual technology, which comprises: the red date sorting system is connected with the defective product eliminating system and can store the red dates with the defective products eliminated in a grading mode according to the size. This application adopts the stirring wheel to overturn the red date, contrasts the detection to the red date through two pictures of shooting the different angles of red date, and the red date is stirred to the stirring wheel, and red date pivoted angle is uncertain, and the whole outer peripheral face of red date can not be shot completely, and the red date both ends produce blackhead and rotten damage the easiest, and the circumference of red date can only be shot to this application, is difficult to gather and filter the image at red date both ends.
Disclosure of Invention
The invention aims to provide an automatic red date screening method which has the effects of high screening accuracy and high screening efficiency.
2. The technical purpose of the invention is realized by the following technical scheme: the method comprises the following steps:
s1, automatic feeding: red dates are placed in a storage hopper of a climbing machine, the red dates are conveyed to a material distribution hopper through the climbing machine, the material distribution hopper divides the red dates into two parts which respectively fall into a V-shaped groove, the red dates are arranged in the V-shaped groove end to end through vibration of a vibration motor and then fall onto conveying rollers of a conveying assembly one by one, and the conveying rollers autorotate under the action of brushes, so that the red dates on the conveying rollers are parallel to the conveying rollers and are relatively fixed between the two conveying rollers;
s2, image acquisition: a CCD camera in the image acquisition unit circumferentially acquires four images of the red dates according to a preset time interval, acquires left and right side views of two ends of the red dates and transmits acquired image information to a computer;
s3, image screening: extracting gray values of four images of the circumferential direction of the red dates by using image processing software arranged in the computer, setting the gray value of the smooth surface of the red dates to be 0 by taking the range of the gray value with the largest proportion in the red dates as the gray value of the smooth surface of the red dates, and regarding the gray value larger than the range as the wrinkle part of the red dates, and keeping the original gray value; then comparing the gray values reserved at the same position of the red dates in the four images, marking the image with the gray value change within a set threshold as a normal date, marking the image with the gray value change smaller than the set threshold as a breach, and marking the image with the gray value change larger than the set threshold as a skin deformation crack;
s4, sorting: the processing result of the image processing software arranged in the computer is transmitted to the PLC, the PLC control cavity controls the action of the electromagnetic valve according to the processing result to sort the corresponding red dates in real time, and the red dates with different damage types and the red dates with different grades are sent out from the corresponding sorting channels.
The invention is further provided with: in step S2, the interval time between the photographing of the CCD camera is equal to the time of 1/4 rotations of the red dates.
The invention is further provided with: in the step S3, the image processing software built in the computer extracts the left and right side views of the red dates, converts the RGB image model acquired by the CCD camera into an HIS image model, and screens the black head rot of the red dates by using an HIS color model.
The invention is further provided with: in the step S3, the computer embeds image processing software to extract four circumferential images of the red dates, the four-line scanning method is adopted to extract the long-diameter and short-diameter pixel values of the red dates in the images, the functional relationship between the real values of the long diameter and the short diameter of the red dates and the pixel values is fitted, a red date size grading model is built, and the red dates are divided into a special grade, a first grade, a second grade and a third grade according to the values of different long diameters and short diameters.
The invention is further provided with: the threshold set in the step S3 is trained by a large number of samples, and the distribution rule of the sample values is observed to obtain the threshold for measuring the defect types of the red dates.
The invention is further provided with: in step S3, after the image is extracted by the image processing software built in the computer, the image is first subjected to threshold segmentation by using a maximum variance threshold method, and the red date region image is separated from the background.
The invention has the beneficial effects that:
1. adopt the transfer roller to transmit the red date, set up the CCD camera in transfer roller both sides and can gather the image at red date both ends, the transfer roller can the rotation under the effect of brush to drive 360 rotations of red date, the rotational speed is comparatively invariable, through the frequency of shooing of adjusting the CCD camera, can shoot four global images of red date, can do not have the dead angle to the surface and the both ends of red date and detect, guarantee the accuracy of screening result.
2. The computer is internally provided with image processing software to analyze four images in the circumferential direction of the red dates, one image is acquired when the red dates rotate by 90 degrees, an image of 180 degrees of the upper surface of the red dates can be shot in each image, namely 50 percent of adjacent two images acquired by the CCD camera are overlapped, the gray value of the same part of the red dates is different under different rotation angles due to different shadows of the red dates at different rotation angles obtained by the red dates at different rotation angles because the angle of a light source in an illumination phase is fixed, the gray value change degree of the red dates is obviously different from the normal red date gray value change for the damaged and cracked parts of the red dates, pulp is exposed at the damaged part of the red dates, the gray value change is smaller under different illumination, the illumination angle is different for the cracked parts, the gray value change at the cracks is larger, and the defect types of the red dates can be accurately judged through the gray value change difference, the screening method is simple and has high accuracy.
3. The method has the advantages that the gray value of the red date smooth surface is set to be 0 at first, the numerical value of the red dates can be denoised first, screening accuracy is improved, the wrinkle position and the deformation crack position of the red dates are closer in gray value, the red date wrinkle position is difficult to distinguish only by the gray value, the gray value of the red date wrinkle position is reserved, then the difference value of the gray value of the wrinkle position in adjacent photos is compared, and wrinkles and deformation cracks can be effectively distinguished.
4. According to the automatic red date screening method, the defect condition of the red dates is judged through comparison of the gray values of the same red dates at different angles, different defects of the red dates can be accurately screened without complex calculation, and the accuracy and the screening efficiency of red date screening can be greatly improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a process schematic of the process of the present invention.
Detailed Description
The technical solution of the present invention will be clearly and completely described below with reference to specific embodiments. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
Example (b): an automatic red date screening method comprises the following steps:
s1, automatic feeding: red dates are placed in a storage hopper of a climbing machine, the red dates are conveyed to a material distribution hopper through the climbing machine, the material distribution hopper divides the red dates into two parts which respectively fall into a V-shaped groove, the red dates are arranged in the V-shaped groove end to end through vibration of a vibration motor and then fall onto conveying rollers of a conveying assembly one by one, and the conveying rollers autorotate under the action of brushes, so that the red dates on the conveying rollers are parallel to the conveying rollers and are relatively fixed between the two conveying rollers;
s2, image acquisition: a CCD camera in the image acquisition unit acquires four images in the circumferential direction of the red dates according to a preset time interval, acquires left and right side views of two ends of the red dates and transmits acquired image information to a computer, and the shooting interval time of the CCD camera is equal to 1/4 circles of time for the red dates to rotate;
s3, image screening:
s301, extracting gray values of four images of the red dates in the circumferential direction by using image processing software arranged in a computer;
s302, after the image is extracted by the image processing software arranged in the computer, firstly, the image is subjected to threshold segmentation by adopting a maximum variance threshold method, and the red date area image is separated from the background;
s303, setting the gray value of the smooth surface of the red dates to be 0 by taking the gray value range with the largest proportion of the red dates as the gray value of the smooth surface of the red dates, and regarding the gray value larger than the range as the wrinkle part of the red dates, and keeping the original gray value;
s304, comparing the gray values reserved at the same position of the red dates photographed in the four images;
s305, marking the image with the gray value change within the set threshold value as a normal jujube, marking the image with the gray value change smaller than the set threshold value as a breach, and marking the image with the gray value change larger than the set threshold value as a skin deformation crack;
setting a threshold, training by a large number of samples, and observing the distribution rule of the sample values to obtain the threshold for measuring the defect types of the red dates;
extracting left and right side views of red dates by using image processing software arranged in a computer, converting an RGB image model acquired by a CCD camera into an HIS image model, and screening the black head rotten loss of the red dates by using an HIS color model;
extracting four circumferential images of the red dates by using image processing software arranged in a computer, extracting long-diameter and short-diameter pixel values of the red dates in the images by adopting a four-line scanning method, fitting the functional relationship between the real values of the long diameter and the short diameter of the red dates and the pixel values, establishing a red date size grading model, and dividing the red dates into a special grade, a first grade, a second grade and a third grade according to the values of different long diameters and short diameters;
s4, sorting: the processing result of the image processing software arranged in the computer is transmitted to the PLC, the PLC control cavity controls the action of the electromagnetic valve according to the processing result to sort the corresponding red dates in real time, and the red dates with different damage types and the red dates with different grades are sent out from the corresponding sorting channels.
Claims (6)
1. An automatic red date screening method is characterized in that: the method comprises the following steps:
s1, automatic feeding: red dates are placed in a storage hopper of a climbing machine, the red dates are conveyed to a material distribution hopper through the climbing machine, the material distribution hopper divides the red dates into two parts which respectively fall into a V-shaped groove, the red dates are arranged in the V-shaped groove end to end through vibration of a vibration motor and then fall onto conveying rollers of a conveying assembly one by one, and the conveying rollers autorotate under the action of brushes, so that the red dates on the conveying rollers are parallel to the conveying rollers and are relatively fixed between the two conveying rollers;
s2, image acquisition: a CCD camera in the image acquisition unit circumferentially acquires four images of the red dates according to a preset time interval, acquires left and right side views of two ends of the red dates and transmits acquired image information to a computer;
s3, image screening: extracting gray values of four images of the circumferential direction of the red dates by using image processing software arranged in the computer, setting the gray value of the smooth surface of the red dates to be 0 by taking the range of the gray value with the largest proportion in the red dates as the gray value of the smooth surface of the red dates, and regarding the gray value larger than the range as the wrinkle part of the red dates, and keeping the original gray value; then comparing the gray values reserved at the same position of the red dates in the four images, marking the image with the gray value change within a set threshold as a normal date, marking the image with the gray value change smaller than the set threshold as a breach, and marking the image with the gray value change larger than the set threshold as a skin deformation crack;
s4, sorting: the processing result of the image processing software arranged in the computer is transmitted to the PLC, the PLC control cavity controls the action of the electromagnetic valve according to the processing result to sort the corresponding red dates in real time, and the red dates with different damage types and the red dates with different grades are sent out from the corresponding sorting channels.
2. The automatic red date screening method according to claim 1, wherein the method comprises the following steps: in step S2, the interval time between the photographing of the CCD camera is equal to the time of 1/4 rotations of the red dates.
3. The automatic red date screening method according to claim 1, wherein the method comprises the following steps: in the step S3, the image processing software built in the computer extracts the left and right side views of the red dates, converts the RGB image model acquired by the CCD camera into an HIS image model, and screens the black head rot of the red dates by using an HIS color model.
4. The automatic red date screening method according to claim 1, wherein the method comprises the following steps: in the step S3, the computer embeds image processing software to extract four circumferential images of the red dates, the four-line scanning method is adopted to extract the long-diameter and short-diameter pixel values of the red dates in the images, the functional relationship between the actual values of the long diameter and the short diameter of the red dates and the pixel values is fitted, a red date size grading model is established, and the red dates are divided into a special grade, a first grade, a second grade and a third grade according to the values of different long diameters and short diameters.
5. The automatic red date screening method according to claim 1, wherein the method comprises the following steps: the threshold set in the step S3 is trained by a large number of samples, and the distribution rule of the sample values is observed to obtain the threshold for measuring the defect types of the red dates.
6. The automatic red date screening method according to claim 1, wherein the method comprises the following steps: in step S3, after the image is extracted by the image processing software built in the computer, the image is first subjected to threshold segmentation by using a maximum variance threshold method, and the red date region image is separated from the background.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110048903.7A CN112871746B (en) | 2021-01-14 | 2021-01-14 | Automatic red date screening method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110048903.7A CN112871746B (en) | 2021-01-14 | 2021-01-14 | Automatic red date screening method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112871746A true CN112871746A (en) | 2021-06-01 |
CN112871746B CN112871746B (en) | 2023-10-20 |
Family
ID=76048734
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110048903.7A Active CN112871746B (en) | 2021-01-14 | 2021-01-14 | Automatic red date screening method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112871746B (en) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103185609A (en) * | 2011-12-29 | 2013-07-03 | 机械科学研究总院先进制造技术研究中心 | Image detecting method for grading of tomatoes |
KR101635460B1 (en) * | 2015-03-20 | 2016-07-01 | 최병훈 | Fruit sorting machine |
CN106311628A (en) * | 2016-08-29 | 2017-01-11 | 安徽兆晨农业科技发展有限公司 | Red jujube grading device |
CN108526043A (en) * | 2018-06-29 | 2018-09-14 | 天津工业大学 | A kind of machine classification equipment for jujube quality-screening based on deep learning |
CN112200826A (en) * | 2020-10-15 | 2021-01-08 | 北京科技大学 | Industrial weak defect segmentation method |
-
2021
- 2021-01-14 CN CN202110048903.7A patent/CN112871746B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103185609A (en) * | 2011-12-29 | 2013-07-03 | 机械科学研究总院先进制造技术研究中心 | Image detecting method for grading of tomatoes |
KR101635460B1 (en) * | 2015-03-20 | 2016-07-01 | 최병훈 | Fruit sorting machine |
CN106311628A (en) * | 2016-08-29 | 2017-01-11 | 安徽兆晨农业科技发展有限公司 | Red jujube grading device |
CN108526043A (en) * | 2018-06-29 | 2018-09-14 | 天津工业大学 | A kind of machine classification equipment for jujube quality-screening based on deep learning |
CN112200826A (en) * | 2020-10-15 | 2021-01-08 | 北京科技大学 | Industrial weak defect segmentation method |
Non-Patent Citations (1)
Title |
---|
李新疆;王赏贵;王丹;李扬;李疆;: "基于HSV色彩空间的红枣叶片病斑分割方法", 安徽农学通报, no. 04, pages 213 - 218 * |
Also Published As
Publication number | Publication date |
---|---|
CN112871746B (en) | 2023-10-20 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN100547394C (en) | Fruit quality detection system based on image information fusion technology | |
CN107203990B (en) | Label breakage detection method based on template matching and image quality evaluation | |
CN110403232B (en) | Cigarette quality detection method based on secondary algorithm | |
CN107966454A (en) | A kind of end plug defect detecting device and detection method based on FPGA | |
CN111266315A (en) | Ore material online sorting system and method based on visual analysis | |
CN106468668A (en) | Industrial camera cylinder detection method | |
CN112184648A (en) | Piston surface defect detection method and system based on deep learning | |
CN107328781A (en) | A kind of columnar product detection method of surface flaw and device based on machine vision | |
CN109461156B (en) | Threaded sealing plug assembly detection method based on vision | |
CN113894055A (en) | Hardware surface defect detection and classification system and method based on machine vision | |
CN104048966B (en) | The detection of a kind of fabric defect based on big law and sorting technique | |
CN111667475A (en) | Machine vision-based Chinese date grading detection method | |
CN111054655A (en) | Crab sorting device and application method thereof | |
CN106872473A (en) | A kind of potato defects detection identifying system design based on machine vision | |
CN104952754A (en) | Coated silicon chip sorting method based on machine vision | |
CN114113129B (en) | Lens micro defect recognition and grabbing system and method | |
CN111968082A (en) | Product packaging defect detection and identification method based on machine vision | |
CN113916127A (en) | Visual inspection system and method for appearance of valve guide pipe finished product | |
CN116441190A (en) | Longan detection system, method, equipment and storage medium | |
CN112871746A (en) | Automatic red date screening method | |
CN203069148U (en) | Finished magnetic ring image automatic detection system | |
CN107246841A (en) | A kind of multiple views grouping system device of auto parts and components | |
CN116740449A (en) | Shaving form detection method and system based on AI (advanced technology attachment) computer vision technology | |
CN208098654U (en) | The automatic detection device of cylindrical plug needle | |
CN116002330A (en) | Automatic test tube sorting device and automatic test tube sorting method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |