CN109013386B - Bird's nest feather picking device and method based on machine vision - Google Patents
Bird's nest feather picking device and method based on machine vision Download PDFInfo
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- CN109013386B CN109013386B CN201810785510.2A CN201810785510A CN109013386B CN 109013386 B CN109013386 B CN 109013386B CN 201810785510 A CN201810785510 A CN 201810785510A CN 109013386 B CN109013386 B CN 109013386B
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- 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
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- 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
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
- B07C5/362—Separating or distributor mechanisms
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- 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
- B07C2501/0063—Using robots
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- 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
- B07C2501/0081—Sorting of food items
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Abstract
The invention discloses a bird's nest feather picking device and method based on machine vision. The bird's nest feather picking device based on machine vision is simple in structure and low in manufacturing cost, and can effectively pick light and tiny feathers; the picking method can quickly and accurately finish the identification of a large number of feather characteristics, can quickly grasp the feather characteristics, is particularly suitable for the field of robot automatic production lines, and has high production efficiency. The picking device provided by the invention also has the advantages of simple structure, convenience in operation and easiness in implementation.
Description
Technical Field
The invention relates to the technical field of machine vision, in particular to a bird's nest feather picking device and method based on machine vision.
Background
The existing technology for picking the feathers in the natural bird nest mainly comprises the steps of manually picking and clamping the feathers from the natural bird nest by using tweezers, and the cost of one person of the natural bird nest to complete picking is approximately 3 to 5 hours due to the complexity of the picking process. In another hair picking mode, bird's nest is soaked in a free state and then is manually picked, so that a large amount of bird's nest is lost, and the nutritional ingredients of natural bird's nest are damaged.
The existing four-axis serial and parallel robot mainly realizes the movement and carrying modes of objects due to the special structure of the robot, and is difficult to realize the grabbing operation of the objects. Therefore, there is a need for a simple and lightweight robotic end effector for performing grasping and picking operations on objects.
The machine vision technology can sort out the feature objects to be processed from the objects by identifying the feature objects and controlling the positioning and grabbing of automatic equipment such as robots. Because of the advantages of high automation integration level, convenience and rapidness, the method is widely applied to the field of the current automatic production line, particularly the field of the robot automation technology, not only shortens the production period of the product, but also improves the quality and efficiency of the product production.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a bird's nest feather picking device based on machine vision, which has a simple structure.
Another object of the present invention is to overcome the drawbacks of the prior art and to provide a picking method based on the above-mentioned picking device.
The aim of the invention is achieved by the following technical scheme:
the utility model provides a bird's nest feather pick device based on machine vision, covers feather pick device mainly including the tight extraction element of clamp that is used for picking the feather, be used for blowing off the air nozzle of feather, be used for discernment feather characteristic and drive to press from both sides tight extraction element and air nozzle work's control unit, and flattening hold-down frame. The leveling compacting frame is fixedly connected with the mechanical arm. The clamping extraction part and the air nozzle are both arranged on the leveling compaction frame. The control unit is arranged at a height of 600 mm above the picking station and is respectively connected with the clamping extraction part and the air nozzle in a driving way.
Specifically, the leveling compacting frame mainly comprises a base, a supporting rod and a pressing plate, wherein the base and the supporting rod are sequentially arranged from top to bottom, and the pressing plate is used for pressing micro-soaked cubilose. The base is fixedly connected with the mechanical arm. The upper end of the supporting rod is fixedly connected with the bottom of the base, and the lower end of the supporting rod is fixed with the pressing plate. The clamp plate middle part is equipped with the notch that is used for pressing from both sides to get the feather, the notch is located and presss from both sides tight extraction element directly under.
Specifically, the clamping extraction part comprises a lifting cylinder, an air pipe joint, a push plate, a connecting plate, an opening and closing cylinder, a sliding block and a clamp. The lifting cylinder is downwards arranged at the bottom of the base, and the output end of the lifting cylinder is fixedly connected with the push plate. The top of the connecting plate is fixed with the push plate, and the bottom of the connecting plate is fixedly connected with the opening and closing cylinder. The sliding blocks are arranged on the opening and closing cylinders in pairs, so that the opening and closing cylinders drive the sliding blocks to move in opposite directions or in opposite directions. The clamps are respectively arranged on the sliding blocks, so that the sliding blocks drive the clamps to clamp or release feathers. The air pipe joint is respectively arranged on the lifting cylinder and the opening and closing cylinder and is connected with an external high-pressure air pipe.
Specifically, the air nozzle comprises an air nozzle and an air nozzle bracket. One end of the air tap bracket is clamped on the supporting rod, and the other end of the air tap bracket clamps the air tap. The air outlet of the air tap faces the clip, and the air inlet is connected with an external high-pressure air pipe.
Specifically, the control unit comprises a camera for acquiring bird's nest images, a lens, a visual light source and a controller for processing image information and driving the clamping extraction part and the air nozzle. The controller is respectively and electrically connected with the camera and the visual light source, and the controller is respectively and drivingly connected with the lifting cylinder, the opening and closing cylinder and the air nozzle. The visual light source vertically irradiates on the bird's nest, and the camera is aligned to the bird's nest to be picked through the lens.
As a preferable scheme of the invention, in order to improve the size and the clamping efficiency of the clamping opening of the picking device, the notch adopts a rectangular design, the length is 16 mm, the width is 2mm, and the depth is the penetrating pressing plate.
Furthermore, in order to facilitate the connection and installation of the starting device, the top of the base is provided with two grooves which are convenient for connecting an external high-pressure air pipe. One end of the slot is arranged in the center of the base, and the other end of the slot extends to the edge of the base.
As a preferable scheme of the invention, in order to conveniently adjust the gap between the two clamps, the connecting interface between the clamps and the sliding block is a U-shaped notch which is convenient for adjusting the gap size in the clamping state.
As a preferable scheme of the invention, in order to improve the probability of successful feather clamping of the clamps, 8 mutually staggered teeth are arranged at the lower ends of the clamps.
As a preferred embodiment of the present invention, the camera is an industrial CCD color RGB camera; the visual light source adopts an LED light source.
The other object of the invention is achieved by the following technical scheme:
a bird's nest feather picking method based on machine vision mainly comprises the following steps:
step S1: and (3) image acquisition, namely vertically and parallelly irradiating a direct-current LED light source on the soaked natural bird's nest, and shooting and acquiring bird's nest images by using an industrial CCD color camera at a rate of 30 frames per second.
Step S2: and (3) feather feature identification, namely carrying out gray level binarization and morphological pretreatment on the acquired bird's nest image, reducing interference of micro holes and flaws in the image, and then identifying feather features through a threshold segmentation algorithm.
Step S3: and (3) positioning feather features, extracting the contours of the identified feather features based on an edge extraction algorithm, calculating the barycenter coordinates of the contour image, and obtaining the pose of the feather features under the robot base coordinates through coordinate transformation.
Step S4: the picking device is used for grabbing, and the lifting cylinder and the opening and closing cylinder of the tail end picking device of the robot are controlled to act according to the pose of the obtained feather outline centroid under the robot base coordinates, so that the clamp is driven to grab the feathers.
Step S5: the feathers are blown off and recycled, the robot is controlled to position the clamped feathers above the water tank, high-pressure gas is blown out by utilizing a gas pipe on the air nozzle, the feathers in the clamp are blown down into the water tank, and separation and recycling are performed again.
As a preferable scheme of the invention, the morphological pretreatment in the step S2 adopts a corrosion and expansion algorithm, so that the influence of misidentification of non-feather characteristics and micro-feather leakage identification is reduced.
As a preferable scheme of the invention, the threshold segmentation algorithm in the step S2 adopts multi-level threshold segmentation, so that feather characteristics with different sizes can be fully identified.
Compared with the prior art, the invention has the following advantages:
(1) The bird's nest feather picking device based on machine vision has the advantages of compact structure, light weight, convenience and high response speed, and can be applied to the field of robot automated production to improve the efficiency and quality of product production.
(2) According to the bird's nest feather picking device based on machine vision, the lifting cylinder and the opening and closing cylinder are installed in a 90-degree staggered mode through the connecting plate, the two sliding blocks fixed on the sliding rail of the opening and closing cylinder are always symmetrical when moving, and the lower end of the clamp is provided with the mutually staggered teeth, so that feathers can be effectively picked out.
(3) The bird's nest feather picking device based on machine vision provided by the invention can accurately and rapidly identify feather characteristics, and drive a robot and the tail end picking device of the robot to rapidly pick and pick feathers.
Drawings
Fig. 1 is a schematic structural diagram of a bird's nest feather picking device based on machine vision.
Fig. 2 is a schematic diagram of a clamping state of the bird's nest feather picking device based on machine vision.
Fig. 3 is an initial state cross-sectional view of the bird's nest feather picking device based on machine vision provided by the invention.
Fig. 4 is a sectional view of a blown-off feather state of the bird's nest feather picking device based on machine vision.
Fig. 5 is a workflow diagram of a bird's nest feather picking method based on machine vision provided by the invention.
The reference numerals in the above figures illustrate:
1-leveling compacting frame, 2-lifting cylinder, 3-air pipe connector, 4-push plate, 5-connecting plate, 6-opening and closing cylinder, 7/8-sliding block, 9-air tap bracket, 10-air tap, 11-notch, 12/13-clip, 14-pressure plate, 15-support bar and 16-base.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear and clear, the present invention will be further described below with reference to the accompanying drawings and examples.
Example 1:
as shown in fig. 1 to 5, the present embodiment discloses a bird's nest feather picking device based on machine vision, and the cover feather picking device mainly includes a clamping extraction part for picking up feathers, an air nozzle for blowing off feathers, a control unit for recognizing feather characteristics and driving the clamping extraction part and the air nozzle to work, and a leveling compaction frame 1. The leveling compaction frame 1 is fixedly connected with the mechanical arm. The clamping extraction part and the air nozzle are both arranged on the leveling compaction frame 1. The control unit is arranged at a height of 600 mm above the picking station and is respectively connected with the clamping extraction part and the air nozzle in a driving way.
Specifically, the leveling compacting frame 1 mainly includes a base 16, a supporting rod 15, and a pressing plate 14 for pressing the micro-soaked nidus Collocaliae, which are sequentially arranged from top to bottom. The base 16 is fixedly connected with the mechanical arm. The upper end of the supporting rod 15 is fixedly connected with the bottom of the base 16, and the lower end is fixed with the pressing plate 14. The middle part of the pressing plate 14 is provided with a notch 11 for clamping feathers, and the notch 11 is positioned right below the clamping extraction part.
Specifically, the clamping extraction part comprises a lifting cylinder 2, an air pipe joint 3, a push plate 4, a connecting plate 5, an opening and closing cylinder 6, a sliding block 7/8 and a clamp 12/13. The lifting cylinder 2 is downwards arranged at the bottom of the base 16, and the output end of the lifting cylinder is fixedly connected with the push plate 4. The top of the connecting plate 5 is fixed with the push plate 4, and the bottom is fixedly connected with the opening and closing cylinder 6. The sliding blocks 7/8 are arranged on the opening and closing air cylinders 6 in pairs, so that the opening and closing air cylinders 6 drive the sliding blocks 7/8 to move in opposite directions or in opposite directions. The clamps 12/13 are respectively arranged on the sliding blocks 7/8, so that the sliding blocks 7/8 drive the clamps 12/13 to clamp or release feathers. The air pipe joint 3 is respectively arranged on the lifting air cylinder 2 and the opening and closing air cylinder 6 and is connected with an external high-pressure air pipe.
Specifically, the air nozzle comprises an air nozzle 10 and an air nozzle bracket 9. One end of the air tap bracket 9 is clamped on the supporting rod 15, and the other end clamps the air tap 10. The air outlet of the air tap 10 faces the clamp 12/13, and the air inlet is connected with an external high-pressure air pipe.
Specifically, the control unit comprises a camera for acquiring bird's nest images, a lens, a visual light source and a controller for processing image information and driving the clamping extraction part and the air nozzle. The controller is respectively and electrically connected with the camera and the visual light source, and is respectively and drivingly connected with the lifting cylinder 2, the opening and closing cylinder 6 and the air tap 10. The visual light source vertically irradiates on the bird's nest, and the camera is aligned to the bird's nest to be picked through the lens.
As a preferred embodiment of the present invention, in order to increase the size and efficiency of the clamping opening of the picking device, the slot 11 of the present invention is rectangular, and has a length of 16 mm, a width of 2mm, and a depth penetrating the platen 14.
Further, in order to facilitate the connection and installation of the starting device, the top of the base 16 is provided with two slots for facilitating the connection of an external high-pressure air pipe. One end of the slot is arranged in the center of the base 16, and the other end extends to the edge of the base 16.
As a preferable scheme of the invention, in order to conveniently adjust the gap between the two clamps 12/13, the connecting interface between the clamps 12/13 and the sliding blocks 7/8 is provided with a U-shaped notch 11 which is convenient for adjusting the gap size in the clamping state.
As a preferable scheme of the invention, in order to improve the probability of successfully clamping the feathers by the clamps 12/13, 8 mutually staggered teeth are arranged on the lower ends of the clamps 12/13.
As a preferred embodiment of the present invention, the camera is an industrial CCD color RGB camera; the visual light source adopts an LED light source.
The embodiment also discloses a bird's nest feather picking method based on machine vision, which mainly comprises the following steps:
step S1: and (3) image acquisition, namely vertically and parallelly irradiating a direct-current LED light source on the soaked natural bird's nest, and shooting and acquiring bird's nest images by using an industrial CCD color camera at a rate of 30 frames per second.
Step S2: and (3) feather feature identification, namely carrying out gray level binarization and morphological pretreatment on the acquired bird's nest image, reducing interference of micro holes and flaws in the image, and then identifying feather features through a threshold segmentation algorithm.
Step S3: and (3) positioning feather features, extracting the contours of the identified feather features based on an edge extraction algorithm, calculating the barycenter coordinates of the contour image, and obtaining the pose of the feather features under the robot base coordinates through coordinate transformation.
Step S4: the picking device is used for grabbing, and the lifting cylinder 2 and the opening and closing cylinder 6 of the tail end picking device of the robot are controlled to act according to the pose of the obtained feather outline centroid under the robot base coordinates, so that the clamps 12/13 are driven to grab the feathers.
Step S5: the feathers are blown off and recycled, the robot is controlled to position the clamped feathers above the water tank, high-pressure gas is blown out by utilizing a gas pipe on the gas nozzle, the feathers in the clamps 12/13 are blown down into the water tank, and separation and recycling are performed again.
As a preferable scheme of the invention, the morphological pretreatment in the step S2 adopts a corrosion and expansion algorithm, so that the influence of misidentification of non-feather characteristics and micro-feather leakage identification is reduced.
As a preferable scheme of the invention, the threshold segmentation algorithm in the step S2 adopts multi-level threshold segmentation, so that feather characteristics with different sizes can be fully identified.
Example 2:
as shown in fig. 5, an industrial CCD camera is used for acquiring and collecting images of natural bird's nest placed under a visual light source, a machine vision algorithm is used for identifying feather features, a driving robot is used for positioning the feather features, and then the bird's nest feather picking device based on machine vision provided by the invention is used for picking feathers, clamping the feathers and moving to a designated position for blowing and recycling.
As shown in fig. 1, a bird's nest feather picking device based on machine vision includes: a leveling compaction frame 1 which in turn comprises a base 16, a support bar 15 and a pressure plate 14; the clamping and extracting device comprises a lifting cylinder 2, a connecting plate 5, an opening and closing cylinder 6, a clamp 12 and a clamp 13; the air nozzle comprises an air nozzle 10 and an air nozzle bracket 9.
The base 16 is fixedly connected with the tail end of the robot, the pressing plate 14 is fixedly connected with the base 16 through the middle supporting rod 15, so that the pressing plate 14 can downwards press the bird's nest along with the tail end of the robot, the bird's nest after micro-soaking can be in a flat state, and the picking of hairs is facilitated.
The middle of the pressing plate 14 is provided with a 16 x 2mm notch for the clamp to clamp the feather through, and ensure that the bird's nest attached to the feather is not clamped out.
The lifting cylinder 2 further comprises two air pipe joints 3 and a push plate 4, and the lifting and descending of the push plate 4 are controlled by controlling the air inlet and air outlet states of the two air pipe joints.
As shown in fig. 2 and 3, the lifting cylinder 2 and the opening and closing cylinder 6 are connected in a 90-degree staggered manner through the connecting plate 5, and the push plate 4 is fixedly connected with the connecting plate 5, so that the opening and closing cylinder 6 can ascend and descend along with the push plate 4.
The opening and closing cylinder 6 further comprises a sliding block 7, a sliding block 8 and two air pipe joints 3 which are fixed on the sliding rail, and the sliding block 7 and the sliding block 8 are symmetrically opened and closed on the sliding rail by controlling the air inlet and outlet states of the two air pipe joints 3.
The clips 12 and 13 are fixed to the slider 7 and the slider 8, respectively, and open and close together with the slider 7 and the slider 8.
As shown in fig. 4, the air tap 10 is fixed on the air tap bracket 9, the air tap bracket 9 is fixed on the supporting rod 15 of the leveling compacting frame, and can rotate 360 degrees around the supporting rod, so that the direction of blowing off the feathers can be adjusted arbitrarily.
The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.
Claims (9)
1. The bird's nest feather picking device based on machine vision is characterized by comprising a clamping extraction part for picking feathers, an air nozzle for blowing off the feathers, a control unit for identifying feather characteristics and driving the clamping extraction part and the air nozzle to work, and a leveling compaction frame; the leveling compacting frame is fixedly connected with the mechanical arm; the clamping extraction part and the air nozzle are both arranged on the leveling compaction frame; the control unit is arranged at a height of 600 mm above the picking station and is respectively connected with the clamping extraction part and the air nozzle in a driving way;
the leveling compaction frame comprises a base, a supporting rod and a pressing plate, wherein the base, the supporting rod and the pressing plate are sequentially arranged from top to bottom; the base is fixedly connected with the mechanical arm; the upper end of the supporting rod is fixedly connected with the bottom of the base, and the lower end of the supporting rod is fixed with the pressing plate; the middle part of the pressing plate is provided with a notch for clamping feathers, and the notch is positioned right below the clamping extraction part;
the clamping extraction part comprises a lifting cylinder, an air pipe joint, a push plate, a connecting plate, an opening and closing cylinder, a sliding block and a clamp; the lifting cylinder is downwards arranged at the bottom of the base, and the output end of the lifting cylinder is fixedly connected with the push plate; the top of the connecting plate is fixed with the push plate, and the bottom of the connecting plate is fixedly connected with the opening and closing cylinder; the sliding blocks are arranged on the opening and closing cylinders in pairs, so that the opening and closing cylinders drive the sliding blocks to move in opposite directions or in opposite directions; the clamps are respectively arranged on the sliding blocks, so that the sliding blocks drive the clamps to clamp or release feathers; the air pipe joint is respectively arranged on the lifting cylinder and the opening and closing cylinder and is connected with an external high-pressure air pipe;
the air nozzle comprises an air nozzle and an air nozzle bracket; one end of the air tap bracket is clamped on the supporting rod, and the other end of the air tap bracket clamps the air tap; the air outlet of the air tap faces the clip, and the air inlet is connected with an external high-pressure air pipe;
the control unit comprises a camera, a lens, a visual light source and a controller, wherein the camera is used for acquiring bird's nest images, and the controller is used for processing image information and driving the clamping extraction part and the air nozzle; the controller is respectively and electrically connected with the camera and the visual light source, and is respectively and drivingly connected with the lifting cylinder, the opening and closing cylinder and the air tap; the visual light source vertically irradiates on the bird's nest, and the camera is aligned to the bird's nest to be picked through the lens.
2. The machine vision based bird's nest feather picking device of claim 1, wherein the slot is of rectangular design, has a length of 16 mm, a width of 2mm, and a depth of through-going platen.
3. The bird's nest feather picking device based on machine vision according to claim 1, wherein two grooves which are convenient to connect with an external high-pressure air pipe are formed in the top of the base, one end of each groove is arranged in the center of the base, and the other end of each groove extends to the edge of the base.
4. The machine vision based bird's nest feather picking device of claim 1, wherein the connection interface between the clip and the slider is provided as a U-shaped slot that facilitates adjustment of the gap size when in a clamped state.
5. The machine vision based bird's nest feather picking device of claim 1, wherein a pair of said clips are provided with 8 staggered teeth on their lower ends.
6. The machine vision based bird's nest feather picking device of claim 1, wherein the camera employs an industrial CCD color RGB camera; the visual light source adopts an LED light source.
7. A bird's nest feather picking method based on machine vision is characterized by comprising the following steps:
step S1: the method comprises the steps of image acquisition, namely vertically and parallelly irradiating a direct-current LED light source on soaked natural bird's nest, and shooting and acquiring bird's nest images by using an industrial CCD color camera at a rate of 30 frames per second;
step S2: feather feature identification, namely carrying out gray level binarization and morphological pretreatment on an acquired bird's nest image, reducing interference of micro holes and flaws in the image, and then identifying feather features through a threshold segmentation algorithm;
step S3: the feather feature is positioned, the recognized feather feature is subjected to contour extraction based on an edge extraction algorithm, the centroid coordinates of a contour image are calculated, and the pose of the feather feature under the robot base coordinates is obtained through coordinate transformation;
step S4: the picking device is used for grabbing, and the lifting cylinder and the opening and closing cylinder of the tail end picking device of the robot are controlled to act according to the pose of the obtained feather outline centroid under the robot base coordinates, so that the clamp is driven to grab the feathers;
step S5: the feathers are blown off and recycled, the robot is controlled to position the clamped feathers above the water tank, high-pressure gas is blown out by utilizing a gas pipe on the air nozzle, the feathers in the clamp are blown down into the water tank, and separation and recycling are performed again.
8. The machine vision based bird' S nest feather picking method according to claim 7, wherein the morphological preprocessing in step S2 adopts a corrosion and expansion algorithm, so as to reduce the effects of misrecognition of non-feather features and fine feather leakage recognition.
9. The machine vision-based bird' S nest feather picking method according to claim 7, wherein the threshold segmentation algorithm in the step S2 adopts multi-level threshold segmentation, so that feather features with different sizes can be sufficiently identified.
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| CN109701893B (en) * | 2019-01-02 | 2020-08-28 | 广州南颐贸易有限公司 | Instant edible bird's nest intelligent processing system |
| CN109834081A (en) * | 2019-01-23 | 2019-06-04 | 广东工业大学 | Intelligent bird's nest poacher |
| CN112772910A (en) * | 2021-01-11 | 2021-05-11 | 南宁海关技术中心 | Efficient cubilose hair picking system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08240537A (en) * | 1995-03-01 | 1996-09-17 | Toray Eng Co Ltd | Feather inspection device |
| JP2003311670A (en) * | 2002-04-17 | 2003-11-05 | Denso Wave Inc | Positioning control method of robot arm and robot equipment |
| JP2006341959A (en) * | 2005-06-09 | 2006-12-21 | Tokyo Univ Of Science | Feather conveying device and feather sorting device |
| CN103111062A (en) * | 2013-02-27 | 2013-05-22 | 南通大学 | Full-automatic goose feather sorting and ironing integrated system |
| CN105154988A (en) * | 2015-08-10 | 2015-12-16 | 安徽工程大学 | Apparatus automatically extracting down feather and extracting method |
| CN106651882A (en) * | 2016-12-29 | 2017-05-10 | 广东工业大学 | Method and device for identifying and detecting cubilose impurities based on machine vision |
| CN209109636U (en) * | 2018-07-17 | 2019-07-16 | 广东工业大学 | A kind of bird's nest feather based on machine vision picks device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN211760896U (en) * | 2020-01-01 | 2020-10-27 | 安徽水瑾悦健康管理有限公司 | Edible bird's nest draws uses edulcoration device |
-
2018
- 2018-07-17 CN CN201810785510.2A patent/CN109013386B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08240537A (en) * | 1995-03-01 | 1996-09-17 | Toray Eng Co Ltd | Feather inspection device |
| JP2003311670A (en) * | 2002-04-17 | 2003-11-05 | Denso Wave Inc | Positioning control method of robot arm and robot equipment |
| JP2006341959A (en) * | 2005-06-09 | 2006-12-21 | Tokyo Univ Of Science | Feather conveying device and feather sorting device |
| CN103111062A (en) * | 2013-02-27 | 2013-05-22 | 南通大学 | Full-automatic goose feather sorting and ironing integrated system |
| CN105154988A (en) * | 2015-08-10 | 2015-12-16 | 安徽工程大学 | Apparatus automatically extracting down feather and extracting method |
| CN106651882A (en) * | 2016-12-29 | 2017-05-10 | 广东工业大学 | Method and device for identifying and detecting cubilose impurities based on machine vision |
| CN209109636U (en) * | 2018-07-17 | 2019-07-16 | 广东工业大学 | A kind of bird's nest feather based on machine vision picks device |
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