CN111242057A - Product sorting system, method, computer device and storage medium - Google Patents
Product sorting system, method, computer device and storage medium Download PDFInfo
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Abstract
The invention discloses a product sorting system, a method, computer equipment and a storage medium, wherein the system comprises an image acquisition module, a sorting module and a sorting module, wherein the image acquisition module is used for acquiring product images; the image processing module is used for acquiring the characteristic information and the position information of the product and judging whether the product is qualified or not; the communication module is used for transmitting all information of the products to the sorting module; and the sorting module is used for realizing product sorting. The method comprises the following steps: collecting an image of a product to be sorted; acquiring shape information of a product, judging whether the product is qualified, if so, executing the next step, and otherwise, executing the next step; acquiring color information of a product; acquiring position information of a product; and the sorting module is used for sorting the products according to all the information of the products. The computer device and the storage medium can implement the above-described method processes by executing a computer program. The invention acquires the product image based on the single camera and obtains the sorting information through image processing, so that the sorting can be accurately executed, the sorting efficiency is improved, and the labor cost is reduced.
Description
Technical Field
The invention belongs to the technical field of machine vision, particularly relates to the technical field of logistics sorting, and particularly relates to a product sorting system, a product sorting method, computer equipment and a storage medium.
Background
Machine vision is to use a machine to replace human eyes for measurement and judgment. The machine vision system converts the shot target into an image signal through a machine vision product and transmits the image signal to a special image processing system. The image processing is to process the image data by using a computer data processing technology to acquire the shape information of the shot object, including information such as pixel distribution, brightness, color and the like. The traditional machine vision identification scheme mostly adopts an artificial feature sorting mode, the detection robustness of artificial features to the conditions of random positions of articles, change of image visual angles, change of illumination, background interference and the like is poor, the method is time-consuming, only a small part of feature information in the images is used, the information utilization rate is low, and the actual detection effect is influenced to a great extent.
The information contained in an image is digital information of a large number of pixel points which are measured by tens of thousands or even higher orders; in a monochrome image, each pixel point only contains one type of gray information; in the color image, each pixel point contains brightness information of three colors of RGB. Processing such a huge amount of information, the process is quite complex, it is not practical if all machine vision researchers are working from the lowest level of processing, and the development time is too long and cost too high.
Disclosure of Invention
The invention aims to provide a product sorting system and method with the characteristics of high efficiency, high accuracy and the like.
The technical solution for realizing the purpose of the invention is as follows: a product sorting system comprises an image acquisition module, an image processing module, a communication module and a sorting module;
the image acquisition module is used for acquiring images of products to be sorted;
the image processing module is used for acquiring the characteristic information and the position information of the product to be sorted according to the acquired image and judging whether the product to be sorted is qualified or not;
the communication module is used for transmitting all information of the products to be sorted, which is acquired by the image processing module, to the sorting module;
and the sorting module is used for sorting the products to be sorted according to the received information.
Further, the image processing module includes:
the color identification unit is used for detecting the color information of the product to be sorted based on the HSV color space;
the qualified information detection unit is used for detecting the shape of the product to be sorted and realizing the detection of whether the product to be sorted is qualified or not based on the classifier;
and the positioning unit is used for detecting the position information of the product to be sorted.
Further, the sorting module comprises:
the control unit is used for receiving the information of the products to be sorted transmitted by the communication module and controlling the mechanical arm sorting unit to sort the products according to the information of the products to be sorted;
and the mechanical arm sorting unit is used for sorting the products under the control of the control unit.
A method of sorting products, the method comprising:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
Further, the step 2 of judging whether the product to be sorted is qualified according to the shape information specifically includes:
step 2-1, collecting a plurality of product images, extracting shape information and qualified information of each product to serve as training samples;
2-2, constructing a multilayer perceptron, and setting parameters of the multilayer perceptron, wherein the parameters comprise the number of input layers, output layers and hidden layers, an activation function and a preprocessing function;
2-3, training the multilayer perceptron by combining the training samples and the parameters of the multilayer perceptron;
2-4, extracting shape information of the product to be sorted according to the image of the product to be sorted;
and 2-5, taking the shape information of the product to be sorted as the input of the trained multilayer perceptron, and outputting a result whether the product to be sorted is qualified or not by the multilayer perceptron.
Further, step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted, specifically includes:
step 3-1, performing color gamut conversion on an image of a product to be sorted, and converting an RGB image into an HSV image;
and 3-2, performing threshold segmentation on the H-domain image to obtain the color of the product to be sorted.
Further, in step 4, acquiring the position information of the product to be sorted based on the image of the product to be sorted specifically includes:
step 4-1, obtaining coordinate values of the calibration plate in a camera coordinate system and a world coordinate system respectively;
step 4-2, establishing an affine transformation matrix between the camera coordinate system and the world coordinate system according to coordinate values of the calibration plate in the camera coordinate system and the world coordinate system respectively;
4-3, performing morphological processing and connected domain analysis on the image subjected to threshold segmentation in the step 3-2 to obtain the position of a product to be sorted in a camera coordinate system;
and 4-4, combining the position of the product to be sorted in the camera coordinate system with the affine transformation matrix to obtain the position of the product to be sorted in the world coordinate system.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
Compared with the prior art, the invention has the following remarkable advantages: 1) compared with the traditional template matching method, the method has the advantages that the problems of wood block texture interference and the like can be eliminated, and the accuracy and the rapidity of product sorting are enhanced; 2) the RGB graph is converted into the HSV space to carry out different color identification, and compared with the traditional gray level identification, the method can effectively reduce different illumination environments, particularly the interference of light and dark illumination changes on detection, and improve the sorting accuracy; 3) the hand-eye positioning based on the calibration plate is used for quickly identifying and positioning the target product and determining the position of the product position, so that the industrial robot arm is controlled to quickly and accurately sort and package the product, the sorting efficiency is improved, and the labor cost is reduced.
The present invention is described in further detail below with reference to the attached drawing figures.
Drawings
FIG. 1 is a flow diagram of a method for sorting products in one embodiment.
FIG. 2 is a flow diagram of pattern detection in one embodiment.
FIG. 3 is a flow diagram of color identification in one embodiment.
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, the invention provides a product sorting system, which comprises an image acquisition module, an image processing module, a communication module and a sorting module;
the image acquisition module is used for acquiring images of products to be sorted;
the image processing module is used for acquiring the characteristic information and the position information of the product to be sorted according to the acquired image and judging whether the product to be sorted is qualified or not;
the communication module is used for transmitting all information of the products to be sorted, which is acquired by the image processing module, to the sorting module;
and the sorting module is used for sorting the products to be sorted according to the received information.
Further, in one embodiment, the image processing module includes:
the color identification unit is used for detecting the color information of the product to be sorted based on the HSV color space;
the qualified information detection unit is used for detecting the shape of the product to be sorted and realizing the detection of whether the product to be sorted is qualified or not based on the classifier;
and the positioning unit is used for detecting the position information of the product to be sorted.
As a specific example, the classifier specifically employs a multi-layer perceptron.
Further, in one embodiment, the sorting module includes:
the control unit is used for receiving the information of the products to be sorted transmitted by the communication module and controlling the mechanical arm sorting unit to sort the products according to the information of the products to be sorted;
and the mechanical arm sorting unit is used for sorting the products under the control of the control unit.
Here, as a specific example, the robot arm sorting unit includes six industrial robot arms and suction cups provided at ends of the robot arms, and an air pump controlling operation of the suction cups.
In one embodiment, in conjunction with fig. 1, the present invention provides a method of sorting products, the method comprising:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
Further, in one embodiment, with reference to fig. 2, the step 2 of determining whether the product to be sorted is qualified according to the shape information specifically includes:
step 2-1, collecting a plurality of product images, extracting shape information and qualified information of each product to serve as training samples;
2-2, constructing a multilayer perceptron, and setting parameters of the multilayer perceptron, wherein the parameters comprise the number of input layers, output layers and hidden layers, an activation function and a preprocessing function;
2-3, training the multilayer perceptron by combining the training samples and the parameters of the multilayer perceptron;
2-4, extracting shape information of the product to be sorted according to the image of the product to be sorted;
and 2-5, taking the shape information of the product to be sorted as the input of the trained multilayer perceptron, and outputting a result whether the product to be sorted is qualified or not by the multilayer perceptron.
Further, in one embodiment, with reference to fig. 3, step 3 is to acquire color information of the product to be sorted based on the image of the product to be sorted, and specifically includes:
step 3-1, performing color gamut conversion on an image of a product to be sorted, and converting an RGB image into an HSV image;
and 3-2, performing threshold segmentation on the H-domain image to obtain the color of the product to be sorted.
Further, in one embodiment, the step 4 of acquiring the position information of the product to be sorted based on the image of the product to be sorted specifically includes:
step 4-1, obtaining coordinate values of the calibration plate in a camera coordinate system and a world coordinate system respectively;
step 4-2, establishing an affine transformation matrix between the camera coordinate system and the world coordinate system according to coordinate values of the calibration plate in the camera coordinate system and the world coordinate system respectively;
4-3, performing morphological processing and connected domain analysis on the image subjected to threshold segmentation in the step 3-2 to obtain the position of a product to be sorted in a camera coordinate system;
and 4-4, combining the position of the product to be sorted in the camera coordinate system and the affine transformation matrix to obtain the position of the product to be sorted in the world coordinate system.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data required in the process of fusing the data of the multiple systems. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of multi-system data fusion.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
Further, in one embodiment, the processor executes the computer program to determine whether the product to be sorted is qualified according to the shape information, specifically implementing the following steps:
step 2-1, collecting a plurality of product images, extracting shape information and qualified information of each product to serve as training samples;
2-2, constructing a multilayer perceptron, and setting parameters of the multilayer perceptron, wherein the parameters comprise the number of input layers, output layers and hidden layers, an activation function and a preprocessing function;
2-3, training the multilayer perceptron by combining the training samples and the parameters of the multilayer perceptron;
2-4, extracting shape information of the product to be sorted according to the image of the product to be sorted;
and 2-5, taking the shape information of the product to be sorted as the input of the trained multilayer perceptron, and outputting a result whether the product to be sorted is qualified or not by the multilayer perceptron.
Further, in one embodiment, the processor executes a computer program to obtain color information of the product to be sorted based on the image of the product to be sorted, and specifically implements the following steps:
step 3-1, performing color gamut conversion on an image of a product to be sorted, and converting an RGB image into an HSV image;
and 3-2, performing threshold segmentation on the H-domain image to obtain the color of the product to be sorted.
Further, in one embodiment, the processor executes a computer program to obtain the position information of the product to be sorted based on the image of the product to be sorted, and specifically implements the following steps:
step 4-1, obtaining coordinate values of the calibration plate in a camera coordinate system and a world coordinate system respectively;
step 4-2, establishing an affine transformation matrix between the camera coordinate system and the world coordinate system according to coordinate values of the calibration plate in the camera coordinate system and the world coordinate system respectively;
4-3, performing morphological processing and connected domain analysis on the image subjected to threshold segmentation in the step 3-2 to obtain the position of a product to be sorted in a camera coordinate system;
and 4-4, combining the position of the product to be sorted in the camera coordinate system and the affine transformation matrix to obtain the position of the product to be sorted in the world coordinate system.
In one embodiment, a computer readable storage medium having a computer program stored thereon, the computer program when executed by a processor implementing the steps of:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
Further, in one embodiment, the computer program is executed by a processor to implement the above-mentioned determining whether the product to be sorted is qualified according to the shape information, and specifically implements the following steps:
step 2-1, collecting a plurality of product images, extracting shape information and qualified information of each product to serve as training samples;
2-2, constructing a multilayer perceptron, and setting parameters of the multilayer perceptron, wherein the parameters comprise the number of input layers, output layers and hidden layers, an activation function and a preprocessing function;
2-3, training the multilayer perceptron by combining the training samples and the parameters of the multilayer perceptron;
2-4, extracting shape information of the product to be sorted according to the image of the product to be sorted;
and 2-5, taking the shape information of the product to be sorted as the input of the trained multilayer perceptron, and outputting a result whether the product to be sorted is qualified or not by the multilayer perceptron.
Further, in one embodiment, the computer program is executed by a processor to implement the above-mentioned obtaining of color information of a product to be sorted based on an image of the product to be sorted, and specifically implement the following steps:
step 3-1, performing color gamut conversion on an image of a product to be sorted, and converting an RGB image into an HSV image;
and 3-2, performing threshold segmentation on the H-domain image to obtain the color of the product to be sorted.
Further, in one embodiment, the computer program is executed by a processor to implement the above-mentioned obtaining of the position information of the product to be sorted based on the image of the product to be sorted, and specifically implement the following steps:
step 4-1, obtaining coordinate values of the calibration plate in a camera coordinate system and a world coordinate system respectively;
step 4-2, establishing an affine transformation matrix between the camera coordinate system and the world coordinate system according to coordinate values of the calibration plate in the camera coordinate system and the world coordinate system respectively;
4-3, performing morphological processing and connected domain analysis on the image subjected to threshold segmentation in the step 3-2 to obtain the position of a product to be sorted in a camera coordinate system;
and 4-4, combining the position of the product to be sorted in the camera coordinate system and the affine transformation matrix to obtain the position of the product to be sorted in the world coordinate system.
In conclusion, the invention collects the product image based on the single camera and obtains the sorting information through the image processing unit, thereby accurately executing the sorting, improving the sorting efficiency and reducing the labor cost.
Claims (10)
1. A product sorting system is characterized by comprising an image acquisition module, an image processing module, a communication module and a sorting module;
the image acquisition module is used for acquiring images of products to be sorted;
the image processing module is used for acquiring the characteristic information and the position information of the product to be sorted according to the acquired image and judging whether the product to be sorted is qualified or not;
the communication module is used for transmitting all information of the products to be sorted, which is acquired by the image processing module, to the sorting module;
and the sorting module is used for sorting the products to be sorted according to the received information.
2. The product sorting system according to claim 1, wherein the image processing module comprises:
the color identification unit is used for detecting the color information of the product to be sorted based on the HSV color space;
the qualified information detection unit is used for detecting the shape of the product to be sorted and realizing the detection of whether the product to be sorted is qualified or not based on the classifier;
and the positioning unit is used for detecting the position information of the product to be sorted.
3. The product sorting system according to claim 2, wherein the sorter employs in particular a multi-tier perception machine.
4. The product sortation system as claimed in claim 3, wherein said sorting module comprises:
the control unit is used for receiving the information of the products to be sorted transmitted by the communication module and controlling the mechanical arm sorting unit to sort the products according to the information of the products to be sorted;
and the mechanical arm sorting unit is used for sorting the products under the control of the control unit.
5. A method of sorting products, the method comprising:
step 1, collecting an image of a product to be sorted;
step 2, acquiring shape information of the product to be sorted based on the image of the product to be sorted, judging whether the product to be sorted is qualified or not according to the shape information, if so, executing step 3, otherwise, executing step 4;
step 3, acquiring color information of the product to be sorted based on the image of the product to be sorted;
step 4, acquiring position information of the product to be sorted based on the image of the product to be sorted;
and 5, transmitting all information of the products to be sorted obtained in the process to a sorting module, and sorting the products by the sorting module.
6. The product sorting method according to claim 5, wherein the step 2 of judging whether the product to be sorted is qualified according to the shape information specifically comprises:
step 2-1, collecting a plurality of product images, extracting shape information and qualified information of each product to serve as training samples;
2-2, constructing a multilayer perceptron, and setting parameters of the multilayer perceptron, wherein the parameters comprise the number of input layers, output layers and hidden layers, an activation function and a preprocessing function;
2-3, training the multilayer perceptron by combining the training samples and the parameters of the multilayer perceptron;
2-4, extracting shape information of the product to be sorted according to the image of the product to be sorted;
and 2-5, taking the shape information of the product to be sorted as the input of the trained multilayer perceptron, and outputting a result whether the product to be sorted is qualified or not by the multilayer perceptron.
7. The product sorting method according to claim 6, wherein the step 3 of obtaining color information of the product to be sorted based on the image of the product to be sorted specifically comprises:
step 3-1, performing color gamut conversion on an image of a product to be sorted, and converting an RGB image into an HSV image;
and 3-2, performing threshold segmentation on the H-domain image to obtain the color of the product to be sorted.
8. The product sorting method according to claim 7, wherein the step 4 of obtaining the position information of the product to be sorted based on the image of the product to be sorted specifically comprises:
step 4-1, obtaining coordinate values of the calibration plate in a camera coordinate system and a world coordinate system respectively;
step 4-2, establishing an affine transformation matrix between the camera coordinate system and the world coordinate system according to coordinate values of the calibration plate in the camera coordinate system and the world coordinate system respectively;
4-3, performing morphological processing and connected domain analysis on the image subjected to threshold segmentation in the step 3-2 to obtain the position of a product to be sorted in a camera coordinate system;
and 4-4, combining the position of the product to be sorted in the camera coordinate system with the affine transformation matrix to obtain the position of the product to be sorted in the world coordinate system.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 5 to 8 are implemented by the processor when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 5 to 8.
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