CN111507959A - Mushroom head quantity statistical system based on image recognition - Google Patents
Mushroom head quantity statistical system based on image recognition Download PDFInfo
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- CN111507959A CN111507959A CN202010295523.9A CN202010295523A CN111507959A CN 111507959 A CN111507959 A CN 111507959A CN 202010295523 A CN202010295523 A CN 202010295523A CN 111507959 A CN111507959 A CN 111507959A
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Abstract
The mushroom head quantity statistical system based on image recognition is reasonable in design, the image sampling module is used for acquiring and transmitting mushroom head images and performing digital-to-analog conversion, the image processing module is used for performing image decoloring, contrast adjustment, gray level processing, binarization processing and optimization, and finally the image recognition module is used for recognizing the images, so that the statistics of the number of the mushroom heads and the distribution of the mushroom heads is completed, the growth condition of strains can be effectively tracked, the data collection of mushroom planting is facilitated, and data support is provided for mushroom planting and research.
Description
Technical Field
The invention relates to the technical field of mushroom planting and cultivation, in particular to a mushroom head quantity statistical system based on image recognition.
Background
Folk references to mushrooms are common: the fungus soup is a treasure for good health; if the body is thin, people eat more mushrooms and less meat, so that the popularity of mushrooms can be seen.
In daily life, people often buy mushrooms for eating, and the consumption of the mushrooms is huge, so that the cultivation of the mushrooms is particularly important. When the mushroom is cultured, the screening of strains is particularly important, and good strains can effectively improve the planting efficiency and yield of the mushroom.
In order to effectively screen strains with excellent quality, the growth state of the strains needs to be tracked and recorded during strain culture, and data support is provided for mushroom planting and research.
Disclosure of Invention
The invention aims at the problems and discloses a mushroom head quantity statistical system based on image recognition.
The specific technical scheme is as follows:
a mushroom head quantity statistical system based on image recognition is characterized by comprising an image sampling module, an image processing module and an image recognition module;
the image sampling module: the mushroom head image data acquisition module is used for acquiring mushroom head image data and generating mushroom head image data for processing;
the image processing module: processing the mushroom head image data and generating binaryzation image data for identification;
the image identification module: and the effective pixel points are used for identifying the effective pixel points of the binary image data, and effective mushroom head statistical data are generated based on the effective pixel points.
The mushroom head quantity statistical system based on image identification comprises a shooting device for acquiring mushroom head image data, a conversion unit for converting the mushroom head image data and a transmission unit for transmitting the mushroom head image data.
The mushroom head quantity statistical system based on image recognition is characterized in that the shooting device is a camera, the conversion unit is an A/D converter, and the transmission unit is a wireless transmission module or a wired transmission module.
The mushroom head quantity statistical system based on image recognition is characterized in that after the shooting equipment collects mushroom head image data, the mushroom head image data are input into the A/D converter through the transmission unit, the A/D converter performs signal conversion on the mushroom head image data, and the mushroom head image data are finally transmitted to the image processing module.
The mushroom head quantity statistical system based on image identification is characterized in that the image processing module performs image variable adjustment on received mushroom head image data, performs binarization processing, performs image area optimization to obtain binarized image data, and finally transmits the binarized image data to the image identification module.
The mushroom head number statistical system based on image recognition is characterized in that the image variable adjustment: after the image processing module receives the mushroom head image data, the color removal processing is firstly carried out, the image contrast is improved, and meanwhile, a gray level image is generated.
The mushroom head number statistical system based on image recognition comprises the following steps: and after the image processing module generates a gray level image, carrying out image binarization on the gray level image, reserving black and white colors, carrying out reverse color processing, and removing redundant gray level colors to obtain a binarization preliminary image.
The mushroom head number statistical system based on image recognition is characterized in that the image area optimization: and after the binarization processing is finished, the image processing module removes useless color lumps at the edge of the binarized preliminary image, and reserves effective points in the middle of the image, so that binarized image data is obtained.
The image identification-based mushroom head quantity statistical system comprises an image identification module, an image acquisition module, a data processing module and a data processing module, wherein the image identification module is used for establishing an X-Y coordinate axis for received binary image data, identifying effective points in the middle of the binary image data and generating point coordinates corresponding to each effective point, the numerical value of the point coordinates is mushroom head coordinates, and the total quantity of the point coordinates is mushroom head total quantity.
In the mushroom head quantity statistical system based on image recognition, the image recognition module needs to set recognition accuracy in advance when generating the point coordinates.
The invention has the beneficial effects that:
the mushroom head quantity statistical system based on image recognition is reasonable in design, the image sampling module is used for acquiring and transmitting mushroom head images and performing digital-to-analog conversion, the image processing module is used for performing image decoloring, contrast adjustment, gray level processing, binarization processing and optimization, and finally the image recognition module is used for recognizing the images, so that the statistics of the number of the mushroom heads and the distribution of the mushroom heads is completed, the growth condition of strains can be effectively tracked, the data collection of mushroom planting is facilitated, and data support is provided for mushroom planting and research.
Drawings
Fig. 1 is a mushroom head image (substantially a color image) acquired in the second embodiment.
FIG. 2 is a mushroom head image after completion of the decoloring, contrast enhancement and gray scale processing.
FIG. 3 is a mushroom head image after binarization processing.
Fig. 4 is a reversed image of the mushroom head in fig. 3.
Fig. 5 is a mushroom head image after image area optimization.
Fig. 6 is a mushroom head image after coordinate axis establishment is completed.
Detailed Description
In order to make the technical solution of the present invention clearer and clearer, the present invention is further described below with reference to embodiments, and any solution obtained by substituting technical features of the technical solution of the present invention with equivalents and performing conventional reasoning falls within the scope of the present invention.
Example one
The mushroom head quantity statistical system based on image recognition is characterized by comprising an image sampling module, an image processing module and an image recognition module;
the image sampling module: the mushroom head image data acquisition module is used for acquiring mushroom head image data and generating mushroom head image data for processing;
the image processing module: processing the mushroom head image data and generating binaryzation image data for identification;
the image identification module: the mushroom head statistical data generation device is used for identifying effective pixel points of the binary image data and generating effective mushroom head statistical data based on the effective pixel points;
the embodiment is designed based on the image acquisition and identification technology, the acquisition of the mushroom head images on the strains is realized through the acquisition, the identification of the number of the mushroom heads is carried out, the growth condition of the strains can be effectively tracked, the data collection of the mushroom planting is facilitated, and the data support is provided for the mushroom planting and research.
Example two
The system for counting the number of mushroom heads based on image recognition in the embodiment comprises an image sampling module, a data processing module and a data processing module, wherein the image sampling module comprises shooting equipment for acquiring mushroom head image data, a conversion unit for converting the mushroom head image data and a transmission unit for transmitting the mushroom head image data;
the shooting equipment is a camera, the conversion unit is an A/D converter, the transmission unit is a wireless transmission module or a wired transmission module, the shooting equipment acquires mushroom head image data, inputs the mushroom head image data into the A/D converter through the transmission unit, and the signal conversion is carried out on the mushroom head image data by the A/D converter and finally the mushroom head image data is transmitted to the image processing module;
this embodiment uses the camera as shooting equipment, carries out mushroom head image data's collection, carries out data transmission through wireless transmission module or wired transport module, and the camera is wireless camera, arranges more conveniently, and shooting equipment needs to carry out digital-to-analog conversion after accomplishing mushroom head image data and gathers, converts into digital signal, the subsequent image processing of being convenient for.
EXAMPLE III
In the image recognition-based mushroom head quantity statistical system of the embodiment, the image processing module performs image variable adjustment on received mushroom head image data, performs binarization processing, performs image area optimization to obtain binarized image data, and finally transmits the binarized image data to the image recognition module;
wherein the image variable adjustment: after the image processing module receives the mushroom head image data, firstly, the decolorizing processing is carried out, the image contrast is improved, meanwhile, a gray level image is generated, and the binaryzation processing comprises the following steps: after the image processing module generates a gray level image, the image binarization is carried out on the gray level image, black and white colors are reserved, the reverse color processing is carried out, redundant gray level colors are removed, a binarization preliminary image is obtained, and the image area is optimized: after the binarization processing is finished, the image processing module removes useless color lumps at the edge of the binarized preliminary image, and retains effective points in the middle of the image, so that binarized image data is obtained;
in this embodiment, the image processing of the mushroom head image data includes a plurality of steps, and the goal of the decolorizing processing, the image contrast improvement and the gray image generation is to optimize a graph, the decolorizing processing is to remove an image variable affecting the mushroom head recognition, and the image contrast improvement and the gray image generation are to improve the effect of the subsequent binarization processing and improve the image quality.
Example four
In the image recognition-based mushroom head quantity statistical system of the embodiment, the image recognition module establishes an X-Y coordinate axis for the received binarized image data, recognizes effective points in the middle of the binarized image data, and generates point coordinates corresponding to each effective point, wherein the numerical value of the point coordinates is a mushroom head coordinate, and the total quantity of the point coordinates is the total quantity of mushroom heads;
when the image recognition module generates point coordinates, the recognition accuracy needs to be preset;
according to the method, coordinate axis establishment is carried out on the binarization image data, the identification efficiency of the mushroom head is effectively guaranteed, detailed statistics is carried out on the distribution of the mushroom head, mushroom planting and research are facilitated, and the identification precision needs to be adjusted according to mushroom varieties and growth states. The device comprises an image sampling module, an image processing module and an image identification module.
In conclusion, the invention has reasonable design, the image sampling module is used for acquiring and transmitting the mushroom head image and performing digital-to-analog conversion, the image processing module is used for decoloring, adjusting contrast, processing gray scale, performing binarization processing and optimizing the image, and the image recognition module is used for recognizing the image finally to complete the statistics of the number and distribution of the mushroom heads, thereby effectively tracking the growth condition of strains, being beneficial to the data collection of the mushroom planting and providing data support for the mushroom planting and research.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are also included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A mushroom head quantity statistical system based on image recognition is characterized by comprising an image sampling module, an image processing module and an image recognition module;
the image sampling module: the mushroom head image data acquisition module is used for acquiring mushroom head image data and generating mushroom head image data for processing;
the image processing module: processing the mushroom head image data and generating binaryzation image data for identification;
the image identification module: and the effective pixel points are used for identifying the effective pixel points of the binary image data, and effective mushroom head statistical data are generated based on the effective pixel points.
2. The image recognition-based mushroom head quantity statistical system according to claim 1, wherein the image sampling module comprises a shooting device for mushroom head image data acquisition, a conversion unit for mushroom head image data conversion and a transmission unit for mushroom head image data transmission.
3. The system for counting the number of mushroom heads based on image recognition according to claim 2, wherein the photographing device is a camera, the converting unit is an A/D converter, and the transmitting unit is a wireless transmitting module or a wired transmitting module.
4. The image recognition-based mushroom head quantity statistical system according to claim 3, wherein after the mushroom head image data is collected by the shooting device, the mushroom head image data is input into the A/D converter through the transmission unit, and the A/D converter performs signal conversion on the mushroom head image data and finally transmits the mushroom head image data to the image processing module.
5. The image recognition-based mushroom head quantity statistical system according to claim 2, wherein the image processing module performs image variable adjustment on the received mushroom head image data, then performs binarization processing, performs image area optimization to obtain binarized image data, and finally transmits the binarized image data to the image recognition module.
6. An image recognition-based mushroom head counting system according to claim 5, wherein the image variable adjusts: after the image processing module receives the mushroom head image data, the color removal processing is firstly carried out, the image contrast is improved, and meanwhile, a gray level image is generated.
7. The image recognition-based mushroom head counting system according to claim 6, wherein the binarization processing: and after the image processing module generates a gray level image, carrying out image binarization on the gray level image, reserving black and white colors, carrying out reverse color processing, and removing redundant gray level colors to obtain a binarization preliminary image.
8. The image recognition-based mushroom head counting system according to claim 7, wherein the image area optimization: and after the binarization processing is finished, the image processing module removes useless color lumps at the edge of the binarized preliminary image, and reserves effective points in the middle of the image, so that binarized image data is obtained.
9. The system of claim 5, wherein the image recognition module performs X-Y coordinate axis establishment on the received binarized image data, recognizes effective points in the middle of the binarized image data, and generates point coordinates corresponding to each effective point, the value of the point coordinates is mushroom head coordinates, and the total number of the point coordinates is mushroom head total number.
10. The system for counting the number of mushroom heads based on image recognition according to claim 9, wherein the image recognition module is required to set recognition accuracy in advance when generating point coordinates.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113933304A (en) * | 2021-10-25 | 2022-01-14 | 南京航空航天大学苏州研究院 | Vision-based needle mushroom maturity state detection method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104700404A (en) * | 2015-03-02 | 2015-06-10 | 中国农业大学 | Fruit location identification method |
| CN105158253A (en) * | 2015-01-25 | 2015-12-16 | 无锡桑尼安科技有限公司 | Identification method of crop maturity |
| CN105427275A (en) * | 2015-10-29 | 2016-03-23 | 中国农业大学 | Filed environment wheat head counting method and device |
| CN108305270A (en) * | 2018-03-19 | 2018-07-20 | 河南工业大学 | A kind of storage grain worm number system and method based on mobile phone photograph |
| CN108921067A (en) * | 2018-06-22 | 2018-11-30 | 三明学院 | A kind of method, apparatus, equipment and system counting agricultural pests |
| KR20190081708A (en) * | 2017-12-29 | 2019-07-09 | 주식회사 비스텔 | Method and computer program for recognizing defect pattern of wafer map based on neural network model |
-
2020
- 2020-04-15 CN CN202010295523.9A patent/CN111507959A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105158253A (en) * | 2015-01-25 | 2015-12-16 | 无锡桑尼安科技有限公司 | Identification method of crop maturity |
| CN104700404A (en) * | 2015-03-02 | 2015-06-10 | 中国农业大学 | Fruit location identification method |
| CN105427275A (en) * | 2015-10-29 | 2016-03-23 | 中国农业大学 | Filed environment wheat head counting method and device |
| KR20190081708A (en) * | 2017-12-29 | 2019-07-09 | 주식회사 비스텔 | Method and computer program for recognizing defect pattern of wafer map based on neural network model |
| CN108305270A (en) * | 2018-03-19 | 2018-07-20 | 河南工业大学 | A kind of storage grain worm number system and method based on mobile phone photograph |
| CN108921067A (en) * | 2018-06-22 | 2018-11-30 | 三明学院 | A kind of method, apparatus, equipment and system counting agricultural pests |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113933304A (en) * | 2021-10-25 | 2022-01-14 | 南京航空航天大学苏州研究院 | Vision-based needle mushroom maturity state detection method |
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