CN117132813A - Microfluidic chip channel identification method, device, equipment and readable storage medium - Google Patents

Abstract

The application belongs to the technical field of micro-fluidic chip quality detection, and discloses a micro-fluidic chip channel identification method, a device, equipment and a readable storage medium, which comprise the following steps: acquiring an image of a microfluidic chip acquired by an imaging sensor; preprocessing an image of a microfluidic chip to obtain a first image; sliding on the first image by using a sliding window with a preset size, and storing the central coordinate of the sliding window meeting the preset condition as a first target point to a target coordinate list; judging whether all first target points in the target coordinate list are in a micro-fluidic chip channel or not; performing water-diffusion filling treatment by taking a first target point in a chip channel as a seed point to obtain an image mask of a channel image in the microfluidic chip image; and cutting out the image of the microfluidic chip by using the image mask to obtain a target image only containing channels of the microfluidic chip. The application can realize the efficient and high-precision division of the channels in the image of the microfluidic chip.

Description

Microfluidic chip channel identification method, device, equipment and readable storage medium

Technical field

The present application relates to the technical field of microfluidic chip quality detection, and in particular to a microfluidic chip channel identification method, device, equipment and readable storage medium.

Background technique

Biochip technology originated in the 1980s and is also known as "microfluidic technology", "lab on a chip", etc. It is a technology that can integrate basic operations such as sample preparation, reaction, separation, and detection in biological, chemical, and medical analysis processes onto a micron-scale chip. It can automatically complete the entire analysis process and has low cost. , few samples, short time, and simple operation. Compared with the increasingly mature development of the microfluidic chip industry, the development of microfluidic chip quality inspection technology is relatively lagging behind. Due to the small size of the microfluidic chip itself, its channels are invisible to the naked eye and require manual observation with the help of an integrated platform. Long-term manual visual inspection can easily fatigue the inspection personnel's vision, thus affecting the inspection results. At present, manual visual inspection is still the main inspection method for microfluidic chips.

For microfluidic chip images, algorithms can be designed to find the chip channel part in the image, thereby achieving the division of channels in the microfluidic chip image. However, there are two main technical difficulties in digital PCR instrument microfluidic chip channel images, including incomplete camera channels and overall transparency of the chip, which makes it difficult to identify channels in microfluidic chip channel images. Among them, the chip is transparent as a whole, and its color is determined by the background color under lighting conditions. It has no color characteristics, and is thicker at the droplet outlet. There are some shadows that affect the observation channel under lighting conditions. The photographing channel is incomplete and the overall image cannot be observed. Unlike conventional detection methods, the target is completely in the image. If you want to observe the microfluidic chip channel, you cannot observe the entire structure and can only observe each structure of the chip in sequence. , thereby determining whether the chip channel is clean, that is, the detection cannot be completed using template matching in traditional image processing.

Contents of the invention

This application provides a microfluidic chip channel identification method, device, equipment and readable storage medium, which can achieve efficient and high-precision division of channels in microfluidic chip images.

In a first aspect, embodiments of the present application provide a microfluidic chip channel identification method, which method includes:

Obtain the microfluidic chip image collected by the imaging sensor;

Preprocess the microfluidic chip image to obtain a first image, wherein the preprocessing includes image enhancement, image binarization and small target removal;

Use a sliding window of preset size to slide on the first image, and save the center coordinate of the sliding window that meets the preset conditions as the first target point to the target coordinate list, where the preset condition is that the target pixel value appears in the sliding window. Coordinate points;

Determine whether all first target points in the target coordinate list are within the microfluidic chip channel;

The first target point in the chip channel is used as a seed point for flood filling processing to obtain an image mask of the channel image in the microfluidic chip image, in which the gray value of the seed point that has been flooded and filled is the target pixel value ;

The image mask is used to crop the microfluidic chip image to obtain a target image containing only the microfluidic chip channels.

Further, the step of preprocessing the microfluidic chip image to obtain the first image includes:

The MSRCP algorithm developed based on the retinex algorithm performs image enhancement on the microfluidic chip image to obtain the second image;

The second image is binarized based on the adaptive equalization algorithm to obtain a third image. During the binarization process, the gray value of the microfluidic chip channel outline part in the microfluidic chip image is set to the target pixel value. ;

The background impurity removal process is performed on the third image based on the small target removal algorithm to obtain the first image, wherein during the background impurity removal process, connected areas whose overall number of pixel values is not greater than a preset threshold are removed.

Further, the step of determining whether all first target points in the target coordinate list are within the microfluidic chip channel includes:

Check all the first target points in the target coordinate list, where the check includes taking the first target point as the center, emitting line segments with a length not greater than the minimum length and width of the sliding window in four directions, and determining the distance between the line segment and the first target point. The intersection point of the outline portion of the microfluidic chip channel in an image;

If the line segments in the up and down direction or the left and right directions have intersection points at the same time and the absolute value of the difference in the number of intersection points on both sides of the line segments in the up and down direction or the left and right direction is less than the preset difference, then it is determined that the first target point is within the microfluidic chip channel.

Further, the preset size is set to one-sixteenth of the first image size.

In a second aspect, the present invention also provides a microfluidic chip channel identification device, which device includes:

An acquisition module is used to acquire the microfluidic chip image collected by the imaging sensor;

An image preprocessing module, used to preprocess the microfluidic chip image to obtain the first image, where the preprocessing includes image enhancement, image binarization and small target removal;

The sliding window processing module is used to slide on the first image using a sliding window of a preset size, and save the center coordinates of the sliding window that meets the preset conditions as the first target point to the target coordinate list, where the preset condition is sliding The coordinate point of the target pixel value appears in the window;

A judgment module used to judge whether all first target points in the target coordinate list are within the microfluidic chip channel;

The flood filling processing module is used to perform flooding filling processing on the first target point in the chip channel as a seed point to obtain an image mask of the channel image in the microfluidic chip image, wherein the seeds that have been flooded filling processed The point gray value is the target pixel value;

A cropping module is used to crop the microfluidic chip image using the image mask to obtain a target image containing only the microfluidic chip channel.

Further, the image preprocessing module is specifically used for:

The MSRCP algorithm developed based on the retine microfluidic chip channel recognition algorithm performs image enhancement on the microfluidic chip image to obtain the second image;

The second image is binarized based on the adaptive equalization algorithm to obtain a third image. During the binarization process, the gray value of the microfluidic chip channel outline part in the microfluidic chip image is set to the target pixel value. ;

The background impurity removal process is performed on the third image based on the small target removal algorithm to obtain the first image, wherein during the background impurity removal process, connected areas whose overall number of pixel values is not greater than a preset threshold are removed.

Further, the judgment module is specifically used for:

Check all the first target points in the target coordinate list, where the check includes taking the first target point as the center, emitting line segments with a length not greater than the minimum length and width of the sliding window in four directions, and determining the distance between the line segment and the first target point. The intersection point of the outline portion of the microfluidic chip channel in an image;

If the line segments in the up and down direction or the left and right directions have intersection points at the same time and the absolute value of the difference in the number of intersection points on both sides of the line segments in the up and down direction or the left and right direction is less than the preset difference, then it is determined that the first target point is within the microfluidic chip channel.

Further, the preset size is set to one-sixteenth of the first image size.

In a third aspect, embodiments of the present application also provide a microfluidic chip channel identification device. The microfluidic chip channel identification device includes a processor, a memory, and a device that is stored in the memory and can be executed by the processor. A microfluidic chip channel identification program, wherein when the microfluidic chip channel identification program is executed by the processor, the steps of the microfluidic chip channel identification method described above are implemented.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium. A microfluidic chip channel identification program is stored on the computer-readable storage medium, wherein the microfluidic chip channel identification program is executed by a processor. When, the steps of the microfluidic chip channel identification method as described above are implemented.

To sum up, compared with the existing technology, the beneficial effects brought by the technical solutions provided by the embodiments of the present application at least include:

The embodiments of this application provide a microfluidic chip channel identification method, device, equipment and readable storage medium. In this application, the collected microfluidic chip images are preprocessed, sliding window processed, flooded and cropped. After processing, a target image containing only the microfluidic chip channels is obtained, which can achieve efficient and high-precision division of channels in the microfluidic chip image. Moreover, the obtained target image also corresponds to only the visible part of the chip channel in the microfluidic chip image, so it can promptly assist manual visual inspection and replace the existing step of determining the channel position during manual visual inspection. Subsequent manual visual inspection can be performed again. On the determined target image, the channel is then inspected for foreign matter, quality defects and other issues to better alleviate the visual fatigue of inspection personnel during manual visual inspection.

Description of the drawings

Figure 1 is a schematic flow chart of a microfluidic chip channel identification method provided by one embodiment of the present application;

Figure 2 is a schematic diagram of sliding window processing of a microfluidic chip channel identification method provided by an embodiment of the present application;

Figure 3 is a schematic diagram of the functional modules of the microfluidic chip channel identification device provided by one embodiment of the present application;

Figure 4 is a schematic diagram of the hardware structure of the microfluidic chip channel identification device involved in one embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

Please refer to Figure 1. This embodiment of the present application provides a microfluidic chip channel identification method. The method specifically includes:

Step S10, obtain the microfluidic chip image collected by the imaging sensor;

Step S20, preprocess the microfluidic chip image to obtain a first image, where the preprocessing includes image enhancement, image binarization and small target removal;

Step S30: Use a sliding window of a preset size to slide on the first image, and save the center coordinates of the sliding window that meets the preset conditions as the first target point to the target coordinate list, where the preset condition is that the target appears in the sliding window. The coordinate point of the pixel value;

Step S40, determine whether all first target points in the target coordinate list are within the microfluidic chip channel;

Step S50, use the first target point in the chip channel as a seed point to perform flooding filling processing, and obtain an image mask of the channel image in the microfluidic chip image, where the gray value of the seed point after flooding filling processing is target pixel value;

Step S60: Use the image mask to crop the microfluidic chip image to obtain a target image containing only microfluidic chip channels.

In this embodiment, the image of the microfluidic chip is obtained by using an imaging sensor such as a digital microscope to directly photograph the chip under the illumination of natural light. Considering that the two technical difficulties of the existing solution, incomplete camera channels and the overall transparency of the chip, make it difficult to identify the channel in the microfluidic chip channel image, the conventional template matching strategy is used to find the chip channel part in the microfluidic chip image. At this time, because the whole cannot be observed, only part of the chip channels can be obtained. Due to the transparent characteristics, only the outline of the chip channel is obtained instead of the channel. It is impossible to divide the channels in the microfluidic chip image. Therefore, in order to achieve efficient and high-precision division of channels in the microfluidic chip image, this embodiment scheme will preprocess and slide the collected microfluidic chip image after acquiring the microfluidic chip image collected by the imaging sensor. Window processing, flood processing and cropping processing are used to obtain the target image containing only the microfluidic chip channel. Among them, the microfluidic chip image only contains part of the chip channel image, and the obtained target image also corresponds to only containing the visible part of the chip channel in the microfluidic chip image. Although the target image only contains the part of the chip channel that is visible in the microfluidic chip image, since the target image only contains the microfluidic chip channel, it can assist manual visual inspection in time, replacing the existing step of determining the channel position during manual visual inspection. , the subsequent manual visual inspection can then detect whether there are foreign objects, quality defects and other problems in the channel on the determined target image, so as to better alleviate the visual fatigue of the inspection personnel during manual visual inspection.

Specifically, since the chip is transparent as a whole, the outline of the microfluidic chip channel is not clearly distinguished from other parts of the chip. Therefore, after obtaining the microfluidic chip image collected by the imaging sensor, the microfluidic chip image will be included Preprocessing of image enhancement, image binarization and small target removal to obtain the first image. Among them, image enhancement can improve the brightness of the channel outline (corresponding to the shaded part) in the microfluidic chip image, thereby making the contrast between the chip outline and other chip parts more obvious, laying the foundation for subsequent image processing algorithms. Since it is mainly necessary to divide the channels in the microfluidic chip, the gray value of the contour part of the chip channel can be binarized to distinguish it from the gray value of other parts. In addition, since there may also be small targets similar to the chip channel outline in other parts, these small targets may become noise interference for the channel division in the chip image. Therefore, the microfluidic chip image will also be binarized. During processing, small targets are removed from the microfluidic chip image to ensure that the retained channel contours are clearer and more precise.

On the basis of determining that the retained channel contour is clearer and more accurate, in order to divide a more accurate area within the actual channel based on the channel contour, this embodiment will perform sliding window processing and flooding processing on the first image obtained after preprocessing. Thus, the image mask of the area within the channel is obtained. Among them, when performing sliding window processing on the first image, a sliding window of preset size will be used to slide on the first image. When the target pixel value (corresponding to the grayscale value of the chip channel outline part after binarization) appears in the sliding window ) coordinate point, confirm that the sliding window touches the chip channel outline point. Referring to Figure 2, at this time, the center coordinate of the sliding window can be saved to the target coordinate list as the first target point. After sliding on the entire first image, by determining whether the first target point in the target coordinate list is located in the microfluidic chip channel, it can be determined whether the first target point needs to be used as a seed point for water flooding processing.

The first target point in the chip channel can be used as a seed point for flooding filling processing. Taking the outline of the chip channel as the boundary, set the coordinate point to the middle of the channel, and flood the water to obtain the image mask of the chip channel in the microfluidic chip image. code. The first target point in the chip channel is used as a seed point for flooding processing. When the image mask of the channel image in the microfluidic chip image is obtained, it will be detected in real time whether the seed point has been flooded. After the flooding processing Finally, the channel outline on the first image, including the channel outline, remains at the same pixel value, that is, the target pixel value of the channel outline part set during binarization. When the target pixel value is set to 255, it is filled with water. The gray value of the processed seed point is also 255. This image mask is then used to crop the original directly obtained microfluidic chip image, and a target image containing only the microfluidic chip channel can be obtained.

Further, in one embodiment, the step S20 includes:

The MSRCP algorithm developed based on the retine microfluidic chip channel recognition algorithm performs image enhancement on the microfluidic chip image to obtain the second image;

The second image is binarized based on the adaptive equalization algorithm to obtain a third image. During the binarization process, the gray value of the microfluidic chip channel outline part in the microfluidic chip image is set to the target pixel value. ;

The background impurity removal process is performed on the third image based on the small target removal algorithm to obtain the first image, wherein during the background impurity removal process, connected areas whose overall number of pixel values is not greater than a preset threshold are removed.

In this embodiment, when preprocessing the microfluidic chip image including image enhancement, image binarization, and small target removal, common image enhancement algorithms are compared, such as histogram equalization, grayscale world algorithm, and Retinex algorithm. , automatic white balance, automatic color balance and other image enhancement algorithms. The MSRCP algorithm developed based on the retinex algorithm has the most significant improvement in the brightness of the chip channel outline (shaded part) in the microfluidic chip image. Therefore, the retine microfluidic based algorithm will be used first. The MSRCP algorithm developed from the microfluidic chip channel identification algorithm performs image enhancement on the microfluidic chip image to obtain a second image. After image enhancement, you can directly use the adaptive equalization algorithm in OpenCV to binarize the enhanced microfluidic chip image. The binarized microfluidic chip image, the gray of the chip channel outline, The degree value can be 255, and the rest can be 0. In this case, the target pixel value can be 255. Among them, after binarization, all white parts except the channel part are regarded as background impurities, and the corresponding grayscale values of the white parts (including the channel outline part and the background impurity part) are all 255. For the background impurities that appear after binarization, this embodiment directly uses the small target removal algorithm in OpenCV, and uses a function to retain the area where the overall number of pixel values in the connected area is greater than the preset threshold. It is determined through experiments that the preset threshold (corresponding to the minimum pixel value of the connected area) is preferably set to 4000. By using a function to retain the area where the overall number of pixel values in the connected area is greater than 4000, and removing the surrounding isolated pixels, the purpose of making the channel outline clearer and more accurate is achieved.

Further, in one embodiment, the step S40 includes:

Check all the first target points in the target coordinate list, where the check includes taking the first target point as the center, emitting line segments with a length not greater than the minimum length and width of the sliding window in four directions, and determining the distance between the line segment and the first target point. The intersection point of the outline portion of the microfluidic chip channel in an image;

If the line segments in the up and down direction or the left and right directions have intersection points at the same time and the absolute value of the difference in the number of intersection points on both sides of the line segments in the up and down direction or the left and right direction is less than the preset difference, then it is determined that the first target point is within the microfluidic chip channel.

In this embodiment, when determining whether all the first target points in the target coordinate list are in the microfluidic chip channel, all the first target points in the target coordinate list will be checked, with the first target point as the center, upward Line segments with lengths no greater than the minimum length and width of the window are emitted in the four directions, and the intersection point of the line segment with the outline of the microfluidic chip channel in the first image is determined to determine whether the first target point is within the channel. Only when the line segments in the up and down directions or the left and right directions have intersection points at the same time, and the absolute value of the difference between the number of intersection points on the up and down or left and right sides is less than the preset difference value, can it be determined that the first target point is within the microfluidic chip channel outline, Except for this, other first target points are outside the outline of the microfluidic chip channel. Among them, the preset difference value is preferably set to 3. Through the inspection of the above scheme, the seed points that are not within the channel outline of the microfluidic chip can be eliminated. The subsequent image mask obtained by flood processing based on the filtered first target point can more accurately distinguish and characterize the microfluidic chip. The channel part and other parts outside the channel, and the above filtering method does not require additional image processing, consumes less computing resources, and the filtering speed is also faster.

Further, in one embodiment, the preset size is set to one-sixteenth of the first image size.

In this embodiment, when the sliding window is used to slide the first image, the preset size of the sliding window is set to one-sixteenth of the size of the first image, mainly because the size of the first image processed may be different. In the experiment, the images are mainly 2048x3096 size, but it may also be 1024x72048 size. Taking into account adapting to image processing of different sizes, it is set to one-sixteenth of the image size. In addition, the sliding step size of the sliding window is preferably set to 50px, that is, 50 pixel values. The window slides from left to right and from top to bottom. When the moving distance is less than 50, it will move directly to the end position, thereby completing the entire Sliding processing of the first image.

An embodiment of the present application also provides a microfluidic chip channel identification device.

Refer to Figure 3, which is a schematic diagram of the functional modules of the first embodiment of the microfluidic chip channel identification device.

In this embodiment, the microfluidic chip channel identification device includes:

The acquisition module 10 is used to acquire the microfluidic chip image collected by the imaging sensor;

The image preprocessing module 20 is used to preprocess the microfluidic chip image to obtain the first image, where the preprocessing includes image enhancement, image binarization and small target removal;

The sliding window processing module 30 is configured to use a sliding window of a preset size to slide on the first image, and save the center coordinates of the sliding window that meets the preset conditions as the first target point to the target coordinate list, where the preset condition is The coordinate point where the target pixel value appears in the sliding window;

The judgment module 40 is used to judge whether all the first target points in the target coordinate list are within the microfluidic chip channel;

The flood filling processing module is used to perform flooding filling processing on the first target point in the chip channel as a seed point to obtain an image mask of the channel image in the microfluidic chip image, wherein the seeds that have been flooded filling processed The point gray value is the target pixel value;

The cropping module 50 is used to crop the microfluidic chip image using the image mask to obtain a target image containing only the microfluidic chip channel.

Further, in one embodiment, the image preprocessing module 20 is specifically used for:

The MSRCP algorithm developed based on the retine microfluidic chip channel recognition algorithm performs image enhancement on the microfluidic chip image to obtain the second image;

The second image is binarized based on the adaptive equalization algorithm to obtain a third image. During the binarization process, the gray value of the microfluidic chip channel outline part in the microfluidic chip image is set to the target pixel value. ;

The background impurity removal process is performed on the third image based on the small target removal algorithm to obtain the first image, wherein during the background impurity removal process, connected areas whose overall number of pixel values is not greater than a preset threshold are removed.

Further, in one embodiment, the judgment module 40 is specifically used to:

Check all the first target points in the target coordinate list, where the check includes taking the first target point as the center, emitting line segments with a length not greater than the minimum length and width of the sliding window in four directions, and determining the distance between the line segment and the first target point. The intersection point of the outline portion of the microfluidic chip channel in an image;

If the line segments in the up and down direction or the left and right directions have intersection points at the same time and the absolute value of the difference in the number of intersection points on both sides of the line segments in the up and down direction or the left and right direction is less than the preset difference, then it is determined that the first target point is within the microfluidic chip channel.

Further, in one embodiment, the preset size is set to one-sixteenth of the first image size.

Among them, the functional implementation of each module in the above-mentioned microfluidic chip channel identification device corresponds to each step in the embodiment of the above-mentioned microfluidic chip channel identification method, and its functions and implementation processes will not be repeated here.

Embodiments of the present application provide a microfluidic chip channel identification device. The microfluidic chip channel identification device may be a personal computer (PC), notebook computer, server, or other device with data processing functions.

Referring to Figure 4, Figure 4 is a schematic diagram of the hardware structure of the microfluidic chip channel identification device involved in the embodiment of the present application. In the embodiment of the present application, the microfluidic chip channel identification device may include a processor 1001 (such as a Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize connection and communication between these components; the user interface 1003 can include a display screen (Display) and an input unit such as a keyboard (Keyboard); the network interface 1004 can optionally include a standard wired interface and a wireless interface. (such as wireless fidelity, WI-FI interface); the memory 1005 can be a high-speed random access memory (random access memory, RAM), or a stable memory (non-volatile memory), such as disk memory, memory 1005 may optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art can understand that the hardware structure shown in the microfluidic chip channel identification figure does not constitute a limitation of the present invention, and may include more or less components than shown in the figure, or combine certain components, or different Component placement.

Continuing to refer to Figure 4, the memory 1005 as a computer-readable storage medium in Figure 4 can include an operating system, a network communication module, a user interface module and a microfluidic chip channel identification program. The processor 1001 can call the microfluidic chip channel identification program stored in the memory 1005 and execute the steps of the microfluidic chip channel identification method provided by the embodiments of the present application.

For the method implemented when the microfluidic chip channel identification program is executed, reference can be made to various embodiments of the microfluidic chip channel identification method of the present application, and will not be described again here.

The technical features of the above embodiments can be combined in any way. To simplify the description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, all possible combinations should be used. It is considered to be within the scope of this manual.

The above-described embodiments only express several implementation modes of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all fall within the protection scope of the present application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims (10)

1. A microfluidic chip channel identification method, the method comprising:

acquiring an image of a microfluidic chip acquired by an imaging sensor;

preprocessing an image of a microfluidic chip to obtain a first image, wherein the preprocessing comprises image enhancement, image binarization and small target removal;

sliding on the first image by using a sliding window with a preset size, and storing the central coordinate of the sliding window meeting a preset condition as a first target point to a target coordinate list, wherein the preset condition is a coordinate point of a target pixel value in the sliding window;

judging whether all first target points in the target coordinate list are in a micro-fluidic chip channel or not;

performing water-flooding filling treatment by taking a first target point in a chip channel as a seed point to obtain an image mask of a channel image in the microfluidic chip image, wherein the gray value of the seed point subjected to water-flooding filling treatment is a target pixel value;

and cutting out the image of the microfluidic chip by using the image mask to obtain a target image only containing channels of the microfluidic chip.

2. The method of claim 1, wherein the step of preprocessing the image of the microfluidic chip to obtain the first image comprises:

performing image enhancement on the image of the microfluidic chip by using an MSRCP algorithm developed based on a retinex algorithm to obtain a second image;

performing binarization processing on the second image based on a self-adaptive equalization algorithm to obtain a third image, wherein the gray value of the outline part of the microfluidic chip channel in the microfluidic chip image is set as a target pixel value during the binarization processing;

and carrying out background impurity removal processing on the third image based on a small target removal algorithm to obtain a first image, wherein the number of the connected areas with the whole pixel values not larger than a preset threshold value is removed during the background impurity removal processing.

3. The method of claim 1, wherein the step of determining whether all the first target points in the target coordinate list are within the microfluidic chip channel comprises:

checking all first target points in a target coordinate list, wherein the checking comprises taking the first target point as a center, transmitting line segments with lengths not more than the minimum value of the length and the width of a sliding window in four directions, namely, up, down, left and right, and determining the intersection point of the line segments and the contour part of a microfluidic chip channel in a first image;

and if the line segments in the up-down direction or the left-right direction have intersection points at the same time and the absolute value of the difference between the intersection points of the two sides of the line segments in the up-down direction or the left-right direction is smaller than a preset difference value, determining that the first target point is in the microfluidic chip channel.

4. The method according to claim 1, characterized in that: the preset size is set to 16 times the size of the first image size.

5. A microfluidic chip channel identification device, the device comprising:

the acquisition module is used for acquiring the image of the microfluidic chip acquired by the imaging sensor;

the image preprocessing module is used for preprocessing the image of the microfluidic chip to obtain a first image, wherein the preprocessing comprises image enhancement, image binarization and small target removal;

the sliding window processing module is used for sliding on the first image by using a sliding window with a preset size, and storing the central coordinate of the sliding window meeting the preset condition as a first target point to a target coordinate list, wherein the preset condition is a coordinate point of a target pixel value in the sliding window;

the judging module is used for judging whether all the first target points in the target coordinate list are in the microfluidic chip channel or not;

the device comprises a water-flooding filling processing module, a first target point processing module and a second target point processing module, wherein the water-flooding filling processing module is used for performing water-flooding filling processing by taking the first target point in a chip channel as a seed point to obtain an image mask of a channel image in a microfluidic chip image, and the gray value of the seed point subjected to water-flooding filling processing is a target pixel value;

and the clipping module is used for clipping the image of the microfluidic chip by using the image mask to obtain a target image only containing channels of the microfluidic chip.

6. The apparatus according to claim 5, wherein the image preprocessing module is specifically configured to:

performing image enhancement on the image of the microfluidic chip based on an MSRCP algorithm developed by a retine microfluidic chip channel recognition algorithm to obtain a second image;

performing binarization processing on the second image based on a self-adaptive equalization algorithm to obtain a third image, wherein the gray value of the outline part of the microfluidic chip channel in the microfluidic chip image is set as a target pixel value during the binarization processing;

and carrying out background impurity removal processing on the third image based on a small target removal algorithm to obtain a first image, wherein the number of the connected areas with the whole pixel values not larger than a preset threshold value is removed during the background impurity removal processing.

7. The apparatus of claim 5, wherein the determining module is specifically configured to:

checking all first target points in a target coordinate list, wherein the checking comprises taking the first target point as a center, transmitting line segments with lengths not more than the minimum value of the length and the width of a sliding window in four directions, namely, up, down, left and right, and determining the intersection point of the line segments and the contour part of a microfluidic chip channel in a first image;

and if the line segments in the up-down direction or the left-right direction have intersection points at the same time and the absolute value of the difference between the intersection points of the two sides of the line segments in the up-down direction or the left-right direction is smaller than a preset difference value, determining that the first target point is in the microfluidic chip channel.

8. The apparatus according to claim 5, wherein: the preset size is set to 16 times the size of the first image size.

9. A microfluidic chip channel recognition device, characterized in that it comprises a processor, a memory, and a microfluidic chip channel recognition program stored on the memory and executable by the processor, wherein the microfluidic chip channel recognition program, when executed by the processor, implements the steps of the microfluidic chip channel recognition method according to any one of claims 1 to 4.

10. A computer readable storage medium, wherein a microfluidic chip channel recognition program is stored on the computer readable storage medium, wherein the microfluidic chip channel recognition program, when executed by a processor, implements the steps of the microfluidic chip channel recognition method according to any one of claims 1 to 4.