Base cluster brightness detection method, electronic device, and readable storage medium

Abstract

The application discloses a base cluster brightness detection method, an electronic device and a readable storage medium, and is applied to the technical field of gene sequencing. The base cluster brightness detection method comprises the following steps: selecting local background pixels in global pixels of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected; determining a background brightness value corresponding to the base cluster to be detected according to the local background pixels; and performing brightness detection on the base cluster to be detected according to the background brightness value, so as to obtain a brightness detection result. The application solves the technical problem of low detection efficiency of the brightness detection on the base cluster.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gene sequencing, and particularly relates to a base cluster brightness detection method, an electronic device and a readable storage medium. BACKGROUND

[0002] With the continuous development of science and technology, high-throughput sequencing has become a core technical means for gene sequencing. After chemical reaction of base clusters of a gene sequence and fluorescent dyes, a corresponding fluorescent image can be obtained by photographing the generated fluorescent clusters through a miniature camera. Then, the base clusters belonging to different clusters are identified based on base cluster brightness values. The identification of the base clusters is one of important links for realizing high-precision gene sequencing.

[0003] The base cluster identification is to extract the brightness of the base clusters in the fluorescent image. The base cluster brightness is usually obtained by subtracting the background brightness from the measured brightness. Therefore, the background brightness can be obtained by extracting the background brightness in the fluorescent image. At present, the fluorescent cluster region and the background region in the fluorescent image are usually segmented, and then the background region is globally averaged to obtain the background brightness. However, since the threshold value of all pixel points in the fluorescent image needs to be calculated for segmenting the fluorescent image, the high complexity of the calculation will result in long calculation time, and thus the sequencing throughput is easily limited. Therefore, the detection efficiency of the current brightness detection of the base clusters is low. SUMMARY

[0004] The main purpose of the present application is to provide a base cluster brightness detection method, an electronic device and a readable storage medium, and to solve the technical problem of low detection efficiency of the brightness detection of the base clusters in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides a base cluster brightness detection method, which comprises the following steps:

[0006] selecting a local background pixel point in global pixel points of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected;

[0007] determining a background brightness value corresponding to the base cluster to be detected according to the local background pixel point;

[0008] performing brightness detection on the base cluster to be detected according to the background brightness value to obtain a brightness detection result.

[0009] To achieve the above-mentioned purpose, the present application further provides a base cluster brightness detection device, which comprises the following steps:

[0010] a selecting module configured to select a local background pixel point in global pixel points of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected;

[0011] determining, according to the local background pixel point, a background brightness value corresponding to the to-be-detected base cluster;

[0012] detecting, according to the background brightness value, the to-be-detected base cluster to obtain a brightness detection result.

[0013] The application further provides an electronic device, which comprises at least one processor and a memory connected with the at least one processor in communication, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the base cluster brightness detection method.

[0014] The application further provides a computer readable storage medium, which stores a program for implementing a base cluster brightness detection method, and the program for implementing the base cluster brightness detection method performs the steps of the base cluster brightness detection method when executed by a processor.

[0015] The application further provides a computer program product, which comprises a computer program, and the computer program performs the steps of the base cluster brightness detection method when executed by a processor.

[0016] The application provides a base cluster brightness detection method, an electronic device and a readable storage medium, that is, a local background pixel point is selected from global pixel points of a target base cluster image, wherein the target base cluster image carries a to-be-detected base cluster; a background brightness value corresponding to the to-be-detected base cluster is determined according to the local background pixel point; and the to-be-detected base cluster is detected according to the background brightness value to obtain a brightness detection result.

[0017] The application selects a local background pixel point from global pixel points of a target base cluster image carrying a to-be-detected base cluster, and then determines a background brightness value corresponding to the to-be-detected base cluster through the local background pixel point, that is, the overall background brightness of the target base cluster image is determined through the local background pixel point, and finally the to-be-detected base cluster is detected through the background brightness value, that is, a local background pixel point is selected from global pixel points of a target base cluster image, and then a brightness detection result of a to-be-detected base cluster is obtained through the local background pixel point.

[0018] Since the local background pixel points can detect the brightness of the to-be-detected base cluster, that is, the number of background pixel points extracted when detecting the brightness of the to-be-detected base cluster is reduced, at the same time, the local background pixel points are selected from the global pixel points of the target base cluster image, that is, the target base cluster image carrying the to-be-detected base cluster does not need to be segmented when detecting the brightness of the to-be-detected base cluster, so the detection process when detecting the brightness of the to-be-detected base cluster is simplified, that is, the purpose of detecting the brightness of the to-be-detected base cluster based on the background brightness value determined by the local pixel points is achieved.

[0019] Based on this, the application selects local background pixel points from the global pixel points of the target base cluster image, and then determines the background brightness value corresponding to the to-be-detected base cluster through the local background pixel points, and finally obtains the brightness detection result of the to-be-detected base cluster through the background brightness value, thereby achieving the purpose of detecting the brightness of the to-be-detected base cluster through the local background pixel points in the target base cluster image, that is, overcoming the technical defects that the calculation of the threshold value of all pixel points in the fluorescence image is required when the fluorescence image is segmented, and the high complexity of the calculation amount will result in long calculation time, and then the sequencing throughput is limited. Therefore, the detection efficiency of the brightness detection of the base cluster is improved. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the application.

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, those skilled in the art can obtain other drawings according to these drawings without any creative labor.

[0022] Figure 1 The base cluster brightness detection method provided by Embodiment One of the application is shown in the base cluster brightness detection schematic diagram.

[0023] Figure 2 The base cluster brightness detection method provided by Embodiment One of the application is shown in the base cluster brightness detection schematic diagram.

[0024] Figure 3 The base cluster brightness detection method provided by Embodiment One of the application is shown in the base cluster brightness detection schematic diagram.

[0025] Figure 4 The base cluster brightness detection method provided by Embodiment One of the application is shown in the base cluster brightness detection schematic diagram.

[0026] Figure 5A curve diagram of pixel point luminance value-pixel point serial number of the overall luminance uniform image of the base cluster luminance detection method provided by Embodiment One of the present application;

[0027] Figure 6 A division schematic diagram of the overall luminance discrete image of the base cluster luminance detection method provided by Embodiment One of the present application;

[0028] Figure 7 A flow schematic diagram of the base cluster luminance detection method provided by Embodiment Two of the present application;

[0029] Figure 8 A structure schematic diagram of the base cluster luminance detection device provided by Embodiment Three of the present application;

[0030] Figure 9 A structure schematic diagram of the electronic device provided by Embodiment Four of the present application.

[0031] The purposes, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0032] In order to make the above objectives, features and advantages of the present application more apparent, clear and complete, the technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0033] Embodiment One

[0034] Firstly, it should be understood that, in the high-throughput sequencing process, the base recognition will affect the feasibility of the recognized base, so the recognition of the base is particularly important. For example, in the base recognition, the base cluster is reacted with different fluorescent dyes, and then the base cluster is irradiated by laser to make the cluster produce fluorescence, i.e. fluorescent cluster. Then, the A (Adenine, adenine) image, C (Cytosine, cytosine) image, G (Guanine, guanine) image and T (Thymine, thymine) image are obtained by photographing with a microscope camera. Then, the luminance of the same base cluster on different images is recognized by a base luminance extraction algorithm, and then the luminance of the four base clusters is detected to obtain the base of the cluster. In the base cluster luminance detection process, the luminance of the base cluster is detected by referring to the luminance of the base cluster in the same image, and then the base of the cluster is obtained by detecting the luminance of the four base clusters. Figure 1 , Figure 1In order to represent the base cluster brightness detection schematic diagram, the brightness of the base cluster, that is, the brightness of the cluster signal is obtained by subtracting the background brightness from the measured brightness. At present, the image segmentation algorithm is usually used to segment the fluorescent region and the background region of the image, and then the global background is obtained by averaging the background region, for example, by global averaging, or the local background is obtained by local averaging, that is, the brightness of the base cluster is detected by relying on all background pixel points in the fluorescent image. However, the above method has the following problems: when the sequencing sequence is long and the image signal-to-noise ratio is low, the reliability of image segmentation will be reduced, which leads to the inability to accurately distinguish the base fluorescent cluster and the background. At the same time, the threshold is usually calculated by using clustering method during image segmentation, which has high calculation complexity, and thus the image segmentation will consume a lot of time. The limitation of sequencing throughput makes it impossible to carry out large-scale sequencing. Therefore, there is an urgent need for a method for improving the detection efficiency of base cluster brightness detection.

[0035] The embodiment of the present application provides a base cluster brightness detection method. In the first embodiment of the base cluster brightness detection method, referring to Figure 2 , the base cluster brightness detection method comprises the following steps.

[0036] Step S10, local background pixel points are selected from global pixel points of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected.

[0037] Step S20, a background brightness value corresponding to the base cluster to be detected is determined according to the local background pixel points.

[0038] Step S30, the base cluster to be detected is subjected to brightness detection according to the background brightness value, and a brightness detection result is obtained.

[0039] In the embodiment, it should be noted that Figure 2The logical order is shown, but in some cases the steps shown or described can be performed in an order different from that shown, the base cluster brightness detection method is applied to a base cluster brightness detection device, which can be an automatic gene sequencer or a manual gene sequencer, etc., the target base cluster image is used to represent the fluorescence image obtained by the shooting device after the base cluster and the fluorescent dye are chemically reacted, which can be A image, C image, G image or T image, etc., wherein the target base cluster image carries the base cluster to be detected, the base cluster to be detected is used to represent the base cluster waiting for brightness detection, in the fluorescence image obtained by the shooting device, there are a large number of base clusters, any base cluster can be used as the base cluster to be detected, wherein the determination of the base cluster can be based on the area, that is, the base cluster to be detected can be a single base cluster, or a base cluster composed of multiple single base clusters, for example, in an implementable manner, three base clusters A, B and C are selected in the fluorescence image, wherein the base cluster A and the base cluster B are in a bonded state, the base cluster C is in a single state, and the base cluster area corresponding to the bonded base cluster A and the base cluster B and the base cluster area of the base cluster C are all less than a preset area threshold, then the base cluster composed of the base cluster A and the base cluster B and the base cluster C can all be used as the base cluster to be detected.

[0040] In addition, it should be noted that the global pixel point is used to represent all the pixel points in a certain area, and the local background pixel point is used to represent part of the background pixel points in the global pixel point. For the base cluster image, if the image segmentation algorithm is not used, the image background brightness value of the base cluster image can be fed back based on the local background pixel point with a certain accuracy, and then the image background brightness value is used as the background brightness value corresponding to the base cluster to be detected, that is, the purpose of brightness detection of the base cluster to be detected can be achieved, for example, in an implementable manner, the target base cluster image can be divided into a plurality of sub-region images, by comparing the pixel point brightness values of all the pixel points in each sub-region image, and taking the pixel point with the smallest pixel point brightness value as the regional background brightness value of the sub-region image, the image background brightness value of the target base cluster image can be obtained by averaging the regional background brightness values of different sub-region images, wherein the brightness detection result is used to represent the output result of the brightness detection, which can be the actual brightness value, for example, in an implementable manner, assuming that the image background brightness value is a, and the measured brightness value of the base cluster to be detected is b, then the actual brightness value c of the base cluster to be detected is b-a.

[0041] As an example, steps S10 to S30 include: taking any isolated base cluster in a target base cluster image as a base cluster to be detected, and dividing the target base cluster image into a plurality of sub-region images; for any sub-region image, obtaining a pixel point with the minimum pixel point brightness value in the sub-region image by comparing the pixel point brightness values of all pixel points in the sub-region image, and taking the pixel points with the minimum pixel point brightness value in each sub-region image as local background pixel points; obtaining an image background brightness value of the target base cluster image by averaging the pixel point brightness values of the local background pixel points, taking the image background brightness value of the target base cluster image as a background brightness value corresponding to the base cluster to be detected; obtaining a measured brightness value of the base cluster to be detected, and taking the difference between the measured brightness value and the background brightness value as a brightness detection result of the base cluster to be detected.

[0042] The embodiment of the present application collects local background pixel points composed of the pixel points with the minimum pixel point brightness value in different sub-region images in a target base cluster image, and then obtains a background brightness value corresponding to a base cluster to be detected by averaging the pixel point brightness values of the local background pixel points. Finally, the difference between a measured brightness value of the base cluster to be detected and the background brightness value is taken as a brightness detection result of the base cluster to be detected. Since the pixel points with the minimum pixel point brightness value in different sub-region images in the target base cluster image can reflect the regional background brightness condition of the sub-region image to a certain extent, and the background brightness value objectively reflecting the image background brightness condition of the target base cluster image can be obtained by averaging the brightness values of the pixel points with the minimum pixel point brightness value in different sub-region images, compared with the way of taking all background pixel points in a region to participate in the calculation of a threshold value and then detecting the brightness of a base cluster to be detected by using an image segmentation algorithm, the embodiment of the present application can achieve the purpose of reducing the number of pixel points to be calculated when calculating the background brightness value corresponding to the base cluster to be detected, since the local background pixel points are certainly less than all background pixel points in the target base cluster image. Therefore, the detection efficiency of the brightness detection of the base cluster is improved.

[0043] The step of selecting the local background pixel points from the global pixel points of the target base cluster image includes:

[0044] Step A10, detecting the image type of the target base cluster image according to the image brightness variance of the target base cluster image;

[0045] Step A20, if it is detected that the target base cluster image is a whole brightness uniform image, obtaining the local background pixel points by performing brightness sorting on the global pixel points of the whole brightness uniform image;

[0046] Step A30, if it is detected that the target base cluster image is a whole brightness discrete image, then the local background pixel points are obtained by performing brightness sorting on the global pixel points of the whole brightness discrete image.

[0047] In this embodiment, it should be noted that the difference between the base cluster image and the conventional image is that the base cluster image is composed of two types of pixel points, i.e., high-brightness base cluster pixel points and low-brightness background pixel points. If the brightness of all pixel points of the base cluster image is sorted according to a certain rule, the high-brightness base cluster pixel points and the low-brightness background pixel points can be concentrated in different regions, and then the local background pixel points can be obtained by selecting the region where the low-brightness background pixel points are concentrated, thereby eliminating the step of determining the local background pixel points in the target base cluster image by comparison. For example, in an implementable manner, all pixel points of the target base cluster image are sorted according to the pixel brightness value from high to low, and then a preset number of pixel points at the end of the sequence are extracted as the local background pixel points, wherein the preset number can be 100, 200, or 300, etc. Since the local background pixel points are extracted after the brightness sorting of the global pixel points, the local background pixel points can reflect the background brightness value of different regions of the target base cluster image to a certain extent, and then the average value can objectively reflect the background brightness value of the target base cluster image. The background brightness value of the target base cluster image is taken as the background brightness value corresponding to the detected cluster, for example, in an implementable manner, assuming that the local background pixel points include five background pixel points a, b, c, d, and e, the background brightness value of the target base cluster image is the average value of the brightness values of the five background pixel points, i.e., the background brightness value corresponding to the detected base cluster.

[0048] In addition, it should be noted that generally, the overall brightness of the target base cluster image is not uniform, and in some extreme cases, the overall brightness of the target base cluster image is uniform. When the overall brightness of the target base cluster image is uniform, a specific value can be considered to represent the background value of the target base cluster image. When the overall brightness of the target base cluster image is not uniform, for example, the target base cluster image has a convex phenomenon with the middle part being bright and the surrounding part being dark, or the upper part of the target base cluster image is bright and the lower part is dark, a specific value cannot represent the overall background value of the target base cluster image. Therefore, for different types of target base cluster images, different sorting methods can be used to select the local background pixel points, wherein the whole brightness uniform image is used to represent the image with uniform overall brightness, the whole brightness discrete image is used to represent the image with non-uniform overall brightness, and the image brightness variance is the square of the noise. For details, refer to Figure 3 Figure 3 For a schematic diagram of the whole brightness uniform image, refer to Figure 4 Figure 4 ​​For the schematic diagram of the overall brightness discrete image, different types of target base cluster images can be determined by setting an image brightness variance threshold.

[0049] As an example, steps A10 to A20 include: calculating the image brightness variance of the target base cluster image, determining the image type of the target base cluster image by detecting the relationship between the image brightness variance and a preset image brightness variance threshold; if it is detected that the image brightness variance is greater than the preset image brightness variance threshold, determining that the target base cluster image is an overall brightness uniform image, and then obtaining the local background pixel point by performing brightness sorting on the global pixel points of the overall brightness uniform image; and if it is detected that the image brightness variance is not greater than the preset image brightness variance threshold, obtaining the local background pixel point by performing brightness sorting on the global pixel points of the overall brightness discrete image.

[0050] The specific steps of obtaining the local background pixel point by performing brightness sorting on the global pixel points of the overall brightness uniform image can be:

[0051] performing brightness sorting on the global pixel points of the overall brightness uniform image in the order of pixel brightness value from high to low to obtain a uniform image pixel point sequence with different uniform image pixel point sequence numbers, and collectively taking the pixel points with an image pixel point sequence number greater than a uniform image pixel point sequence number threshold as the local background pixel point, wherein the uniform image pixel point sequence number threshold can be set as required.

[0052] Due to the image characteristics of the base cluster image, after performing brightness sorting on the global pixel points of the overall brightness uniform image in the order of pixel brightness value from high to low, the background pixel point set reflecting the image background brightness condition is concentrated at the low brightness end, and thus the local background pixel point reflecting the image background brightness condition can be quickly obtained by setting a certain threshold, thereby improving the selection efficiency of the local background pixel point.

[0053] In an implementable manner, the brightness detection process of the base cluster carried by the overall brightness uniform image can be as follows: after obtaining the target base cluster image, performing brightness sorting on all pixel points in the image in the order of pixel brightness value from high to low, and then obtaining a pixel brightness value-pixel sequence number curve diagram of all pixel points of the overall brightness uniform image, referring to Figure 5 , Figure 5A curve diagram of pixel point luminance value-pixel point serial number of the overall luminance uniform image, wherein the x-axis is different pixel point serial numbers, and the y-axis is different pixel point luminance values, and then all pixel points with pixel point serial numbers greater than the uniform image pixel point serial number threshold value form a local background pixel point, and the luminance value of any pixel point in the local background pixel point can be directly obtained, and then the pixel point at the middle position in the local background pixel point can be directly taken as the image background luminance value of the overall luminance uniform image, for example, assuming that the pixel point serial numbers of the local background pixel points are 8000-8100, the luminance value of the pixel point with the pixel point serial number 8050 is taken as the image background luminance value of the overall luminance uniform image. The way of intercepting the tail segment pixel points as the local background pixel points has certain stability when detecting the base cluster luminance in the actual application scene, has strong anti-interference ability, and meets the statistical characteristics.

[0054] The step of obtaining the local background pixel point by performing luminance sorting on the global pixel points of the overall luminance discrete image comprises:

[0055] Step B10, dividing the global pixel points of the overall luminance discrete image into at least one unit global pixel point of a unit base cluster image;

[0056] Step B20, for any unit base cluster image, performing luminance sorting on the unit global pixel points of the unit base cluster image to obtain a pixel point sequence;

[0057] Step B30, according to the size relationship between the serial number of the pixel point sequence and the preset serial number threshold value, selecting a unit local background pixel point of the unit base cluster image from the pixel point sequence;

[0058] Step B40, taking the unit local background pixel points of each unit base cluster image as the local background pixel point.

[0059] In this embodiment, it should be noted that for the overall luminance discrete image with non-uniform overall image luminance, the luminance difference between different positions of the image is large, and thus the overall image luminance cannot be reflected by a specific value, so it is necessary to decompose the overall luminance discrete image into a plurality of small local regions, and the luminance of the local region is uniform. Figure 6 , Figure 6The unit base cluster image is used to represent any unit divided from the overall brightness discrete image. For example, assuming that the overall brightness discrete image is divided into a 100*100 grid, each grid can be a unit base cluster image. The unit global pixel point is used to represent all pixel points in the unit base cluster image. The pixel point sequence is used to represent the sorting of the unit global pixel points according to a certain brightness sorting rule, and the pixel point set is configured with a sequence number for the unit global pixel points according to the certain brightness sorting rule. For example, in an implementable manner, assuming that the unit global pixel point includes 100, the unit global pixel points can be sorted according to the brightness value from high to low, and the sequence numbers 1 to 100, to obtain the pixel point sequence.

[0060] As an example, steps B10 to B40 include: dividing the overall brightness discrete image into at least one unit base cluster image, wherein the global pixel points of the overall brightness discrete image are composed of the unit global pixel points of each unit base cluster image; for any unit base cluster image, the brightness of the unit global pixel points in the unit base cluster image is sorted to obtain a pixel point sequence; selecting a sequence number greater than a preset sequence number threshold in the sequence number of the pixel point sequence, and the pixel points corresponding to the sequence number greater than the preset sequence number threshold in the pixel point sequence are collectively composed of the unit local background pixel points of the unit base cluster image, wherein the unit local background pixel points are used to represent the local background pixel points of the unit base cluster image, and the preset sequence number threshold can be set according to requirements; and the unit local background pixel points of each unit base cluster image are collectively used as the local background pixel points.

[0061] In an implementable manner, the procedure of the brightness detection of the to-be-detected base cluster carried by the overall brightness discrete image can be as follows: the overall brightness discrete image is divided into 100 unit base cluster images, and the local background pixel points (i.e., unit local background pixel points) in each unit base cluster image are independently counted. The counting manner can refer to the brightness sorting manner of the overall brightness uniform image, which will not be described herein again. The discrete image pixel point serial number threshold used when all the pixel points in the unit base cluster image are sorted in brightness can be the same as or different from the uniform image pixel point serial number threshold. After the local background pixel points of each unit base cluster image are obtained, the pixel point brightness average of the local background pixel points can be taken as the image background brightness value of the unit base cluster image. When the brightness value of the to-be-detected base cluster is calculated, the calculation can be based on the region to which the to-be-detected base cluster belongs. For example, assuming that the image background brightness value of the unit base cluster image M is m, the image background brightness value of the unit base cluster image N is n, and the measured brightness of the to-be-detected base cluster is h, the brightness detection result of the to-be-detected base cluster when it belongs to the unit base cluster image M is h-m, and the brightness detection result of the to-be-detected base cluster when it belongs to the unit base cluster N is h-n.

[0062] The pixel point sequence includes a local pixel point sequence and a global pixel point sequence, the brightness sorting in the unit global pixel points of the unit base cluster image to obtain the pixel point sequence includes:

[0063] Step C10, extracting local pixel points from the unit global pixel points of the unit base cluster image, and sorting the local pixel points in brightness to obtain the local pixel point sequence; or,

[0064] Step C20, sorting the global pixel points of the unit base cluster image to obtain the global pixel point sequence.

[0065] In this embodiment, it needs to be noted that, in order to further accelerate the obtaining of the pixel point sequence and improve the operation efficiency, when the brightness sorting is performed in the unit global pixel points of the unit base cluster image, all the pixel points of the unit base cluster image can be sorted in brightness, or a sampling manner can be used to sample a plurality of pixel points in the unit global pixel points to perform the brightness sorting, so as to obtain the brightness sorting sequences in different manners. The local pixel point sequence is used to represent a pixel point set in which the local pixel points are arranged according to a certain brightness sorting rule, and the global pixel point sequence is used to represent a pixel point set in which the global pixel points are arranged according to a certain brightness sorting rule. The certain brightness sorting rule can be a sorting rule from high to low or a sorting rule from low to high.

[0066] As an example, steps C10 to C20 include: extracting local pixel points from unit global pixel points of the unit base cluster image, performing brightness sorting on the local pixel points according to the arrangement order from high to low of pixel point brightness values, and obtaining the local pixel point sequence; and performing sorting on global pixel points of the unit base cluster image according to the arrangement order from high to low of pixel point brightness values, and obtaining the global pixel point sequence.

[0067] The sorting manner of extracting local pixel points in an image for brightness sorting or extracting all pixel points in an image for brightness sorting is also applicable to the sorting manner of performing brightness sorting on the overall brightness uniform image, and details are not repeated herein.

[0068] The extracting local pixel points from unit global pixel points of the unit base cluster image includes:

[0069] Step D10, extracting row pixel points of a preset pixel row and column pixel points of a preset pixel column from global pixel points of the unit base cluster image.

[0070] Step D20, taking the row pixel points and the column pixel points as the local pixel points.

[0071] In this embodiment, it should be noted that a specific extraction rule can be formulated when extracting local pixel points, thereby ensuring the extraction stability of the local pixel points in different times, and at the same time, the calculation amount can be further reduced. For example, in an implementable manner, the unit base cluster image can be taken as a calculation unit, and the number of pixel rows and the number of pixel columns of the extracted pixel points are set, 5 row numbers are obtained by an average distribution random method, and 4 column numbers are obtained by an average distribution random method. The pixel points in the 5 rows and 4 columns are extracted for brightness sorting from high to low of pixel point brightness values. The extraction of unit local background pixel points in the pixel point sequence is performed by the above-mentioned setting sequence number threshold manner, and the image background brightness value of each unit base cluster image is finally calculated by averaging.

[0072] As an example, steps D10 to D20 include: extracting row pixel points of a preset pixel row and column pixel points of a preset pixel column from global pixel points of the unit base cluster image; and taking the row pixel points and the column pixel points as the local pixel points.

[0073] The base cluster image to be detected is the overall brightness uniform image, and the step of determining the background brightness value corresponding to the base cluster to be detected according to the local background pixel points includes:

[0074] Step E10, the local background pixel points of the overall brightness uniform image are subjected to brightness mean value processing to obtain a background brightness mean value;

[0075] Step E20, the background brightness mean value is taken as the background brightness value of the to-be-detected base cluster.

[0076] In this embodiment, it should be noted that when the to-be-detected base cluster image is an overall brightness uniform image, since the base clusters are uniformly distributed in the image, the overall background brightness of the image can be reflected by a specific value. However, the median value has a certain error in accuracy for the image region with large background brightness difference. Therefore, by introducing the concept of mean value, the overall brightness of the overall brightness uniform image is fed back to improve the feedback accuracy of the overall background brightness of the overall brightness uniform image, thereby laying a foundation for improving the brightness detection accuracy of the to-be-detected base cluster.

[0077] As an example, steps E10 to E20 include: averaging the pixel brightness values of the local background pixel points of the overall brightness uniform image to obtain a background brightness mean value; and taking the background brightness mean value as the background brightness value of the to-be-detected base cluster.

[0078] The to-be-detected base cluster image is the overall brightness discrete image, and the step of determining the background brightness value corresponding to the to-be-detected base cluster according to the local background pixel points comprises:

[0079] Step F10, according to the position of the to-be-detected base cluster in the overall brightness discrete image, the unit local background pixel point corresponding to the to-be-detected base cluster is queried in the local background pixel points;

[0080] Step F20, the unit local background pixel point is subjected to brightness mean value processing to obtain a unit background brightness mean value;

[0081] Step F30, the unit background brightness mean value is taken as the background brightness value of the to-be-detected base cluster.

[0082] In the embodiment, it is to be noted that when the image of the to-be-detected base cluster is a whole brightness discrete image, the distribution of the base cluster in the image is uneven, and thus the specific value cannot accurately reflect the overall background brightness of the image. In addition, the unit local background pixel point can be selected in the unit base cluster image in the whole brightness discrete image, and thus the unit base cluster image to which the to-be-detected base cluster belongs can be located based on the specific position of the to-be-detected base cluster in the whole brightness discrete image. Then, the image background brightness value that can reflect the image background brightness of the unit base cluster image is used to realize the brightness detection of the to-be-detected base cluster. In this way, the preset pixel point coordinate system can be established with the center point of the whole brightness discrete image as the coordinate origin. The unit base cluster image to which the to-be-detected base cluster belongs is located based on the position of the to-be-detected base cluster in the preset pixel point coordinate system, and the unit local background pixel point of the unit base cluster image is extracted to calculate the background brightness value of the to-be-detected base cluster.

[0083] As an example, steps F10 to F30 include: obtaining the actual position of the to-be-detected base cluster in the whole brightness discrete image in the preset pixel point coordinate system, querying the unit base cluster image to which the to-be-detected base cluster belongs according to the actual position, and querying the unit local background pixel point of the unit base cluster image in the local background pixel point; the pixel point brightness values of the unit local background pixel points are averaged to obtain the unit background brightness mean value; and the unit background brightness mean value is taken as the background brightness value of the to-be-detected base cluster.

[0084] The embodiment of the present application provides a base cluster brightness detection method, that is, selecting a local background pixel point in the global pixel point of a target base cluster image, wherein the target base cluster image carries a to-be-detected base cluster; determining a background brightness value corresponding to the to-be-detected base cluster according to the local background pixel point; and performing brightness detection on the to-be-detected base cluster according to the background brightness value to obtain a brightness detection result.

[0085] The embodiment of the present application selects a local background pixel point in the global pixel point of a target base cluster image carrying a to-be-detected base cluster, and then determines the background brightness value corresponding to the to-be-detected base cluster through the local background pixel point. That is, the image overall background brightness of the target base cluster image is determined through the local background pixel point. Finally, the to-be-detected base cluster is subjected to brightness detection through the background brightness value, that is, a local background pixel point is selected in the global pixel point of a target base cluster image, and then a brightness detection result of a to-be-detected base cluster is obtained through the local background pixel point.

[0086] Since the local background pixel points can detect the brightness of the to-be-detected base cluster, that is, the number of background pixel points extracted when detecting the brightness of the to-be-detected base cluster is reduced, at the same time, the local background pixel points are selected from the global pixel points of the target base cluster image, that is, the target base cluster image carrying the to-be-detected base cluster does not need to be image segmented when detecting the brightness of the to-be-detected base cluster, so the detection process when detecting the brightness of the to-be-detected base cluster is simplified, that is, the purpose of detecting the brightness of the to-be-detected base cluster based on the background brightness value determined by the local pixel points is achieved.

[0087] Based on this, the application selects local background pixel points from the global pixel points of the target base cluster image, and then determines the background brightness value corresponding to the to-be-detected base cluster through the local background pixel points, and finally obtains the brightness detection result of the to-be-detected base cluster through the background brightness value, thereby achieving the purpose of detecting the brightness of the to-be-detected base cluster through the local background pixel points in the target base cluster image, that is, overcoming the technical defects that the calculation of the threshold value of all pixel points in the fluorescence image is required when the fluorescence image is segmented, and the high complexity of the calculation amount will result in long calculation time, and then the sequencing flux is easily limited. Therefore, the detection efficiency of the brightness detection of the base cluster is improved.

[0088] Embodiment two

[0089] Further, with reference to Figure 7 In another embodiment of the application, the same or similar contents as the above-mentioned embodiment one can be referred to the above introduction, and the subsequent will not be described in detail. On this basis, the extracting local pixel points from the unit global pixel points of the unit base cluster image comprises:

[0090] Step G10, obtaining the pixel point coordinate setting value of the random pixel sampling point in the preset pixel point coordinate system of the unit base cluster image;

[0091] Step G20, extracting the local pixel points from the global pixel points of the unit base cluster image according to the pixel point coordinate setting value.

[0092] In the embodiment, it is to be noted that although the setting of the certain pixel point extraction rule can ensure the stability of the pixel point extraction to a certain extent, the too limited extraction rule will result in that the pixel point is not representative, that is, the pixel point extraction lacks a certain randomness, and thus the selected local pixel point cannot feedback the background brightness condition from the global image, and thus a random sampling method is introduced, that is, the sampling density is set, the unit base cluster image is taken as a calculation unit, the sampling pixel points are randomly scattered in the calculation unit, and then the sampling pixel points are sorted in brightness, and the background brightness value corresponding to the to-be-detected base cluster is obtained through the setting of the threshold value of the image background brightness value, wherein the pixel point coordinate setting value can be obtained by the random sampling algorithm, since all the pixel points of the unit base cluster image have actual pixel point coordinates, and thus the actual pixel point of the unit base cluster image at the preset pixel point coordinate system can be inquired through the pixel point coordinate setting value.

[0093] As an example, steps G10 to G20 include: obtaining a pixel point coordinate setting value of a random pixel sampling point in a preset pixel point coordinate system of the unit base cluster image; and extracting the local pixel point from global pixel points of the unit base cluster image by taking the pixel point coordinate setting value as an index.

[0094] Wherein, the random sampling method and the grid extraction method listed in the embodiment one can be used in the process of extracting local pixel points from global pixel points of the overall brightness uniform image, and the embodiment of the present application will not be repeated here.

[0095] The embodiment of the present application provides a local pixel point extraction method, that is, obtaining a pixel point coordinate setting value of a random pixel sampling point in a preset pixel point coordinate system of the unit base cluster image; and extracting the local pixel point from global pixel points of the unit base cluster image according to the pixel point coordinate setting value. The embodiment of the present application sets a preset number of random pixel sampling points, and then indexes the local pixel point from the global pixel points of the unit base cluster image through the pixel point coordinate setting value of the random pixel sampling point in the preset pixel point coordinate system of the unit base cluster image, so as to achieve the purpose of randomly extracting the local pixel point in the unit base cluster image. Therefore, it lays a foundation for improving the detection accuracy and detection efficiency of the brightness detection of the to-be-detected base cluster.

[0096] Embodiment three

[0097] The embodiment of the present application also provides a base cluster brightness detection device, referring to Figure 8 , the base cluster brightness detection device comprises:

[0098] The selecting module 101 is configured to select a local background pixel point from global pixel points of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected;

[0099] The determining module 102 is configured to determine a background brightness value corresponding to the base cluster to be detected according to the local background pixel point;

[0100] The detecting module 103 is configured to perform brightness detection on the base cluster to be detected according to the background brightness value, and obtain a brightness detection result.

[0101] Optionally, the selecting module 101 is further configured to:

[0102] detect an image type of the target base cluster image according to an image brightness variance of the target base cluster image;

[0103] if it is detected that the target base cluster image is an overall brightness uniform image, obtain the local background pixel point by performing brightness sorting on global pixel points of the overall brightness uniform image;

[0104] if it is detected that the target base cluster image is an overall brightness discrete image, obtain the local background pixel point by performing brightness sorting on global pixel points of the overall brightness discrete image.

[0105] Optionally, the selecting module 101 is further configured to:

[0106] divide the global pixel points of the overall brightness discrete image into unit global pixel points of at least one unit base cluster image;

[0107] for any unit base cluster image, perform brightness sorting on the unit global pixel points of the unit base cluster image to obtain a pixel point sequence;

[0108] according to a size relationship between a sequence number of the pixel point sequence and a preset sequence number threshold, select a unit local background pixel point of the unit base cluster image from the pixel point sequence;

[0109] collect the unit local background pixel points of the unit base cluster images as the local background pixel point.

[0110] Optionally, the pixel point sequence includes a local pixel point sequence and a global pixel point sequence, and the selecting module 101 is further configured to:

[0111] extract a local pixel point from the unit global pixel points of the unit base cluster image, perform brightness sorting on the local pixel point, and obtain the local pixel point sequence; or

[0112] Sort the global pixel points of the unit base cluster image to obtain a global pixel point sequence.

[0113] Optionally, the selecting module 101 is further configured to:

[0114] Extract row pixel points of a preset pixel row and column pixel points of a preset pixel column from the global pixel points of the unit base cluster image.

[0115] Take the row pixel points and the column pixel points as the local pixel points.

[0116] Optionally, the selecting module 101 is further configured to:

[0117] Obtain a pixel point coordinate setting value of a random pixel sampling point in a preset pixel point coordinate system of the unit base cluster image.

[0118] Extract the local pixel points from the global pixel points of the unit base cluster image according to the pixel point coordinate setting value.

[0119] Optionally, the base cluster image to be detected is the overall brightness uniform image, and the determining module 102 is further configured to:

[0120] Perform brightness mean value processing on the local background pixel points of the overall brightness uniform image to obtain a background brightness mean value.

[0121] Take the background brightness mean value as the background brightness value of the base cluster to be detected.

[0122] Optionally, the base cluster image to be detected is the overall brightness discrete image, and the determining module 102 is further configured to:

[0123] According to a position of the base cluster to be detected in the overall brightness discrete image, query the unit local background pixel points corresponding to the base cluster to be detected from the local background pixel points.

[0124] Perform brightness mean value processing on the unit local background pixel points to obtain a unit background brightness mean value.

[0125] Take the unit background brightness mean value as the background brightness value of the base cluster to be detected.

[0126] The base cluster brightness detection device provided by the present application adopts the base cluster brightness detection method in the above embodiment, and solves the technical problem of low detection efficiency for brightness detection of base clusters. Compared with the prior art, the base cluster brightness detection device provided by the embodiment of the present application has the same beneficial effects as the base cluster brightness detection method provided by the above embodiment, and other technical features of the base cluster brightness detection device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0127] Embodiment four

[0128] The embodiment of the present application provides an electronic device, which comprises at least one processor and a memory connected with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the base cluster brightness detection method in the above embodiment one.

[0129] Reference will be made to Figure 9 , which shows a structural schematic diagram of an electronic device suitable for implementing the embodiments of the present disclosure. The electronic device in the embodiments of the present disclosure can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablets), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 9 The electronic device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present disclosure.

[0130] As shown in Figure 9 , the electronic device can include a processing device 1001 (such as a central processor, a graphics processor, etc.), which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 to a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for operation of the electronic device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus.

[0131] Generally, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication devices can allow the electronic device to communicate wirelessly or wiredly with other devices to exchange data. Although the electronic device is shown as having various systems, it is understood that all of the shown systems are not required to implement or have. More or less systems can alternatively be implemented or have.

[0132] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication devices 1009, or installed from the storage devices 1003, or installed from the ROM 1002. When the computer program is executed by the processing devices 1001, the above-mentioned functions defined in the methods of embodiments of the present disclosure are performed.

[0133] The electronic device provided by the present application adopts the base cluster brightness detection method in the above-mentioned embodiments, and solves the technical problem of low detection efficiency of brightness detection for base clusters. Compared with the prior art, the electronic device provided by the embodiments of the present application has the same beneficial effects as the base cluster brightness detection method provided by the above-mentioned embodiments, and other technical features in the electronic device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0134] It should be understood that parts of the present disclosure can be realized by hardware, software, firmware, or a combination thereof. In the description of the above-mentioned embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0135] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0136] Example Five

[0137] The embodiment provides a computer readable storage medium having computer readable program instructions stored thereon, and the computer readable program instructions are used for executing the base cluster brightness detection method in the above embodiment.

[0138] The computer readable storage medium provided by the embodiment of the application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination thereof. More specific examples of the computer readable storage medium can include, but are not limited to, an electric connection having one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the embodiment, the computer readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, system, or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (radio frequency), and the like, or any suitable combination of the above.

[0139] The computer readable storage medium described above can be contained in an electronic device, or can exist separately and not be assembled into an electronic device.

[0140] The computer readable storage medium described above carries one or more programs, and when the one or more programs are executed by an electronic device, the electronic device is caused to: select a local background pixel point in a global pixel point of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected; determine a background brightness value corresponding to the base cluster to be detected according to the local background pixel point; and perform brightness detection on the base cluster to be detected according to the background brightness value, to obtain a brightness detection result.

[0141] Computer program code for carrying out operations of the present disclosure can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0142] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0143] The modules involved in the embodiments of the present disclosure can be implemented in the manner of software or hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0144] The computer readable storage medium provided by the present application stores computer readable program instructions for executing the base cluster brightness detection method, and solves the technical problem of low detection efficiency of base cluster brightness detection. Compared with the prior art, the beneficial effects of the computer readable storage medium provided by the embodiments of the present application are the same as those of the base cluster brightness detection method provided by the above embodiments, and are not described here.

[0145] Embodiment six

[0146] The application further provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the base cluster brightness detection method as described above.

[0147] The computer program product provided by the application solves the technical problem of low detection efficiency for brightness detection of base clusters. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the application are the same as those of the base cluster brightness detection method provided by the above-mentioned embodiment, and are not described here.

[0148] The above is only the preferred embodiment of the application, and does not limit the patent scope of the application, and any equivalent structure or equivalent process transformation using the content of the specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent processing scope of the application.

Claims

1. A method for detecting the intensity of a base cluster, characterized by, The base cluster brightness detection method comprises: selecting local background pixels from global pixels of a target base cluster image, wherein the target base cluster image carries a base cluster to be detected; determining a background brightness value corresponding to the base cluster to be detected according to the local background pixels; performing brightness detection on the base cluster to be detected according to the background brightness value to obtain a brightness detection result; wherein the step of selecting local background pixels from global pixels of a target base cluster image comprises: detecting an image type of the target base cluster image according to an image brightness variance of the target base cluster image; if it is detected that the target base cluster image is a whole brightness uniform image, then performing brightness sorting on global pixels of the whole brightness uniform image to obtain the local background pixels; if it is detected that the target base cluster image is a whole brightness discrete image, then performing brightness sorting in global pixels of the whole brightness discrete image to obtain the local background pixels; wherein the step of performing brightness sorting on global pixels of the whole brightness uniform image to obtain the local background pixels comprises: performing brightness sorting on global pixels of the whole brightness uniform image in the order of pixel brightness value from high to low to obtain uniform image pixel sequences marked with different uniform image pixel sequence numbers; collecting pixels with sequence numbers greater than a uniform image pixel sequence number threshold as the local background pixels; wherein the step of performing brightness sorting in global pixels of the whole brightness discrete image to obtain the local background pixels comprises: dividing global pixels of the whole brightness discrete image into unit global pixels of at least one unit base cluster image; for any unit base cluster image, performing brightness sorting in unit global pixels of the unit base cluster image to obtain a pixel sequence; selecting unit local background pixels of the unit base cluster image from the pixel sequence according to a size relationship between a sequence number of the pixel sequence and a preset sequence number threshold; collecting unit local background pixels of each unit base cluster image as the local background pixels.

2. The base cluster brightness detection method as described in claim 1, characterized in that, The pixel sequence comprises local pixel sequences and global pixel sequences, the step of performing brightness sorting in unit global pixels of the unit base cluster image to obtain a pixel sequence comprises: extracting local pixels from unit global pixels of the unit base cluster image, and performing brightness sorting on the local pixels to obtain the local pixel sequences; or performing sorting on global pixels of the unit base cluster image to obtain the global pixel sequences.

3. The base cluster brightness detection method as described in claim 2, characterized in that, the step of extracting local pixels from unit global pixels of the unit base cluster image comprises: extracting row pixels of a preset pixel row and column pixels of a preset pixel column from global pixels of the unit base cluster image; collecting the row pixels and the column pixels as the local pixels.

4. The base cluster brightness detection method as described in claim 2, characterized in that, the step of extracting local pixels from unit global pixels of the unit base cluster image comprises: Obtaining a pixel coordinate setting value of a random pixel sampling point in a preset pixel coordinate system of the unit base cluster image; According to the pixel coordinate setting value, extracting the local pixel point from global pixel points of the unit base cluster image.

5. The method for detecting the brightness of base clusters as described in claim 1, characterized in that, The base cluster image to be detected is the whole brightness uniform image, The step of determining the background brightness value corresponding to the base cluster to be detected according to the local background pixel point comprises: Performing brightness mean value processing on the local background pixel point of the whole brightness uniform image to obtain a background brightness mean value; Taking the background brightness mean value as the background brightness value of the base cluster to be detected.

6. The base cluster brightness detection method as described in claim 1, characterized in that, The base cluster image to be detected is the whole brightness discrete image, The step of determining the background brightness value corresponding to the base cluster to be detected according to the local background pixel point comprises: According to the position of the base cluster to be detected in the whole brightness discrete image, querying the unit local background pixel point corresponding to the base cluster to be detected in the local background pixel point; Performing brightness mean value processing on the unit local background pixel point to obtain a unit background brightness mean value; Taking the unit background brightness mean value as the background brightness value of the base cluster to be detected.

7. An electronic device, comprising: The electronic device comprises: at least one processor; a memory connected in communication with the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the base cluster brightness detection method in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a program for implementing a base cluster brightness detection method, and the program is executed by a processor to implement the steps of the base cluster brightness detection method in any one of claims 1 to 6.

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