CN111141208B - Parallel line detection method and device - Google Patents

Abstract

The present application provides a parallel line detection method and device, including: acquiring an image to be detected; determining the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the to-be-detected image ; Map the position coordinates of each pixel point to the polar coordinate system to obtain the mapping line corresponding to each pixel point, and determine the feature point where at least two mapping lines intersect in the polar coordinate system; Determine the distance between the feature points as The two feature points of the preset distance are feature point pairs; according to the feature point pairs that meet the preset conditions, the parallel lines in the image to be detected are determined. Through this method, the parallel lines in the image to be detected can be directly determined according to the selected feature point pairs, without first determining the straight lines and then determining the parallel lines, which improves the efficiency of parallel line detection.

Description

Method and device for detecting parallel lines

technical field

The present application relates to the technical field of image detection, and in particular, to a parallel line detection method and device.

Background technique

When testing components, such as testing whether the size of components meets the requirements, the parallel line detection algorithm is generally used.

At present, in the method of determining the parallel lines of the preset distance in the image to be detected, all the straight lines in the image to be detected are detected first, and then the parallel lines that satisfy the preset distance condition are selected from the obtained straight lines, and there is a detection speed. slow problem.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present application is to provide a parallel line detection method and device to improve the efficiency of parallel line detection in image detection.

In a first aspect, an embodiment of the present application provides a parallel line detection method, including:

Obtain the image to be detected;

Determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected;

The position coordinates of each pixel point are mapped to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and the feature point at which at least two mapping curves intersect in the polar coordinate system is determined;

Determine that two feature points whose distances between the feature points are preset distances are feature point pairs;

Determine the parallel lines in the to-be-detected image according to the feature point pairs that meet the preset conditions.

In conjunction with the first aspect, the embodiment of the present application provides a first possible implementation manner of the first aspect, wherein the parallel lines in the image to be detected are determined according to the feature point pair that meets a preset condition, include:

Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point;

Calculate the sum of the gradient values of the first selected pixel point;

Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair;

Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point;

According to the second selected pixel points, the parallel lines in the to-be-detected image are determined.

With reference to the first possible implementation manner of the first aspect, the embodiment of the present application provides the second possible implementation manner of the first aspect, wherein the sum of the gradient values is to the feature points that satisfy the preset gradient condition Yes, identified as the selected feature point pair, including:

Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or,

Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer.

In conjunction with the first aspect, the embodiment of the present application provides a third possible implementation manner of the first aspect, wherein, according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel in the to-be-detected image, Determine the gradient value of each pixel, including:

For the i-th pixel in the to-be-detected image, perform the following operations:

Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively;

determining the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value;

Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel.

In conjunction with the third possible implementation manner of the first aspect, the embodiment of the present application provides the fourth possible implementation manner of the first aspect, wherein when the third gradient value is not within the preset gradient value range, the third Gradient values, including:

When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range;

When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range.

In a second aspect, an embodiment of the present application also provides a parallel line detection device, including:

an acquisition module for acquiring the image to be detected;

a first determination module, configured to determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the to-be-detected image;

The second determination module is used to map the position coordinates of each pixel point to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and determine the feature point where at least two mapping curves intersect in the polar coordinate system;

a third determining module, configured to determine that two feature points whose distances between the feature points are preset distances are feature point pairs;

The fourth determination module is configured to determine parallel lines in the image to be detected according to the feature point pairs that meet the preset conditions.

In conjunction with the second aspect, the embodiment of the present application provides a first possible implementation manner of the second aspect, wherein the fourth determination module determines the to-be-detected feature point pair according to the feature point pair that meets a preset condition When parallel lines in an image, specifically for:

Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point;

Calculate the sum of the gradient values of the first selected pixel point;

Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair;

Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point;

According to the second selected pixel points, the parallel lines in the to-be-detected image are determined.

With reference to the first possible implementation manner of the second aspect, the embodiment of the present application provides a second possible implementation manner of the second aspect, wherein, the fourth determination module, after determining that the sum of the gradient values satisfies the predetermined When the feature point pair of the gradient condition is set as the selected feature point pair, it is specifically used for:

Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or,

Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer.

In conjunction with the second aspect, the embodiment of the present application provides a third possible implementation manner of the second aspect, wherein the first determination module is based on the horizontal gradient and the horizontal gradient of each pixel point in the to-be-detected image. The vertical gradient in the vertical direction, when determining the gradient value of each pixel, is specifically used for:

For the i-th pixel in the to-be-detected image, perform the following operations:

Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively;

determining the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value;

Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel.

In conjunction with the third possible implementation manner of the second aspect, the embodiment of the present application provides a fourth possible implementation manner of the second aspect, wherein, the first determination module, when the third gradient value is not in the preset gradient When the value is within the range, when adjusting the third gradient value, it is specifically used for:

When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range;

When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range.

In a third aspect, embodiments of the present application further provide an electronic device, including: a processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor, and when the electronic device runs, the processing A bus communicates between the processor and the memory, and when the machine-readable instructions are executed by the processor, the first aspect or the steps in any possible implementation manner of the first aspect are performed.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to execute the first aspect, or any of the first aspect. steps in one possible implementation.

In the straight line detection method and device provided by the embodiment of the present application, the gradient value of each pixel point is determined by the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected; and then the position coordinates of each pixel point are mapped. In the polar coordinate system, the mapping curve corresponding to each pixel point is obtained, and the feature point where the mapping curve intersects is determined in the polar coordinate system, and then at least one pair of feature point pairs with a preset distance is screened from the feature points, and Determine the parallel lines in the image to be detected according to the feature point pairs that meet the preset conditions. Through the above method, the parallel lines in the image to be detected can be directly determined according to the selected feature point pairs, without first determining the straight line and then determining the parallel line, which improves the efficiency of parallel line detection.

In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the preferred embodiments are exemplified below, and are described in detail as follows in conjunction with the accompanying drawings.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present application more clearly, the following drawings will briefly introduce the drawings that need to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore do not It should be regarded as a limitation of the scope, and for those of ordinary skill in the art, other related drawings can also be obtained according to these drawings without any creative effort.

1 shows a schematic flowchart of a parallel line detection method provided by an embodiment of the present application;

FIG. 2 shows a schematic flowchart of a method for determining a pixel point gradient value provided by an embodiment of the present application;

FIG. 3 shows a vector summation method provided by an embodiment of the present application;

4 shows a schematic flowchart of a method for determining parallel lines in an image to be detected according to feature point pairs that meet preset conditions provided by an embodiment of the present application;

FIG. 5 shows a schematic structural diagram of a parallel line detection apparatus 600 provided by an embodiment of the present application;

FIG. 6 shows a schematic structural diagram of an electronic device 700 provided by an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of the present application, but not all of the embodiments. The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

First, the applicable application scenarios of the method provided in this application are introduced. The method provided in this application can be applied to parallel line detection at a fixed distance, such as locating a rectangular object of known width in an image. In the prior art, for the detection of parallel lines with a fixed distance, a straight line is detected first, then the parallel lines are detected according to the detected straight line, and then the parallel lines with a fixed distance are determined according to the distance between the detected parallel lines. The detection efficiency is low.

In the method provided by the present application, each pixel point of the image to be detected is mapped into the polar coordinate system, and the feature points are determined according to the mapping curve corresponding to the pixel points in the polar coordinate system, and then the feature points are selected according to the distance between the feature points. Feature point pairs are obtained, and finally, according to the feature point pairs that meet the preset conditions, the parallel lines in the image to be detected are determined. The parallel lines are determined directly according to the selected feature point pairs that meet the preset conditions, and the detection efficiency is high.

In order to facilitate the understanding of this embodiment, a parallel line detection method disclosed in the embodiment of this application is first introduced in detail.

Example 1

Referring to FIG. 1 , a schematic flowchart of a parallel line detection method provided by an embodiment of the present application includes the following steps:

S101. Acquire an image to be detected.

S102: Determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected.

In specific implementation, for the ith pixel in the image to be detected, the gradient value of the ith pixel can be determined according to the method for determining the gradient value of the pixel as shown in Figure 2, including the following steps:

S201. Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively.

In a possible implementation manner, set the position of the i-th pixel in the image to be detected as the j-th row and the k-th column, then the first gradient value in the horizontal direction of the i-th pixel can be calculated according to the following formula :

i ₁ =a _j,k+1 -a _j,k-1

Among them, i ₁ represents the first gradient value in the horizontal direction of the ith pixel point, a _{j, k+1} represents the pixel value of the pixel point in the jth row and the k+1th column, and a _{j, k-1} represents the jth row. The pixel value of the pixel in the k-1th column.

Similarly, the second gradient value in the vertical direction of the ith pixel can be calculated according to the following formula:

i ₂ =a _j+1,k -a _j-1,k

Among them, i ₂ represents the second gradient value in the horizontal direction of the i-th pixel point, a _{j+1, k} represents the pixel value of the j+1-th row and k-th column pixel point, a _{j-1, k} represents the j-th The pixel value of the pixel in row 1 and column k.

S202. Determine the third gradient value of the ith pixel point according to the first gradient value and the second gradient value.

In a possible implementation manner, the third gradient value of the i-th pixel point can be calculated according to the vector summation method. As shown in the vector summation method shown in FIG. 3 , let OA be the first gradient value and OB be the first gradient value For the second gradient value, according to the vector summation method, the magnitude and direction of the third gradient value OC can be calculated.

Specifically, the third gradient value can be calculated according to the following formula:

Wherein, i ₁ represents the first gradient value in the horizontal direction of the ith pixel, i ₂ represents the second gradient value in the vertical direction of the ith pixel, and i ₃ represents the third gradient value of the ith pixel.

S203. Determine whether the third gradient value is within a preset gradient value range.

If the judgment result is yes, step S204 is executed sequentially;

If the judgment result is no, step S205 is executed.

In an example of the present application, the preset gradient value range may be [-127, 127], or the preset gradient value range may be set according to specific conditions, which is not limited in this application.

S204. Determine the third gradient value as the gradient value of the i-th pixel point.

S205: Adjust the third gradient value, and determine the adjusted third gradient value as the gradient value of the ith pixel.

In a possible scenario, there may be noise in the image to be detected, causing the calculated third gradient value to be too large or too small. Adjust the pixels that are not in the preset gradient value range to the preset gradient value range.

During specific implementation, when the third gradient value is smaller than the minimum value of the preset gradient value range, the third gradient value can be adjusted to the minimum value of the preset gradient value range; when the third gradient value is greater than the maximum value of the preset gradient value range When the value is set, the third gradient value is adjusted to the maximum value of the preset gradient value range.

S103: Map the position coordinates of each pixel point to a polar coordinate system to obtain a mapping curve corresponding to each pixel point, and determine a feature point where at least two mapping curves intersect in the polar coordinate system.

The position coordinates of the pixel points determined in the image to be detected are two-dimensional rectangular coordinates, and a corresponding mapping curve is obtained by mapping the points in the two-dimensional rectangular coordinates to the polar coordinate system.

The position coordinates of each pixel in the image to be detected are mapped to the polar coordinate system, each pixel corresponds to a mapping curve, and the intersection of the mapping curves in the polar coordinate system may correspond to a straight line in the two-dimensional rectangular coordinate system.

S104. Determine two feature points whose distance between the feature points is a preset distance as a feature point pair.

A feature point in the polar coordinate system may correspond to a straight line in a two-dimensional rectangular coordinate system, and two feature points with a distance L in the polar coordinate system may correspond to a set of parallel lines with a distance L. Therefore, by selecting two feature points whose distance between the feature points is a preset distance as the feature point pair, and then according to the gradient value of the pixel points corresponding to the mapping curve of the feature points included in the feature point pair, the distance is selected as Parallel lines at a preset distance.

For example, suppose the preset distance is W, the polar coordinate system contains five feature points A, B, C, D, and E, the distance between A and B is W, and the distance between A and D is also W, then A and B, A and D are respectively determined as feature point pairs.

S105. Determine parallel lines in the image to be detected according to the pair of feature points that meet the preset condition.

In a possible implementation, the method shown in FIG. 4 can be used to determine the parallel lines in the image to be detected according to the feature point pairs that meet the preset conditions, including the following steps:

S501. Determine the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs as the first selected pixel point.

S502. Calculate the sum of the gradient values of the first selected pixel point.

S503: Determine the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair.

When the feature point pair whose sum of gradients satisfies the preset gradient condition is determined as the selected feature point pair, the feature point pair whose sum of gradient values is greater than the preset threshold may be determined as the selected feature point pair; The sum of the gradient values corresponding to each feature point pair is sorted in descending order, and the feature point pair arranged in the top M is determined as the selected feature point pair, where M is a positive integer.

S504. Determine the pixel point corresponding to each mapping curve of the feature points included in the selected feature point pair as the second selected pixel point.

S505. Determine parallel lines in the image to be detected according to the second selected pixel point.

The second selected pixel point is a pixel point on the parallel line in the image to be detected, therefore, the parallel line in the image to be detected can be determined by the selected second selected pixel point.

In an example of the present application, if it is determined that there are more than one group of parallel lines in the image to be detected after the above steps S101 to S105, the sum of the gradient values corresponding to each group of parallel lines can be output, and the corresponding gradient values in the image to be detected can be output. Label each group of parallel lines. For example, two straight lines of the same group of parallel lines can be marked with the same color, and parallel lines of different groups can be marked with different colors, and the gradient values corresponding to each group of parallel lines can be output. And, the user can determine the required parallel lines according to the parallel lines marked in the image to be detected and the sum of the gradient values corresponding to each group of parallel lines.

In the straight line detection method provided by the embodiment of the present application, the gradient value of each pixel point is determined by the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected; and then the position coordinates of each pixel point are mapped to the polar In the coordinate system, the mapping curve corresponding to each pixel point is obtained, and the feature point where the mapping curve intersects is determined in the polar coordinate system, and then at least a pair of feature point pairs whose distance is a preset distance are screened out from the feature points, and according to the The feature point pairs of the preset conditions determine the parallel lines in the image to be detected. Through the above method, the parallel lines in the image to be detected can be directly determined according to the selected feature point pairs, without first determining the straight line and then determining the parallel line, which improves the efficiency of parallel line detection.

Embodiment 2

An embodiment of the present application provides a parallel line detection device. Referring to FIG. 5 , which is a schematic diagram of the structure of a parallel line detection device 600 provided by an embodiment of the present application, the device 600 includes: an acquisition module 601 , a first determination module 602 , The second determination module 603, the third determination module 604, and the fourth determination module 605, specifically:

an acquisition module 601, configured to acquire an image to be detected;

a first determination module 602, configured to determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the to-be-detected image;

The second determination module 603 is used to map the position coordinates of each pixel point to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and determine the feature point where at least two mapping curves intersect in the polar coordinate system;

A third determining module 604, configured to determine that two feature points whose distances between the feature points are preset distances are feature point pairs;

The fourth determination module 605 is configured to determine parallel lines in the image to be detected according to the feature point pairs that meet the preset conditions.

In a possible implementation manner, the fourth determining module 605, when determining the parallel lines in the image to be detected according to the feature point pairs that meet the preset conditions, is specifically used for:

Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point;

Calculate the sum of the gradient values of the first selected pixel point;

Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair;

Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point;

According to the second selected pixel points, the parallel lines in the to-be-detected image are determined.

In a possible implementation manner, when the fourth determination module 605 determines the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair, it is specifically used for:

Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or,

Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer.

In a possible implementation manner, the first determination module 602, when determining the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected, specifically: Used for:

For the i-th pixel in the to-be-detected image, perform the following operations:

Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively;

determining the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value;

Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel.

In a possible implementation manner, the first determination module 602, when adjusting the third gradient value when the third gradient value is not within the preset gradient value range, is specifically configured to:

When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range;

When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range.

The device provided in this embodiment can directly determine the parallel lines in the image to be detected according to the selected feature point pairs, without first determining the straight line and then determining the parallel line, which improves the efficiency of parallel line detection.

Embodiment 3

Based on the same technical concept, the embodiments of the present application also provide an electronic device. Referring to FIG. 6 , a schematic structural diagram of an electronic device 700 provided in an embodiment of the present application includes a processor 701 , a memory 702 , and a bus 703 . Among them, the memory 702 is used to store the execution instructions, including the memory 7021 and the external memory 7022; the memory 7021 here is also called the internal memory, which is used to temporarily store the operation data in the processor 701 and the data exchanged with the external memory 7022 such as the hard disk, The processor 701 exchanges data with the external memory 7022 through the memory 7021. When the electronic device 700 is running, the processor 701 communicates with the memory 702 through the bus 703, so that the processor 701 executes the following instructions:

Obtain the image to be detected;

Determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected;

The position coordinates of each pixel point are mapped to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and the feature point at which at least two mapping curves intersect in the polar coordinate system is determined;

Determine that two feature points whose distances between the feature points are preset distances are feature point pairs;

Determine the parallel lines in the to-be-detected image according to the feature point pairs that meet the preset conditions.

In a possible design, in the processing performed by the processor 701, the determination of the parallel lines in the to-be-detected image according to the feature point pair that meets the preset condition includes:

Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point;

Calculate the sum of the gradient values of the first selected pixel point;

Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair;

Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point;

According to the second selected pixel points, the parallel lines in the to-be-detected image are determined.

In a possible design, in the processing performed by the processor 701, the feature point pair whose sum of the gradient values satisfies the preset gradient condition is determined as the selected feature point pair, including:

Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or,

Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer.

In a possible design, in the processing performed by the processor 701, the determination of the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected includes:

For the i-th pixel in the to-be-detected image, perform the following operations:

Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively;

determining the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value;

Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel.

In a possible design, in the processing performed by the processor 701, when the third gradient value is not within the preset gradient value range, adjusting the third gradient value includes:

When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range;

When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range.

Embodiment 4

Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the parallel line detection method described in any of the foregoing embodiments are executed .

Specifically, the storage medium can be a general storage medium, such as a removable disk, a hard disk, etc. When the computer program on the storage medium is run, the steps of the parallel line detection method can be executed, thereby improving the efficiency of parallel line detection.

The computer program product for performing the parallel line detection method provided by the embodiments of the present application includes a computer-readable storage medium storing a non-volatile program code executable by a processor, and the instructions included in the program code can be used to execute the foregoing method. For the specific implementation of the method described in the embodiment, reference may be made to the method embodiment, which will not be repeated here.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. The apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces, indirect coupling or communication connection of devices or units, which may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a processor-executable non-volatile computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program codes.

Finally, it should be noted that the above-mentioned embodiments are only specific implementations of the present application, and are used to illustrate the technical solutions of the present application, rather than limit them. The embodiments describe the application in detail, and those of ordinary skill in the art should understand that: any person skilled in the art can still modify the technical solutions described in the foregoing embodiments within the technical scope disclosed in the application. Or can easily think of changes, or equivalently replace some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the application, and should be covered in this application. within the scope of protection. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims (10)

1. a parallel line detection method, is characterized in that, comprises: Obtain the image to be detected; Determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected; The position coordinates of each pixel point are mapped to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and the feature point at which at least two mapping curves intersect in the polar coordinate system is determined; Determine that two feature points whose distances between the feature points are preset distances are feature point pairs; Determine the parallel lines in the to-be-detected image according to the feature point pairs that meet the preset conditions; The determining the parallel lines in the to-be-detected image according to the feature point pairs that meet the preset conditions, includes: Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point; Calculate the sum of the gradient values of the first selected pixel point; Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair; Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point; According to the second selected pixel points, the parallel lines in the to-be-detected image are determined. 2. The method according to claim 1, wherein the feature point pair whose sum of the gradient values satisfies a preset gradient condition is determined as the selected feature point pair, comprising: Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or, Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer. 3. The method according to claim 1, wherein, determining the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected, comprising: For the i-th pixel in the to-be-detected image, perform the following operations: Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively; Determine the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value; wherein, the third gradient value is a vector of the first gradient value and the second gradient value. generated by summation; Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel. 4. The method according to claim 3, wherein when the third gradient value is not within the preset gradient value range, adjusting the third gradient value, comprising: When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range; When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range. 5. A parallel line detection device, characterized in that, comprising: an acquisition module for acquiring the image to be detected; a first determination module, configured to determine the gradient value of each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the to-be-detected image; The second determination module is used to map the position coordinates of each pixel point to the polar coordinate system to obtain the mapping curve corresponding to each pixel point, and determine the feature point where at least two mapping curves intersect in the polar coordinate system; a third determining module, configured to determine that two feature points whose distances between the feature points are preset distances are feature point pairs; a fourth determination module, configured to determine parallel lines in the to-be-detected image according to the pair of feature points that meet preset conditions; The fourth determination module, when determining the parallel lines in the to-be-detected image according to the feature point pairs that meet the preset conditions, is specifically used for: Determine that the pixel point corresponding to the mapping curve of the feature points included in each pair of feature point pairs is the first selected pixel point; Calculate the sum of the gradient values of the first selected pixel point; Determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair; Determine that the pixel point corresponding to each mapping curve of the feature point included in the selected feature point pair is the second selected pixel point; According to the second selected pixel points, the parallel lines in the to-be-detected image are determined. 6. The apparatus according to claim 5, wherein the fourth determination module, when determining the feature point pair whose sum of the gradient values satisfies the preset gradient condition as the selected feature point pair, specifically Used for: Determine the feature point pair whose sum of gradient values is greater than the preset threshold as the selected feature point pair; or, Sort the sum of the gradient values corresponding to each feature point pair in descending order, and determine the feature point pair arranged in the top M positions as the selected feature point pair, where M is a positive integer. 7 . The device according to claim 5 , wherein the first determination module determines each pixel point according to the horizontal gradient in the horizontal direction and the vertical gradient in the vertical direction of each pixel point in the image to be detected. 8 . When the gradient value of , is used for: For the i-th pixel in the to-be-detected image, perform the following operations: Calculate the first gradient value in the horizontal direction and the second gradient value in the vertical direction of the ith pixel respectively; Determine the third gradient value of the i-th pixel point according to the first gradient value and the second gradient value; wherein, the third gradient value is a vector of the first gradient value and the second gradient value. generated by summation; Judging whether the third gradient value is within the preset gradient value range, if the judgment result is yes, then the third gradient value is determined as the gradient value of the i-th pixel point; if the judgment result is no, then The third gradient value is adjusted, and the adjusted third gradient value is determined as the gradient value of the ith pixel. 8. The device according to claim 7, wherein the first determination module, when adjusting the third gradient value when the third gradient value is not within the preset gradient value range, is specifically used for: When the third gradient value is smaller than the minimum value of the preset gradient value range, adjusting the third gradient value to the minimum value of the preset gradient value range; When the third gradient value is greater than the maximum value of the preset gradient value range, the third gradient value is adjusted to the maximum value of the preset gradient value range. 9. An electronic device, comprising: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the The memories communicate with each other through a bus, and the machine-readable instructions execute the steps of the parallel line detection method according to any one of claims 1 to 4 when the machine-readable instructions are executed by the processor. 10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program executes the parallel line detection method according to any one of claims 1 to 4 when the computer program is run by a processor A step of.

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