CN110660096A - Curve consistency detection method and storage medium - Google Patents
Curve consistency detection method and storage medium Download PDFInfo
- Publication number
- CN110660096A CN110660096A CN201910951457.3A CN201910951457A CN110660096A CN 110660096 A CN110660096 A CN 110660096A CN 201910951457 A CN201910951457 A CN 201910951457A CN 110660096 A CN110660096 A CN 110660096A
- Authority
- CN
- China
- Prior art keywords
- curve
- detected
- pixel
- difference
- coordinate system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a curve consistency detection method and a storage medium, wherein the method comprises the following steps: converting a plurality of curve images to be detected into a preset color space to obtain a color space parameter value of each curve image to be detected, extracting pixel coordinate information of a curve in each curve image to be detected according to the color space parameter value of each curve image to be detected, drawing a curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected, and performing consistency detection on a plurality of groups of curves to be detected drawn in the pixel coordinate system to obtain a detection result.
Description
Technical Field
The invention relates to the field of image processing, in particular to a curve consistency detection method and a storage medium.
Background
The relationship and difference between the experimental curves generated by the experimental instrument are the key points of research by researchers, and the experimental curves are usually related to many factors such as time, temperature, equipment parameters and the like, and once the factors are changed, the experimental curves are changed. Most of the existing experimental instruments do not have the function of detecting the consistency of similar experimental curves for a plurality of experimental curve pictures containing the similar experimental curves, and usually, the plurality of experimental curve pictures can only be exported and compared and detected manually; however, the experiment curves are usually complex and changeable, and some similar experiment curves which need to be compared and detected have very high similarity and are not obvious in difference, and the prior art has the problems that the consistency of the similar experiment curves which are respectively in a plurality of experiment curve pictures is high in detection difficulty and the detection result is easy to make mistakes. Therefore, it is an urgent technical problem to provide a method capable of redrawing a plurality of curves to be detected in a plurality of pictures to be obtained under the same pixel coordinate system and performing consistency detection on the plurality of curves to be detected under the same pixel coordinate system.
Disclosure of Invention
The invention provides a curve consistency detection method, which solves the problems that the consistency of similar experiment curves respectively in a plurality of experiment curve pictures is high in detection difficulty and detection results are easy to make mistakes, and achieves the purposes of redrawing a plurality of obtained curves to be detected respectively in a plurality of pictures to the same pixel coordinate system and carrying out consistency detection on a plurality of curves to be detected under the same pixel coordinate system.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
a curve consistency detection method comprises the following steps:
converting the plurality of curve images to be detected into a preset color space to obtain a color space parameter value of each curve image to be detected;
extracting pixel coordinate information of a curve in each to-be-detected curve image according to the color space parameter value of each to-be-detected curve image;
drawing a curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected;
and carrying out consistency detection on a plurality of groups of curves to be detected drawn in the pixel coordinate system to obtain a detection result.
In a preferred choice of the embodiment of the present invention, in the method for detecting consistency of curves, the step of converting the plurality of images of the curves to be detected into the preset color space includes:
carrying out distortion-free conversion on a plurality of curve images to be detected, and respectively storing the plurality of curve images to be detected after the distortion-free conversion into a preset picture format;
and respectively converting the plurality of curve images to be detected stored in the preset picture format into preset color spaces.
In a preferred option of the embodiment of the present invention, in the method for detecting consistency of curves, the step of extracting pixel coordinate information of a curve in each image of the curves to be detected according to a color space parameter value of each image of the curves to be detected includes:
removing image content which does not include a curve area to be detected in the curve image to be detected according to the color space parameter value of each curve image to be detected so as to extract a mask of a curve in each curve image to be detected, and obtaining pixel coordinate information of the curve in the curve image to be detected according to the mask of the curve in the curve image to be detected.
In a preferred option of the embodiment of the present invention, in the method for detecting consistency of curves, the step of obtaining pixel coordinate information of a curve in the image of the curve to be detected according to a mask of the curve in the image of the curve to be detected includes:
and summarizing the pixel coordinates of the highest point of each column in the mask of the curve in the image of the curve to be detected to obtain the pixel coordinate information of the curve in the image of the curve to be detected.
In a preferred selection of the embodiment of the present invention, in the method for detecting consistency of curves, the step of performing consistency detection on a plurality of groups of curves to be detected, which are obtained by plotting in a pixel coordinate system, to obtain a detection result includes:
performing difference calculation on the vertical coordinates of all the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected to obtain the vertical coordinate difference value between the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected;
drawing a difference value curve according to the longitudinal coordinate difference value;
determining whether a plurality of groups of curves to be detected are consistent or not according to the vertical coordinates of the difference curves, wherein when all the vertical coordinates of the difference curves are zero, a plurality of the curves to be detected are consistent; and when the vertical coordinates of the difference curves are not all zero, the multiple curves to be detected are inconsistent.
In a preferred selection of the embodiment of the present invention, in the method for detecting consistency of curves, after the step of performing consistency detection on a plurality of groups of curves to be detected to obtain a detection result, the method further includes:
and establishing a mapping relation between a pixel coordinate system and a rectangular coordinate system, converting the difference curve in the pixel coordinate system into the rectangular coordinate system according to the mapping relation to obtain a target difference curve, and quantitatively judging the difference of the to-be-detected curves according to the target difference curve.
In a preferred option of the embodiment of the present invention, in the method for detecting consistency of curves, the step of converting the difference curve in the pixel coordinate system into the rectangular coordinate system according to the mapping relationship to obtain the target difference curve includes:
taking a difference value between a starting value of an abscissa and an ending value of the abscissa in the rectangular coordinate system as a rectangular abscissa difference value, and taking a difference value between the starting value of the abscissa and the ending value of the abscissa in the pixel coordinate system as a pixel abscissa difference value;
taking the ratio of the abscissa of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel abscissa as the ratio of the abscissa of the difference curve in the rectangular coordinate system to the difference value of the rectangular coordinate system, and thus calculating the abscissa of the target point in the rectangular coordinate system corresponding to the abscissa of each pixel point in the pixel coordinate system of the difference curve;
taking a difference value between a starting value of a vertical coordinate and an ending value of the vertical coordinate in the rectangular coordinate system as a rectangular vertical coordinate difference value, and taking a difference value between the starting value of the vertical coordinate and the ending value of the vertical coordinate in the pixel coordinate system as a pixel vertical coordinate difference value;
taking the ratio of the ordinate of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel ordinate as the ratio of the ordinate of the target point in the rectangular coordinate system to the difference value of the rectangular ordinate, thereby calculating the ordinate of each pixel point in the pixel coordinates of the difference curve corresponding to the ordinate of the target point in the rectangular coordinate system;
and drawing in the rectangular coordinate system according to the abscissa and the ordinate of each pixel point in the difference curve in the rectangular coordinate system to obtain a target difference curve.
In a preferred choice of the embodiment of the present invention, in the method for detecting consistency of curves, before the step of converting the plurality of images of curves to be detected into the preset color space, the method further includes:
and setting different colors for the curve image to be detected containing the curve area to be detected and the curve area not to be detected.
In a preferred option of the embodiment of the present invention, in the method for detecting consistency of a curve, the preset color space includes an HSV color space.
The present invention also provides a storage medium storing a computer program executable by one or more processors for implementing the curve consistency detection method in any one of the above.
According to the curve consistency detection method and the storage medium, provided by the invention, the color space parameter value of each curve image to be detected is obtained by converting a plurality of curve images to be detected into the preset color space; extracting pixel coordinate information of a curve in each to-be-detected curve image according to the color space parameter value of each to-be-detected curve image; drawing a curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected; the consistency detection is carried out on the multiple groups of curves to be detected obtained by drawing in the pixel coordinate system to obtain the detection result, so that the problems that the detection difficulty is high and the detection result is easy to make mistakes when directly carrying out the consistency detection on the similar experiment curves which are respectively in the multiple experiment curve pictures are solved, and the purposes that the multiple obtained curves to be detected which are respectively in the multiple pictures are redrawn under the same pixel coordinate system and the consistency detection is carried out on the multiple curves to be detected which are under the same pixel coordinate system are achieved.
Drawings
The scope of the present disclosure will be better understood from the following detailed description of exemplary embodiments, which is to be read in connection with the accompanying drawings. Wherein the included drawings are:
FIG. 1 is a flow chart of a curve consistency detection method according to an embodiment of the present invention;
FIG. 2 is a flowchart of a curve consistency detection method according to an embodiment of the present invention;
fig. 3 is a further flowchart of the curve consistency detection method according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Referring to fig. 1, an embodiment of the invention provides a method for detecting consistency of a curve, which includes steps S110 to S140.
Step S110: and converting the plurality of curve images to be detected into a preset color space to obtain the color space parameter value of each curve image to be detected.
It can be understood that the formats of the pictures respectively containing the curve image to be detected may be special formats, and many picture processing software cannot directly process the pictures in the special formats, so that the pictures in the special formats need to be converted into the preset pictures in the general format; wherein the special format includes but is not limited to: WMF format, Pixar format, PCX format, and MPO format, the general formats including but not limited to: PNG format, JPG format, JPEG format, and GIF format.
Specifically, in the process of converting the picture in the special format into the picture in the general format, a distortion-free conversion mode should be adopted to retain as much information in the picture in the original special format as possible, for example, the picture in the special format may be converted into the picture in the PDF format, and then the picture in the PDF format may be stored as the preset picture in the general format, wherein the picture in the PDF format is adopted as the transit picture, so that the information in the picture in the special format is ensured not to be distorted.
In this embodiment, the step of converting the plurality of curve images to be detected into the preset color space includes:
carrying out distortion-free conversion on a plurality of curve images to be detected, and respectively storing the plurality of curve images to be detected after the distortion-free conversion into a preset picture format; and respectively converting the plurality of curve images to be detected stored in the preset picture format into preset color spaces.
It is understood that after obtaining the preset picture with the general format, the determined color space parameter values of the curve image to be detected contained in the picture can be obtained.
In this embodiment, the preset color space includes an HSV color space.
It is understood that color spaces include, but are not limited to: preferably, the preset color space in this embodiment is HSV color space, according to the characteristics of the picture content in this embodiment and the characteristics that HSV color space is more intuitive visually than other color spaces.
In this embodiment, before step S110, the method further includes: and setting different colors for the curve image to be detected containing the curve area to be detected and the curve area not to be detected.
It can be understood that by setting the color of the curve image to be detected in each picture to be different from the colors of the other images except the curve image to be detected in the picture, the color space parameter value of the curve image to be detected in the picture can be clearly distinguished from the color space parameter values of the other images except the curve image to be detected in the picture after the picture is converted into the preset color space; it should be noted that, in the method for detecting consistency of curves in this embodiment, consistency detection is performed on one target curve included in each of a plurality of pictures, and therefore, if more than one curve image is included in the picture, in order to extract the target curve, it is necessary to mask other curve images in the picture. It can be understood that, in this embodiment, an HSV color space is adopted, and by setting a parameter value of a hue of a picture in the HSV color space, a color of an image in the picture can be adjusted, where red is 0, green is 60, and blue is 120, and by adjusting the color of the image in the picture, a content of the picture including a curve image to be detected can be distinguished into the curve image to be detected and other images.
Step S120: and extracting the pixel coordinate information of the curve in each curve image to be detected according to the color space parameter value of each curve image to be detected.
In this embodiment, the step S120 includes: removing the image content except the curve area not containing the curve to be detected in the curve image to be detected according to the color space parameter value of each curve image to be detected so as to extract the mask of the curve in each curve image to be detected, and obtaining the pixel coordinate information of the curve in the curve image to be detected according to the mask of the curve in the curve image to be detected.
It can be understood that the adjustable parameters of the HSV color space adopted in this embodiment include, in addition to the hue parameter, a saturation parameter and a brightness parameter, and after setting the hue parameter to set the color of the curve image to be detected in each picture to be a color different from the colors of the other images in the picture except the curve image to be detected, the saturation parameter and the brightness parameter may be set, and the hue parameter may be subjected to fine adjustment to extract a mask of the curve image to be detected included in each picture, where the mask of the curve image to be detected is used to block the other images in the picture to extract information of the curve image to be detected.
In this embodiment, the step of obtaining the pixel coordinate information of the curve in the to-be-detected curve image according to the mask of the curve in the to-be-detected curve image includes: and summarizing the pixel coordinates of the highest point of each column in the mask of the curve in the image of the curve to be detected to obtain the pixel coordinate information of the curve in the image of the curve to be detected.
It can be understood that, since the picture in the preset format described in the present embodiment is composed of a plurality of pixel points, therefore, in the pixel coordinate information of the curve image to be detected extracted through the mask, each pixel abscissa corresponds to a pixel ordinate composed of a plurality of pixel points, in order to ensure the accuracy of the consistency detection of the subsequent curve, a unique pixel point needs to be selected from the pixel ordinate composed of the plurality of pixel points, and the ordinate of the pixel point is taken as the pixel ordinate corresponding to the pixel abscissa, in this embodiment, the ordinate of the pixel point at the highest point in each row in the mask of the to-be-detected curve image is taken as the pixel ordinate corresponding to the abscissa of the pixel point, and it should be noted that, in the pixel coordinate information of the to-be-detected curve image extracted from the mask of the to-be-detected curve image, the ordinate of the pixel point at the lowest point in each row may also be taken as the pixel ordinate corresponding to the abscissa of the pixel point.
Step S130: and drawing the curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected.
It can be understood that the pixel coordinate information of each curve image to be detected includes the pixel abscissa and the pixel ordinate of the pixel point in the curve to be detected, so that the curve to be detected corresponding to the curve image to be detected included in each picture can be drawn in the pixel coordinate system according to the pixel abscissa and the pixel ordinate of all the pixel points in the curve to be detected.
Step S140: and carrying out consistency detection on a plurality of groups of curves to be detected drawn in the pixel coordinate system to obtain a detection result.
It is understood that, in the present embodiment, the plurality of sets of curves to be detected refers to a plurality of curves to be detected.
Referring to fig. 2, in the present embodiment, the step S140 includes steps S141 to S142.
Step S141: and performing difference calculation on the vertical coordinates of all the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected to obtain the vertical coordinate difference value between the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected.
It should be noted that, in this embodiment, performing difference calculation on the ordinate of all the pixel points with the same abscissa in the multiple groups of curves to be detected means: and performing difference calculation on the vertical coordinates of all the pixel points with the same horizontal coordinates in any two curves to be detected in the multiple groups of curves to be detected.
Step S142: and drawing a difference value curve according to the longitudinal coordinate difference value.
It can be understood that a plurality of groups of curves to be detected in a pixel coordinate system have the same abscissa, and the differences of the plurality of groups of curves to be detected are mainly reflected in that the ordinates corresponding to the same abscissa are different, so that the difference of the ordinate of each pixel having the same abscissa in the plurality of groups of curves to be detected can be obtained by performing difference calculation on the ordinate of all pixels having the same abscissa in the plurality of groups of curves to be detected, the difference of the ordinate of each pixel of the plurality of groups of curves to be detected is taken as the ordinate of a difference curve, the abscissa of each pixel of the plurality of groups of curves to be detected is taken as the abscissa of the difference curve, and the difference curve corresponding to the plurality of groups of curves to be detected can be drawn.
Step S143: and determining whether the multiple groups of curves to be detected are consistent or not according to the ordinate of the difference curve.
When all the vertical coordinates of the difference value curves are zero, the multiple curves to be detected are consistent; and when the vertical coordinates of the difference curves are not all zero, the multiple curves to be detected are inconsistent.
It can be understood that when all the vertical coordinates of the difference curve are zero, the vertical coordinates of each pixel point of the multiple curves to be detected with the same horizontal coordinate are also the same, that is, the multiple curves to be detected are completely consistent; when the ordinate of the difference curve is not all zero, the ordinate of the pixel points of the multiple curves to be detected with the same abscissa is not identical, and the ordinate is different, that is, the multiple curves to be detected are not identical.
In this embodiment, after step S140, the method further includes the steps of: and establishing a mapping relation between a pixel coordinate system and a rectangular coordinate system, converting the difference curve in the pixel coordinate system into the rectangular coordinate system according to the mapping relation to obtain a target difference curve, and quantitatively judging the difference of the to-be-detected curves according to the target difference curve.
It is understood that whether the curve to be detected is consistent or not can be detected in the pixel coordinate system, however, the units of the abscissa and the ordinate of the pixel coordinate system are pixels, which is different from the units of the abscissa and the ordinate of the curve to be detected in the rectangular coordinate system before the conversion to the pixel coordinate system, wherein the units of the abscissa of the curve to be detected in the rectangular coordinate system include, but are not limited to: hertz, time, speed and temperature, the ordinate unit of the curve to be detected in the rectangular coordinate system includes but is not limited to: decibel, volt, watt and joule, after detecting that the multiple curves to be detected are inconsistent, in order to quantitatively know the difference of the multiple curves to be detected, the difference curve in the pixel coordinate system needs to be converted into a rectangular coordinate system according to a preset mapping relation to obtain a target difference curve, and the target difference curve is analyzed to quantitatively judge the difference of the curves to be detected.
Specifically, referring to fig. 3, the steps include step S151 to step S155.
Step S151: and taking the difference value between the starting value of the abscissa and the ending value of the abscissa in the rectangular coordinate system as a rectangular abscissa difference value, and taking the difference value between the starting value of the abscissa and the ending value of the abscissa in the pixel coordinate system as a pixel abscissa difference value.
It is understood that the starting value of the abscissa in the coordinate system is usually set to zero, and the ending value of the abscissa in the coordinate system can be set to a target value according to the requirement, however, on the axis of abscissa, the starting value of the difference curve may not be zero, and the ending value of the difference curve may not reach the target value, so the starting value of the abscissa and the ending value of the abscissa in the rectangular coordinate system refer to: on an abscissa axis in the rectangular coordinate system, the starting value of the difference curve and the ending value of the difference curve correspond to each other, and the starting value of the abscissa and the ending value of the abscissa in the pixel coordinate system refer to: on an abscissa axis in the pixel coordinate system, a starting value of the difference curve and an ending value of the difference curve.
Step S152: and taking the ratio of the abscissa of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel abscissa as the ratio of the abscissa of the difference curve in the rectangular coordinate system to the difference value of the rectangular coordinate system, thereby calculating the abscissa of the target point in the rectangular coordinate system corresponding to the abscissa of each pixel point in the pixel coordinate system of the difference curve.
Specifically, the ratio of the abscissa of the target point of the difference curve in the pixel coordinate system in step S152 to the difference value of the abscissa of the pixel is taken as the ratio of the abscissa of the pixel; taking the ratio of the abscissa of the target point of the difference curve in the rectangular coordinate system in the step S152 to the rectangular abscissa difference as a rectangular abscissa ratio; the abscissa of the target point of the difference curve in the rectangular coordinate system is an unknown parameter, and the abscissa, the pixel abscissa difference value and the rectangular abscissa difference value of the target point of the difference curve in the pixel coordinate system are known parameters; by adopting a mapping relation that the pixel abscissa ratio is equal to the rectangular abscissa ratio, the abscissa of the target point in the difference curve in the rectangular coordinate system can be calculated; and calculating to obtain the abscissa of each pixel point in the difference curve in the pixel coordinate system in the rectangular coordinate system corresponding to the abscissa.
Step S153: and taking the difference value between the initial value of the ordinate and the end value of the ordinate in the rectangular coordinate system as a rectangular ordinate difference value, and taking the difference value between the initial value of the ordinate and the end value of the ordinate in the pixel coordinate system as a pixel ordinate difference value.
It is understood that the starting value of the ordinate and the ending value of the ordinate in the rectangular coordinate system refer to: on the ordinate axis in the rectangular coordinate system, the starting value of the difference curve and the ending value of the difference curve correspond to each other, and the starting value of the ordinate and the ending value of the ordinate in the pixel coordinate system refer to: on the ordinate axis in the pixel coordinate system, a starting value of the difference curve and an ending value of the difference curve.
Step S154: and taking the ratio of the ordinate of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel ordinate as the ratio of the ordinate of the target point in the rectangular coordinate system to the difference value of the rectangular ordinate, thereby calculating the ordinate of each pixel point in the pixel coordinates of the difference curve corresponding to the ordinate of the target point in the rectangular coordinate system.
It can be understood that the vertical coordinate of the target pixel point of the difference curve in the pixel coordinate system is obtained by performing difference calculation on the multiple curves to be detected, and therefore, the vertical coordinate of the target pixel point may be zero, may be greater than zero, and may also be less than zero; when the vertical coordinate of the target pixel point is zero, directly assigning the vertical coordinate of the target point in the rectangular coordinate system to be zero; when the ordinate of the target pixel point is not zero, taking the ratio of the ordinate of the target point of the difference curve in the pixel coordinate system to the difference value of the pixel ordinate as the ratio of the pixel ordinate; taking the ratio of the ordinate of the target point of the difference curve in the rectangular coordinate system to the difference value of the rectangular ordinate as the ratio of the rectangular ordinate, wherein the ordinate of the target point of the difference curve in the rectangular coordinate system is an unknown parameter, and the ordinate of the target point of the difference curve in the pixel coordinate system, the difference value of the pixel ordinate and the difference value of the rectangular ordinate are known parameters; by adopting a mapping relation that the pixel ordinate ratio is equal to the rectangular ordinate ratio, the ordinate of the target point of the difference curve in the rectangular coordinate system can be calculated; and calculating to obtain the vertical coordinate in the rectangular coordinate system corresponding to the vertical coordinate of each pixel point of the difference curve in the pixel coordinate system.
Step S155: and drawing in the rectangular coordinate system according to the abscissa and the ordinate of each pixel point in the difference curve in the rectangular coordinate system to obtain a target difference curve.
It can be understood that, in any coordinate system, according to the determined abscissa and ordinate, a graph corresponding to the abscissa and the ordinate can be drawn, and in this embodiment, according to the abscissa and the ordinate, a target difference curve corresponding to the abscissa and the ordinate can be drawn in a rectangular coordinate system. And quantitatively acquiring the difference of the multiple curves to be detected in a preset unit according to the target difference curve.
Embodiments of the present invention further provide a storage medium storing a computer program, which can be executed by one or more processors, and can be used to implement the curve consistency detection method.
In summary, the curve consistency detection method and the storage medium according to the present invention convert a plurality of curve images to be detected into a preset color space to obtain a color space parameter value of each curve image to be detected; extracting pixel coordinate information of a curve in each to-be-detected curve image according to the color space parameter value of each to-be-detected curve image; drawing a curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected; the consistency detection is carried out on a plurality of groups of curves to be detected drawn in the pixel coordinate system to obtain a detection result, and the problems that in the prior art, the consistency of similar experiment curves in a plurality of experiment curve pictures is directly detected with high difficulty and the detection result is easy to make mistakes can be solved. Further, the difference curve in the pixel coordinate system is converted into a rectangular coordinate system according to the mapping relation to obtain a target difference curve, the target difference curve is analyzed, the difference of the curve to be detected can be obtained quantitatively, a researcher can be helped to finely adjust the parameters for generating the curve to be detected, and an expected experiment effect is achieved.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for detecting consistency of curves is characterized in that,
converting the plurality of curve images to be detected into a preset color space to obtain a color space parameter value of each curve image to be detected;
extracting pixel coordinate information of a curve in each to-be-detected curve image according to the color space parameter value of each to-be-detected curve image;
drawing a curve to be detected corresponding to the curve in each curve image to be detected in a pixel coordinate system according to the pixel coordinate information of the curve in each curve image to be detected;
and carrying out consistency detection on a plurality of groups of curves to be detected drawn in the pixel coordinate system to obtain a detection result.
2. The curve consistency detection method according to claim 1, wherein the step of converting the plurality of curve images to be detected into a preset color space comprises:
carrying out distortion-free conversion on a plurality of curve images to be detected, and respectively storing the plurality of curve images to be detected after the distortion-free conversion into a preset picture format;
and respectively converting the plurality of curve images to be detected stored in the preset picture format into preset color spaces.
3. The curve consistency detection method according to claim 1, wherein the step of extracting the pixel coordinate information of the curve in each curve image to be detected according to the color space parameter value of each curve image to be detected comprises:
removing image content which does not include a curve area to be detected in the curve image to be detected according to the color space parameter value of each curve image to be detected so as to extract a mask of a curve in each curve image to be detected, and obtaining pixel coordinate information of the curve in the curve image to be detected according to the mask of the curve in the curve image to be detected.
4. The curve consistency detection method according to claim 3, wherein the step of obtaining the pixel coordinate information of the curve in the curve image to be detected according to the mask of the curve in the curve image to be detected comprises:
and summarizing the pixel coordinates of the highest point of each column in the mask of the curve in the image of the curve to be detected to obtain the pixel coordinate information of the curve in the image of the curve to be detected.
5. The curve consistency detection method according to claim 1, wherein the step of performing consistency detection on a plurality of groups of curves to be detected obtained by plotting in a pixel coordinate system to obtain a detection result comprises:
performing difference calculation on the vertical coordinates of all the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected to obtain the vertical coordinate difference value between the pixel points with the same horizontal coordinate in the multiple groups of curves to be detected;
drawing a difference value curve according to the longitudinal coordinate difference value;
determining whether a plurality of groups of curves to be detected are consistent or not according to the vertical coordinates of the difference curves, wherein when all the vertical coordinates of the difference curves are zero, a plurality of the curves to be detected are consistent; and when the vertical coordinates of the difference curves are not all zero, the multiple curves to be detected are inconsistent.
6. The curve consistency detection method according to claim 5, wherein after the step of performing consistency detection on a plurality of groups of curves to be detected to obtain detection results, the method further comprises:
and establishing a mapping relation between a pixel coordinate system and a rectangular coordinate system, converting the difference curve in the pixel coordinate system into the rectangular coordinate system according to the mapping relation to obtain a target difference curve, and quantitatively judging the difference of the to-be-detected curves according to the target difference curve.
7. The method according to claim 6, wherein the step of transforming the difference curve in the pixel coordinate system into a rectangular coordinate system according to the mapping relationship to obtain the target difference curve comprises:
taking a difference value between a starting value of an abscissa and an ending value of the abscissa in the rectangular coordinate system as a rectangular abscissa difference value, and taking a difference value between the starting value of the abscissa and the ending value of the abscissa in the pixel coordinate system as a pixel abscissa difference value;
taking the ratio of the abscissa of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel abscissa as the ratio of the abscissa of the difference curve in the rectangular coordinate system to the difference value of the rectangular coordinate system, and thus calculating the abscissa of the target point in the rectangular coordinate system corresponding to the abscissa of each pixel point in the pixel coordinate system of the difference curve;
taking a difference value between a starting value of a vertical coordinate and an ending value of the vertical coordinate in the rectangular coordinate system as a rectangular vertical coordinate difference value, and taking a difference value between the starting value of the vertical coordinate and the ending value of the vertical coordinate in the pixel coordinate system as a pixel vertical coordinate difference value;
taking the ratio of the ordinate of the target pixel point in the difference curve in the pixel coordinate system to the difference value of the pixel ordinate as the ratio of the ordinate of the target point in the rectangular coordinate system to the difference value of the rectangular ordinate, thereby calculating the ordinate of each pixel point in the pixel coordinates of the difference curve corresponding to the ordinate of the target point in the rectangular coordinate system;
and drawing in the rectangular coordinate system according to the abscissa and the ordinate of each pixel point in the difference curve in the rectangular coordinate system to obtain a target difference curve.
8. The curve consistency detection method according to claim 1, wherein before the step of converting the plurality of curve images to be detected into the preset color space, the method further comprises:
and setting different colors for the curve image to be detected containing the curve area to be detected and the curve area not to be detected.
9. The method according to claim 1, wherein the predetermined color space comprises an HSV color space.
10. A storage medium storing a computer program executable by one or more processors for implementing the curve conformity detection method as claimed in any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910951457.3A CN110660096B (en) | 2019-10-08 | 2019-10-08 | Curve consistency detection method and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910951457.3A CN110660096B (en) | 2019-10-08 | 2019-10-08 | Curve consistency detection method and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110660096A true CN110660096A (en) | 2020-01-07 |
| CN110660096B CN110660096B (en) | 2023-05-23 |
Family
ID=69038643
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910951457.3A Active CN110660096B (en) | 2019-10-08 | 2019-10-08 | Curve consistency detection method and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110660096B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049598A (en) * | 2012-11-29 | 2013-04-17 | 北京航空航天大学 | Electromagnetic compatibility test curve picture information extraction method based on pixel coordinate strategy |
| CN104697476A (en) * | 2015-03-19 | 2015-06-10 | 北京时代之峰科技有限公司 | Automatic detection method and device for roughness light-incision profile curve |
| CN108052950A (en) * | 2017-12-08 | 2018-05-18 | 东北大学 | A kind of segmentation of electric melting magnesium furnace dynamic flame and feature extracting method based on MIA |
| CN109030391A (en) * | 2018-08-09 | 2018-12-18 | 深圳市中金岭南有色金属股份有限公司 | The measuring method of dissoluble lead, soluble Zn in Lead and Zinc bulk concentrates |
| CN109458980A (en) * | 2018-11-06 | 2019-03-12 | 五邑大学 | A kind of Downtilt measurement method based on linear regression fit |
| CN110263390A (en) * | 2019-05-24 | 2019-09-20 | 五邑大学 | Downtilt automatic adjusting method and system based on unmanned plane vision measurement |
-
2019
- 2019-10-08 CN CN201910951457.3A patent/CN110660096B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049598A (en) * | 2012-11-29 | 2013-04-17 | 北京航空航天大学 | Electromagnetic compatibility test curve picture information extraction method based on pixel coordinate strategy |
| CN104697476A (en) * | 2015-03-19 | 2015-06-10 | 北京时代之峰科技有限公司 | Automatic detection method and device for roughness light-incision profile curve |
| CN108052950A (en) * | 2017-12-08 | 2018-05-18 | 东北大学 | A kind of segmentation of electric melting magnesium furnace dynamic flame and feature extracting method based on MIA |
| CN109030391A (en) * | 2018-08-09 | 2018-12-18 | 深圳市中金岭南有色金属股份有限公司 | The measuring method of dissoluble lead, soluble Zn in Lead and Zinc bulk concentrates |
| CN109458980A (en) * | 2018-11-06 | 2019-03-12 | 五邑大学 | A kind of Downtilt measurement method based on linear regression fit |
| CN110263390A (en) * | 2019-05-24 | 2019-09-20 | 五邑大学 | Downtilt automatic adjusting method and system based on unmanned plane vision measurement |
Non-Patent Citations (3)
| Title |
|---|
| 中国测绘学会: "《中国测绘学科发展蓝皮书》", 31 December 2018, 测绘出版社, pages: 246 - 248 * |
| 刘洁锋等著: "《大洋非线性编辑实用教程 高级篇》", 31 October 2016, 中国传媒大学出版社, pages: 95 - 105 * |
| 托马斯•林德布拉德等: "《图像处理与脉冲耦合神经网络 基于Python的实现 第3版》", 31 January 2017, 国防工业出版社, pages: 123 - 128 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110660096B (en) | 2023-05-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111028213B (en) | Image defect detection method, device, electronic equipment and storage medium | |
| TWI557687B (en) | Processing apparatus and method of binary image | |
| JP2012199901A (en) | Document modification detecting method by character comparison using character shape feature | |
| CN110569774B (en) | Automatic line graph image digitalization method based on image processing and pattern recognition | |
| JP2021189527A5 (en) | ||
| CN110660096B (en) | Curve consistency detection method and storage medium | |
| JP4441300B2 (en) | Image processing apparatus, image processing method, image processing program, and recording medium storing the program | |
| CN115330803B (en) | Surface defect data enhancement method and device, electronic equipment and storage medium | |
| KR102438076B1 (en) | Method and apparatus for detecting parking area | |
| CN109884703B (en) | Color plane attribute graph digitalization method based on HSV color model | |
| CN112152632B (en) | Method and system for compressing infrared image gray data | |
| JPH0744709A (en) | Color discrimination device | |
| JP2013045205A (en) | Image processor, image processing method and image processing program | |
| CN108133210B (en) | Image format identification method and device | |
| CN113095147A (en) | Skin area detection method, system, image processing terminal and storage medium | |
| CN114202665A (en) | Image similarity determining method and device, equipment and storage medium | |
| JP7106318B2 (en) | Image processing device, image processing method and program | |
| CN114119427B (en) | Picture conversion method, device, equipment and readable storage medium | |
| KR20120128539A (en) | Methdo and apparatus for photorealistic enhancing of computer graphic image | |
| US20240169616A1 (en) | Information processing device, information processing method, and non-transitory computer-readable storage medium | |
| JP6198918B1 (en) | Particle number measuring apparatus, particle number measuring method, program, and storage medium | |
| US20220101041A1 (en) | Information processing device, information processing method, and recording medium recorded with information processing program | |
| JP5053979B2 (en) | Image processing program, image processing apparatus, and image processing method | |
| JP2005130000A (en) | Image processing apparatus | |
| CN115880235A (en) | Surface defect data synthesis and evaluation method, electronic device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |