CN111147763A - Image processing method based on gray value and application - Google Patents
Image processing method based on gray value and application Download PDFInfo
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- CN111147763A CN111147763A CN201911386301.1A CN201911386301A CN111147763A CN 111147763 A CN111147763 A CN 111147763A CN 201911386301 A CN201911386301 A CN 201911386301A CN 111147763 A CN111147763 A CN 111147763A
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Abstract
The invention discloses an image processing method based on gray values and application, and relates to the technical field of image processing. The method comprises the following steps: acquiring image pixel information in a fixed area aiming at each frame of image; acquiring a line threshold G [ i ] of each line, adding all the line thresholds G [ i ] of each frame image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame image, and adjusting the gray value of a pixel point to be a preset white brightness constant or a preset black brightness constant according to the regional gray standard value G; and comparing the adjusted image frame with the adjusted next image frame, and judging that a moving object appears in the fixed area when the constant from the white brightness constant to the black brightness constant or the jitter from the black brightness constant to the white brightness constant appears. The invention can improve the identification accuracy of the moving object in the fixed area and reduce the probability of misjudgment.
Description
Technical Field
The invention relates to the technical field of image processing.
Background
The detection of a moving object by a CMOS camera in a fixed area is a general requirement, and the basic idea of detecting the moving object in the fixed area at present is as follows: and judging the moving object according to the change of the gray value in the area. For example, an OV6620 CMOS camera outputs a field of pictures in a progressive scanning manner every 20ms, each field of pictures having a field interrupt signal. Each pixel point corresponds to a gray value (0-255), the larger the gray value is, the brighter (white) the pixel point is, and the smaller the gray value is, the darker (black) the pixel point is. Moving objects can be detected based on changes in the gray level values within the region.
However, the above scheme has the following defects: in some scenes with varying ambient light, misjudgment is likely to occur, especially, for example, in a very dark environment, a black object is passed through the fixed area, and in a very bright environment, a white object is passed through the fixed area. In the two detection scenarios, the variation range of the gray value is often very small, and erroneous judgment is easy to occur during processing.
How to improve the effective discrimination rate of the moving object in the fixed area to reduce the probability of misjudgment is an urgent technical problem to be solved at present.
Disclosure of Invention
The invention aims to: the invention overcomes the defects of the prior art and provides an image processing method based on gray values and application thereof.
In order to achieve the above object, the present invention provides the following technical solutions:
an image processing method based on gray-scale values, comprising the steps of:
acquiring image pixel information in a fixed area aiming at each frame of image;
for the fixed area, obtaining a maximum value max [ i ] and a minimum value min [ i ] of the gray value of each row of pixel points, and carrying out arithmetic averaging to obtain a row threshold value g [ i ] of each row, wherein i represents the current calculation row number, i is 1, 2,.
Adding all line thresholds G [ i ] of each frame of image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame of image, and comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame of image; when the gray value of the pixel point is larger than or equal to G, the pixel point is judged to be a white point, and the gray value of the pixel point is adjusted to be a preset white brightness constant; when the gray value of a pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image;
and comparing the adjusted image frame with the next image frame after adjustment, and judging that a moving object appears in the fixed area when the constant from the white brightness constant to the black brightness constant or the jitter from the black brightness constant to the white brightness constant appears.
Further, the white luminance constant is set to 255, and the black luminance constant is set to 0.
Furthermore, for each frame of image, the method for collecting the image pixel information in the fixed area is,
acquiring the number n of rows and the number m of columns contained in a first frame of image based on a fixed area;
starting from a first pixel point of a first row of the region, acquiring information of each pixel point of the first row and sequentially storing the information into pic [1] [ j ], wherein j represents the number of columns, and j is 1, 2. And so on, acquiring the information of each pixel point in the ith row and sequentially storing the information into pic [ i ] [ j ];
for other image frames, the above steps are repeated to store image pixel information pic [ i ] [ j ] for each image frame.
And further, when the moving object is judged to appear, judging the moving direction of the moving object according to the jumping direction of the pixel points with the jumping gray value.
Further, when the moving object is judged to appear, the size of the moving object is judged according to the region range of the pixel points with the jittering gray value.
The invention also provides an image processing device based on the gray value, which comprises the following structures:
the information acquisition module is used for acquiring image pixel information in the fixed area aiming at each frame of image;
the information analysis module is used for obtaining a maximum value max [ i ] and a minimum value min [ i ] of the gray value of each row of pixel points for the fixed area, and performing arithmetic averaging to obtain a row threshold value g [ i ] of each row, wherein i represents the current calculation row number, i is 1, 2, and n represents the total row number; adding all line thresholds G [ i ] of each frame of image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame of image, and comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame of image;
the image adjusting module is used for judging the pixel point as a white point when the gray value of the pixel point is greater than or equal to G, and adjusting the gray value of the pixel point as a preset white brightness constant; when the gray value of a pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image;
and the judging module is used for comparing the adjusted image frame with the next adjusted image frame and judging that a moving object appears in the fixed area when the constant from the white brightness constant to the black brightness constant or the jitter from the black brightness constant to the white brightness constant appears.
And further, the system also comprises a parameter setting module for setting the white brightness constant and the black brightness constant by a user.
Further, the determination module comprises a moving direction determination submodule for determining the moving direction of the moving object according to the jumping direction of the pixel point with the jumping gray value when the moving object is determined to appear.
Further, the determination module further comprises an object size determination submodule, and the object size determination submodule is used for determining the size of the moving object according to the area range of the pixel points with the bouncing gray value when the moving object is determined to appear.
In another embodiment of the present invention, a method for detecting a moving object in a fixed area is also provided, which uses the foregoing method to detect a moving object.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects as examples: the invention improves the identification accuracy of the moving object in the fixed area and reduces the probability of misjudgment.
Drawings
Fig. 1 is a flowchart of a gray-scale value-based image processing method according to an embodiment of the present invention.
Fig. 2 is a block diagram of an image processing apparatus based on gray-scale values according to an embodiment of the present invention.
Description of reference numerals:
the system comprises an information acquisition module 210, an information analysis module 220, an image adjustment module 230, a judgment module 240, a parameter setting module 250, a moving direction judgment submodule 241 and an object size judgment submodule 242.
Detailed Description
The gray-level value-based image processing method disclosed by the invention and the application thereof are further described in detail in the following with reference to the accompanying drawings and specific embodiments. It should be noted that technical features or combinations of technical features described in the following embodiments should not be considered as being isolated, and they may be combined with each other to achieve better technical effects. In the drawings of the embodiments described below, the same reference numerals appearing in the respective drawings denote the same features or components, and may be applied to different embodiments. Thus, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.
It should be noted that the structures, proportions, sizes, and other dimensions shown in the drawings and described in the specification are only for the purpose of understanding and reading the present disclosure, and are not intended to limit the scope of the invention, which is defined by the claims, and any modifications of the structures, changes in the proportions and adjustments of the sizes and other dimensions, should be construed as falling within the scope of the invention unless the function and objectives of the invention are affected. The scope of the preferred embodiments of the present invention includes additional implementations in which functions may be executed out of order from that described or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present invention.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
Examples
Referring to fig. 1, a gray-value-based image processing method includes the steps of:
and S100, acquiring image pixel information in a fixed area for each frame of image.
Taking 0V6620 CMOS camera as an example, the camera outputs one frame image (or called a field image) in a progressive scanning manner every 20ms, and each frame image has an interrupt signal (called a field interrupt signal). Each pixel point in each frame of image corresponds to a gray value (0-255), the larger the gray value is, the brighter the pixel point is (white), and the smaller the gray value is, the darker the pixel point is (black).
For each image frame, image pixel information within a fixed region is acquired. When the method is implemented, the method can comprise the following steps,
for a first frame of image, acquiring the number of rows n and the number of columns m contained in a fixed area based on the area. The number of rows for any row is denoted by i, i 1, 2. The number of columns for any column is denoted by j, j 1, 2.
Starting from a first pixel point of a first row (i ═ 1) in the region, acquiring information of each pixel point of the first row and sequentially storing the information into pic [1] [ j ], wherein j represents the number of columns, and j ═ 1, 2.... times, m; and so on, acquiring the information of each pixel point in the ith row and sequentially storing the information into pic [ i ] [ j ].
For other image frames, the above steps are repeated to store image pixel information pic [ i ] [ j ] for each image frame.
By way of example and not limitation, for example, the whole frame of each image is taken as a fixed area, each image includes 300 rows and 900 columns, and the image can be represented as pic [ i ] [ j ] (1 < i < 300) (1 < j < 900) by an array, so that the frame of image has 900 to 270000 pixels.
The frame of the fixed area is formed by 900 dots (pic [1] [ j ]) in the first line, 900 dots (pic [300] [ j ]) in the last line, the first dot (pic [ i ] [1]) in each line, and the last dot (pic [ i ] [900]) in each line.
S200, for the fixed area, obtaining the maximum value max [ i ] and the minimum value min [ i ] of the gray value of each row of pixel points, and carrying out arithmetic averaging to obtain the row threshold g [ i ] of each row. I denotes the current number of lines to be calculated, i 1, 2.
By way of example and not limitation, for example, in row 1, the maximum value max [1] of all pic [1] [ j ] is 170, and the minimum value min is 100, and then the row threshold value g [1] of row 1 calculated based on arithmetic mean is (170+100)/2 is 135.
And in the same way, the values of g [2], g [3], g [4], are obtained in sequence.
S300, adding all the line threshold values G [ i ] of each frame of image, and dividing the sum by the total line number n to obtain the area gray level standard value G of the fixed area in the frame of image. Comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame image; when the gray value of the pixel point is larger than or equal to G, the pixel point is judged to be a white point, and the gray value of the pixel point is adjusted to be a preset white brightness constant; when the gray value of the pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image.
The area gray scale standard value G ═ G [1] + G [2] + G [3] + -. + G [ n ])/n of the fixed area of each frame image. By way of example and not limitation, the area gray scale standard value G of the first frame image, such as obtained by the above formula, is 120.
And carrying out gray adjustment on the current image frame according to the area gray standard value G. Specifically, the gray value of each pixel point is compared with the gray standard value G of the region from the first pixel point of the frame image.
When the gray value of the pixel point is larger than or equal to 120, the pixel point is judged to be a white point, and the gray value of the pixel point is adjusted to be a preset white brightness constant.
When the gray value of the pixel point is less than 120, the pixel point is judged to be a black point, and the gray value of the pixel point is adjusted to be a preset black brightness constant.
And completing the adjustment of the last pixel point of the frame image. After adjustment, only two gray values of a white brightness constant and a black brightness constant exist in the frame image.
The white and black luminance constants are used to make black darker and white whiter to enhance contrast. Therefore, when setting the white luminance constant, in particular, a value with a larger luminance (whiter) should be selected, and a value with a smaller luminance (blacker) should be selected for the black luminance constant.
The values of the white brightness constant and the black brightness constant can be default by the system or can be set by the user. In this embodiment, it is preferable that the white luminance constant is set to 255 and the black luminance constant is set to 0.
S400, comparing the adjusted image frame with the next image frame after adjustment, and judging that a moving object appears in the fixed area when the constant from white brightness to black brightness or the constant from black brightness to white brightness jumps.
Taking the white brightness constant as 255 and the black brightness constant as 0 as an example, the gray value of the adjusted current image frame is only 255 or 0, and no matter what moving object comes, no matter what moving object appears in the position of the same pixel point of the current image frame and the next image frame, when the jump of 255 to 0 or 0 to 255 occurs, the moving object can be judged to pass through.
The gray value of the pixel point in the fixed frame is unchanged under the normal condition, when a moving object passes through the fixed area, the gray value of the processed pixel point in the fixed area can be changed violently, and then the gray value is restored to the normal level. The pixel point change of the moving object is regular, and the pixel points of the previous field image, the current field image and the next field image are reflected in the condition that pic [ i + x ] [ j + x ] is the same as pic [ i ] [ j ].
In another embodiment of this embodiment, when it is determined that a moving object is present, the moving direction of the moving object may be determined according to the bouncing direction of the pixel point where the gray value bounces.
By way of example and not limitation, the following 5-field image frames may be acquired from the current image frame, and the moving direction of the moving object may be determined by comparing the jumping directions from the white point to the black point in the 6-field image frame.
And when the moving object is judged to appear, judging the size of the moving object according to the region range of the pixel points with the jittering gray value.
By way of example and not limitation, comparing the current image frame with the next image frame, the region range related to the pixel jumping is: column extents pic [100] [110] -pic [100] [119], row extents pic [100] [ j ] -pic [125] [ j ], and the moving object involves pixels of size 9 × 25 by width.
Referring to fig. 2, an image processing apparatus based on gray-scale values is provided as another embodiment of the present invention.
The device comprises the following structure:
the information acquisition module 210 is configured to acquire image pixel information in a fixed area for each frame of image;
the information analysis module 220 is configured to, for the fixed region, obtain a maximum value max [ i ] and a minimum value min [ i ] of the gray values of the pixel points in each row, and perform arithmetic averaging to obtain a row threshold g [ i ] of each row, where i represents a current calculated row number, i is 1, 2,.. and n represents a total row number; adding all line thresholds G [ i ] of each frame of image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame of image, and comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame of image;
the image adjusting module 230 is configured to determine that the pixel point is a white point when the gray value of the pixel point is greater than or equal to G, and adjust the gray value of the pixel point to be a preset white brightness constant; when the gray value of a pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image;
the determining module 240 is configured to compare the adjusted image frame with the adjusted next image frame, and determine that a moving object occurs in the fixed area when a transition from the white luminance constant to the black luminance constant or a transition from the black luminance constant to the white luminance constant occurs.
The area gray scale standard value G ═ G [1] + G [2] + G [3] + -. + G [ n ])/n of the fixed area of each frame image. By way of example and not limitation, the area gray scale standard value G of the first frame image, such as obtained by the above formula, is 120.
And carrying out gray adjustment on the current image frame according to the area gray standard value G. Specifically, the gray value of each pixel point is compared with the gray standard value G of the region from the first pixel point of the frame image.
When the gray value of the pixel point is larger than or equal to 120, the pixel point is judged to be a white point, and the gray value of the pixel point is adjusted to be a preset white brightness constant.
When the gray value of the pixel point is less than 120, the pixel point is judged to be a black point, and the gray value of the pixel point is adjusted to be a preset black brightness constant.
And completing the adjustment of the last pixel point of the frame image. After adjustment, only two gray values of a white brightness constant and a black brightness constant exist in the frame image.
The white and black luminance constants are used to make black darker and white whiter to enhance contrast. Therefore, when setting the white luminance constant, in particular, a value with a larger luminance (whiter) should be selected, and a value with a smaller luminance (blacker) should be selected for the black luminance constant.
The values of the white brightness constant and the black brightness constant can be default by the system or can be set by the user. In this embodiment, it is preferable that the white luminance constant is set to 255 and the black luminance constant is set to 0.
In this embodiment, a parameter setting module 250 is included for the user to set the white brightness constant and the black brightness constant.
With continued reference to fig. 2, the determination module 240 may further include a movement direction determination submodule 241 and/or an object size determination submodule 242.
The moving direction determination submodule 24 is configured to determine a moving direction of the moving object according to a jumping direction of the pixel where the gray value jumps.
The object size determination submodule 242 is configured to determine the size of the moving object according to the area range of the pixel point where the gray value is jittered.
Other technical features are referred to the foregoing embodiments and will not be described herein.
In another embodiment of the present invention, a method for detecting a moving object in a fixed area is also provided, which uses the foregoing method to detect a moving object.
By the method, the pixel points in the fixed area have more obvious contrast, namely white and black, so that the identification accuracy of the moving object in the fixed area is improved, and the probability of misjudgment is reduced.
Other technical features are referred to the foregoing embodiments and will not be described herein.
In the foregoing description, the disclosure of the present invention is not intended to limit itself to these aspects. Rather, the various components may be selectively and operatively combined in any number within the intended scope of the present disclosure. In addition, terms like "comprising," "including," and "having" should be interpreted as inclusive or open-ended, rather than exclusive or closed-ended, by default, unless explicitly defined to the contrary. All technical, scientific, or other terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. Common terms found in dictionaries should not be interpreted too ideally or too realistically in the context of related art documents unless the present disclosure expressly limits them to that. Any changes and modifications of the present invention based on the above disclosure will be within the scope of the appended claims.
Claims (10)
1. An image processing method based on gray-scale values, characterized by comprising the steps of:
acquiring image pixel information in a fixed area aiming at each frame of image;
for the fixed area, obtaining a maximum value max [ i ] and a minimum value min [ i ] of the gray value of each row of pixel points, and carrying out arithmetic averaging to obtain a row threshold value g [ i ] of each row, wherein i represents the current calculation row number, i is 1, 2,.
Adding all line thresholds G [ i ] of each frame of image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame of image, and comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame of image; when the gray value of the pixel point is larger than or equal to G, the pixel point is judged to be a white point, and the gray value of the pixel point is adjusted to be a preset white brightness constant; when the gray value of a pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image;
and comparing the adjusted image frame with the next image frame after adjustment, and judging that a moving object appears in the fixed area when the constant from the white brightness constant to the black brightness constant or the jitter from the black brightness constant to the white brightness constant appears.
2. The method of claim 1, wherein: the white luminance constant is set to 255 and the black luminance constant is set to 0.
3. The method of claim 1, wherein: the method for collecting the image pixel information in the fixed area aiming at each frame of image comprises the following steps,
acquiring the number n of rows and the number m of columns contained in a first frame of image based on a fixed area; starting from a first pixel point of a first row of the region, acquiring information of each pixel point of the first row and sequentially storing the information into pic [1] [ j ], wherein j represents the number of columns, and j is 1, 2. And so on, acquiring the information of each pixel point in the ith row and sequentially storing the information into pic [ i ] [ j ];
for other image frames, the above steps are repeated to store image pixel information pic [ i ] [ j ] for each image frame.
4. The method of claim 1, wherein: and when the moving object is judged to appear, judging the moving direction of the moving object according to the jumping direction of the pixel point with the jumping gray value.
5. The method according to claim 1 or 4, characterized in that: and when the moving object is judged to appear, judging the size of the moving object according to the region range of the pixel point with the jittering gray value.
6. An image processing apparatus based on a gradation value, characterized by comprising: the information acquisition module is used for acquiring image pixel information in the fixed area aiming at each frame of image;
the information analysis module is used for obtaining a maximum value max [ i ] and a minimum value min [ i ] of the gray value of each row of pixel points for the fixed area, and performing arithmetic averaging to obtain a row threshold value g [ i ] of each row, wherein i represents the current calculation row number, i is 1, 2, and n represents the total row number; adding all line thresholds G [ i ] of each frame of image, dividing the sum by the total line number n to obtain a regional gray standard value G of a fixed region in the frame of image, and comparing the gray value of each pixel point with the regional gray standard value G from the first pixel point of the frame of image;
the image adjusting module is used for judging the pixel point as a white point when the gray value of the pixel point is greater than or equal to G, and adjusting the gray value of the pixel point as a preset white brightness constant; when the gray value of a pixel point is smaller than G, the pixel point is judged to be a black point, the gray value of the pixel point is adjusted to be a preset black brightness constant, and only two gray values of a white brightness constant and a black brightness constant exist in the adjusted frame image;
and the judging module is used for comparing the adjusted image frame with the next adjusted image frame and judging that a moving object appears in the fixed area when the constant from the white brightness constant to the black brightness constant or the jitter from the black brightness constant to the white brightness constant appears.
7. The apparatus of claim 6, wherein: the device also comprises a parameter setting module for setting the white brightness constant and the black brightness constant by a user.
8. The apparatus of claim 6, wherein: the judging module comprises a moving direction judging submodule used for judging the moving direction of the moving object according to the jumping direction of the pixel points with the jumping gray value when the moving object is judged to appear.
9. The apparatus of claim 6 or 8, wherein: the judging module comprises an object size judging submodule and is used for judging the size of the moving object according to the area range of the pixel points with the bouncing gray value when the moving object is judged to appear.
10. A method of detecting a moving object within a fixed area, comprising: detecting moving objects using the method of any one of claims 1-5.
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