CN107610106B - Detection method, detection device, electronic equipment and computer-readable storage medium - Google Patents
Detection method, detection device, electronic equipment and computer-readable storage medium Download PDFInfo
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- CN107610106B CN107610106B CN201710772961.8A CN201710772961A CN107610106B CN 107610106 B CN107610106 B CN 107610106B CN 201710772961 A CN201710772961 A CN 201710772961A CN 107610106 B CN107610106 B CN 107610106B
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Abstract
The embodiment of the invention relates to the field of smart home, and discloses a detection method, a detection device, electronic equipment and a computer-readable storage medium. The detection method comprises the following steps: under the condition that no person is detected outside the door, acquiring a black-and-white image of the surrounding environment where the door is located, and taking the black-and-white image as an image to be detected; processing the image to be detected, and determining a first matrix which corresponds to the image to be detected and is used for representing the color distribution of the image to be detected; comparing the first matrix with a second matrix which is corresponding to the standard image and is used for representing the color distribution of the standard image, and determining a comparison result; and judging whether the door is in a closed state or not according to the comparison result. According to the embodiment of the invention, whether the door is in the closed state can be detected to remind a user, so that potential safety hazards caused by the fact that the door is not closed are reduced, the cost for detecting whether the door is in the closed state is reduced, and the method and the device are convenient to popularize.
Description
Technical Field
The embodiment of the invention relates to the field of smart home, in particular to a detection method, a detection device, electronic equipment and a computer-readable storage medium.
Background
With the continuous development of science and technology, the safety awareness of people is stronger, the traditional cat eye adopts an optical imaging mode, has many defects in use, cannot clearly see the situation outside the door under the condition of insufficient light, and is easy to pry; the needs of people cannot be met, and therefore more and more people use the electronic peep hole now, and the safety is more reliably realized by installing the electronic peep hole on the door.
The inventor finds that at least the following problems exist in the prior art: at present, a traditional mechanical lock is usually adopted for a household door lock, and when a user does not close the door due to negligence or too much hurry when going out of the door and does not know the situation, potential safety hazards are caused; although present in order to solve this potential safety hazard, the design has intelligent lock, can monitor whether the door is closed, however, the cost of this kind of mode is high, is unfavorable for promoting.
Disclosure of Invention
An object of embodiments of the present invention is to provide a detection method, an apparatus, an electronic device, and a computer-readable storage medium, which enable detection of whether a door is in a closed state for reminding a user, reduce potential safety hazards caused by the fact that the door is not closed, reduce cost for detecting whether the door is in the closed state, and facilitate popularization.
In order to solve the above technical problem, an embodiment of the present invention provides a detection method, including: under the condition that no person is detected outside the door, acquiring a black-and-white image of the surrounding environment where the door is located, and taking the black-and-white image as an image to be detected; processing the image to be detected, and determining a first matrix which corresponds to the image to be detected and is used for representing the color distribution of the image to be detected; comparing the first matrix with a second matrix which is corresponding to a standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment of the door, which is acquired under the condition that the door is in a closed state and no person is outside the door; and judging whether the door is in a closed state or not according to the comparison result.
The embodiment of the invention also provides a detection device, which comprises; the device comprises an acquisition module, a matrix determination module, a comparison module and a judgment module; the acquisition module is used for acquiring a black-and-white image of the surrounding environment where the door is located under the condition that no person is detected outside the door, and taking the black-and-white image as an image to be detected; the matrix determining module is used for carrying out image processing on the image to be detected and determining a first matrix which is corresponding to the image to be detected and is used for representing the color distribution of the image to be detected; the comparison module is used for comparing the first matrix with a second matrix which is corresponding to the standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment where the door is located, the black-and-white image is acquired when the door is in a closed state and no person is outside the door; the judging module is used for judging whether the door is in a closed state or not according to the comparison result.
An embodiment of the present invention also provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of detecting.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and is characterized in that the computer program is executed by a processor to realize the detection method.
Compared with the prior art, the method and the device have the advantages that under the condition that the door is unmanned, the black and white image of the surrounding environment where the door is located is obtained and serves as the image to be detected, the image to be detected is processed to obtain the matrix corresponding to the image to be detected, the first matrix is compared with the second matrix to determine the comparison result, and the state of the door is determined according to the comparison result. The acquired standard image and the image to be detected are black and white images, and the acquired images only have black and white colors and are few in color, so that the difficulty of image processing can be effectively reduced, the image processing speed is improved, meanwhile, the interference caused by other colors can be reduced, and the image processing accuracy is improved. In addition, whether the door is in a closed state or not is judged through comparison between matrixes used for expressing image color distribution, comparison between the images is converted into comparison of a mathematical expression, the judgment difficulty between the image to be detected and the standard image is simplified, the judgment of the image to be detected is accelerated, and therefore the judgment of whether the detection door is in the closed state or not is accelerated. Because the intelligent door lock is high in cost, the intelligent door lock does not need to be installed, whether the door is in the closed state or not can be judged, the cost for judging whether the door is in the closed state or not is reduced, and the intelligent door lock is more beneficial to popularization. In addition, the function of judging whether the door is in the closed state is realized through the detection method, so that the detection method not only can detect the environment around the door, but also can effectively detect the state of the door, and effectively reduces the potential safety hazard caused by the fact that the door is not closed.
In addition, before acquiring a black-and-white image of the surrounding environment where the door is located and taking the black-and-white image as an image to be detected, the detection method further includes: setting the resolution of a camera to be a preset resolution, wherein the preset resolution defines that the number of pixels of an image shot by the camera in the horizontal direction is equal to the number of pixels in the vertical direction; and setting the camera to enter a black and white shooting mode. Before the black-and-white image of the surrounding environment where the door is located is obtained, the resolution of the camera is set to be the preset resolution, so that the number of pixel points of the image shot by the camera in the horizontal direction is equal to that of the pixel points of the image shot by the camera in the vertical direction, and the subsequent image processing on the image is facilitated. In addition, the camera is set to be in a black-and-white shooting mode, so that the picture shot by the camera is black and white, software is not needed to process the color image, the processing steps of the image are reduced, the distortion of the image color caused by the software processing can be prevented, and the accuracy of the obtained image is improved.
In addition, the image processing is performed on the image to be detected, and a first matrix corresponding to the image to be detected and used for representing the color distribution of the image to be detected is determined, which specifically includes: reducing the image to be detected according to a preset proportion; dividing the reduced image to be detected into N multiplied by N areas, wherein N is an integer greater than 1, and the sizes of any two areas are the same; determining the dominant color of each area, wherein the dominant color is a color with a larger proportion in the area, and the dominant color is black or white; and determining a first matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the first matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N. And reducing the image to be detected according to the proportion, dividing the image to be detected into areas, determining the dominant color of each area, and accelerating the speed of determining the first matrix by reducing the image.
In addition, determining the dominant color of each region specifically includes: calculating the proportion value of the number of black pixels in each region to the total number of pixels in the region and the proportion value of the number of white pixels to the total number of pixels in the region; and judging whether the proportion value of the number of black pixels in each region to the total number of pixels in the region is larger than the proportion value of the number of white pixels to the total number of pixels in the region, if so, determining that the dominant color of the region is black, and otherwise, determining that the dominant color of the region is white. The ratio of black or white pixel points in each region to the total pixel points in the region is counted, and the larger ratio is determined as the dominant color of the region, so that the image processing operation and the image color error are further simplified, the image processing speed is increased, and the accuracy of the processed image is ensured.
In addition, comparing the first matrix with a second matrix corresponding to the standard image and used for representing the color distribution of the standard image, and determining a comparison result, specifically comprising: counting the number of the elements with the same position in the first matrix and the second matrix, and calculating the proportion value of the counted number in the total element number contained in the first matrix; and taking the ratio of the counted number to the total element number contained in the first matrix as a comparison result. The similarity between the image to be detected and the standard image is judged by counting the number of the elements with the same position in the first matrix and the second matrix, so that the relation between the image to be detected and the standard image can be determined, and the comparison result is accurate by comparing the element value of each element in the matrix corresponding to the image to be detected.
In addition, according to the comparison result, whether the door is in the closed state is judged, and the method specifically comprises the following steps: and judging whether the comparison result exceeds a threshold value, if so, determining that the door is in a closed state, and otherwise, determining that the door is in an unclosed state. By judging whether the comparison result exceeds the threshold value, whether the door is in a closed state or not can be determined quickly and accurately.
In addition, the standard image belongs to any one image in a standard image set, the standard image set comprises M images, and M is an integer greater than 2; before determining whether the comparison result exceeds a threshold, the detection method further includes: determining a threshold value; determining the threshold specifically includes: selecting any one image in the standard image set as a reference image, carrying out image processing on the reference image, and determining a third matrix corresponding to the reference image and used for expressing the color distribution of the reference image; performing image processing on each standard image except the reference image in the standard image set, and determining a matrix which is corresponding to each standard image except the reference image and is used for expressing the color distribution of the standard image; calculating each standard image except the reference image in the standard image set respectively: counting the number of the third matrix which is equal to the element value of the element at the same position in the matrix which is corresponding to the standard image and used for representing the color distribution of the standard image, calculating the proportion value of the counted number in the total element number contained in the third matrix, and taking the proportion value of the counted number in the total element number contained in the third matrix as the comparison result of the standard image; and calculating the average value of the comparison results of the M-1 standard images, and taking the average value as the threshold value. The method comprises the steps of selecting an image from a standard image set as a reference image, comparing a matrix corresponding to the reference image with matrices corresponding to other standard images, determining M-1 comparison results, calculating an average value of the M-1 comparison results and using the average value as a threshold value, wherein the comparison results of the reference image are different due to different brightness in each standard image, and obtaining an accurate threshold value by comparing the reference image with different standard images and then obtaining an average value, so that the judgment result obtained by judging the door state is more accurate.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a schematic flow chart of a detection method according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a specific flow of determining each dominant color in a detection method according to a first embodiment of the present invention;
FIG. 3 is a schematic flowchart of a method for determining a comparison result in a detection method according to a first embodiment of the present invention;
FIG. 4 is a schematic flow chart of a detection method according to a second embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for determining a threshold value in a detection method according to a second embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a detecting device according to a third embodiment of the present invention;
FIG. 7 is a schematic structural diagram of a detecting device according to a fourth embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
A first embodiment of the present invention relates to a detection method. The detection method is applied to electronic equipment, and the electronic equipment can be an intelligent cat eye, a visual doorbell, a visual interphone and the like. The electronic device may be fixed to the door (e.g., at the center of the door) or may not be fixed to the door (e.g., at the periphery of the door or on the left/right walls of the door). The electronic device may include a camera, a human body sensing detector, and the like. The present embodiment will be described in detail with an example in which the electronic device is a smart cat eye. The specific flow is shown in fig. 1:
step 101: and under the condition that no person is detected outside the door, acquiring a black-and-white image of the surrounding environment where the door is located, and taking the black-and-white image as an image to be detected.
Specific human body induction detection of intelligent cat eyeThe detector (such as an infrared sensor and the like) can monitor the outside of the door in real time, and when people or animals enter the monitoring range of the human body induction detector, the human body induction detector can detect the people or the animals outside the door. Under the condition that the human body induction detector detects that no person is outside the door, the intelligent cat eye can be triggered to open the camera of the intelligent cat eye, and images of the surrounding environment where the door is located are shot; or trigger other equipment with a shooting function and in communication connection with the intelligent cat eye (such as a camera installed around and in communication connection with the intelligent cat eye). The captured image may be a color image or a black-and-white image. If the image obtained by shooting is colorful, the color image needs to be converted into a gray image, and then the gray image is converted into a black-and-white image, wherein the method for converting the gray image into the black-and-white image comprises the following steps: 50% threshold, half tone screen, custom pattern, diffuse color imitation, etc. The color has three primary colors (i.e., red, green and blue, abbreviated as "RGB"), and different colors can be accurately represented by RGB color values, wherein the RGB color value of black is (0,0,0), the RGB color value of white is (255 ), and three of the RGB color values, which are completely equal to each other, are gray. The embodiment is described by taking an example of converting a grayscale image into a black-and-white image according to a 50% threshold method, where the 50% threshold method is to determine whether a color value of one color (e.g., red, green, and blue) of each pixel point in the grayscale image is greater than or equal to 50% of a maximum color value, if so, convert the color of the pixel point into white, and otherwise, convert the color of the pixel point into black. For example, assume pixel A in grayscale image A2×3The red color value of (1) is 245, and the pixel point A3×3The red color value is 12, the gray image A is converted into a black-white image by using a 50% threshold value method, and then the pixel point A2×3The red color value 245 is larger than 255 × 50% i.e. pixel A2×3The color is changed to white and the pixel point A3×3Color value 245 is less than 255 × 50% value, i.e. pixel point A3×3The color of (2) turns to black.
And taking the obtained black-and-white image of the surrounding environment where the door is located as an image to be detected.
It should be noted that, when describing the size of an image, the description may be performed in a manner of describing the resolution of the image, for example, assuming that the resolution of the image a is 1024 × 1024 (indicating that the number of pixels included in one row in the horizontal direction is 1024 and the number of pixels included in one column in the vertical direction is 1024), the size of the image a may be described as 1024 × 1024.
It should be noted that the condition for triggering the camera to shoot may be that the human body sensor senses a person or an animal first, and then triggers the camera to shoot an image of the surrounding environment of the door when sensing that no person is outside the door. For example, the human body sensor 1 detects that there is a person outside the door at time T1 to T2, detects that there is no person at time T3, and the time point T2 is earlier than the time point T3, and triggers the camera to capture an image of the surrounding environment of the door.
Step 102: and carrying out image processing on the image to be detected, and determining a first matrix which is corresponding to the image to be detected and is used for expressing the color distribution of the image to be detected.
Specifically, the image to be detected is processed, i.e. a matrix in mathematics is used to describe the color distribution of the image to be detected.
In one possible implementation, the image to be detected is reduced according to a preset proportion; dividing the reduced image to be detected into N multiplied by N areas, wherein N is an integer greater than 1, and the sizes of any two areas are the same; determining the dominant color of each area, wherein the dominant color is a color with a larger proportion in the area, and the dominant color is black or white; and determining a first matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the first matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N.
Specifically, one row in the horizontal direction of the image to be detected is reduced according to a preset proportion, and one column in the vertical direction of the image to be detected is reduced according to a preset direction. The preset ratio may be set according to the resolution of the image, for example, if the resolution of the image is 720 × 720, the preset ratio may be 20 times; if the resolution of the image is 128 × 128, the predetermined ratio may be 4 times. Dividing the reduced image to be detected into N × N regions, where N is an integer greater than 1, for example, assuming that the size of the reduced image a is 720 × 720, dividing the image into regions, and dividing the image a in such a manner that the size of each region is 20 × 20, so as to obtain 36 × 36 regions, where the size of each region is the same. Of course, if the number of pixels in the horizontal direction of the size of the image to be detected is different from the number of pixels in the vertical direction, after the image to be detected is reduced, the image may be divided without using a reduced preset scale value so that any two divided regions are the same, for example, assuming that the size of the reduced image B is 720 × 360, the image is divided into regions, and the image B is divided by using the size of each region as 20 × 10, so as to obtain 36 × 36 regions, where the size of each region is the same.
Determining a first matrix, wherein an element value of the ith row and jth column position in the first matrix represents the dominant color of a region of the ith row and jth column position corresponding to the image to be detected, wherein i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N. For example, the color of the image A to be detected is
The determined first matrix
"0" is used to indicate black and "1" is used to indicate white.
It is worth mentioning that the more the divided regions are, the more accurate the judgment of the image to be detected is.
In a possible embodiment, taking any one of the regions as an example for explanation, the specific flow for determining the dominant color of the region is shown in fig. 2, and includes the following sub-steps:
substep 1021: and calculating the proportion value of the number of black pixels in the area to the total number of pixels in the area and the proportion value of the number of white pixels in the area to the total number of pixels in the area.
Specifically, the RGB color value of black is (0,0,0), and the RGB color value of white is (255 ), the number of white pixels and the number of black pixels in each region can be calculated from the RGB color values, so that the ratio of the number of black pixels in each region to the total number of pixels in the region and the ratio of the number of white pixels to the total number of pixels in the region can be calculated. For example, assuming that the size of a region a is 4 × 4, the total number of pixels in the region a is calculated to be 16, the RGB color values of 13 pixels are counted to be (0,0,0), and the RGB color values of 3 pixels are counted to be (255 ), it is determined that there are 13 black pixels and 3 white pixels in the region a, the ratio of the number of black pixels to the total number of pixels is calculated to be 13/16, and the ratio of the number of white pixels to the total number of pixels is calculated to be 3/16.
Substep 1022: and judging whether the proportion value of the number of the black pixels in the region to the total number of the pixels in the region is larger than the proportion value of the number of the white pixels to the total number of the pixels in the region, if so, executing a substep 1023, and otherwise, executing a substep 1024.
For example, assume that there are 2 regions, the ratio of the number of black pixels in region 1 to the total number of pixels in the region is 13/16, and the ratio of the number of white pixels in region 1 to the total number of pixels in the region is 3/16. The proportion value of the number of black pixels in the region 2 to the total number of pixels in the region is 7/16, and the proportion value of the number of white pixels in the region 2 to the total number of pixels in the region is 9/16, then in the region 1, 13/16 is greater than 3/16, and the substep 1023 is executed; in region 2, 7/16 is less than 9/16, then sub-step 1024 is performed.
Substep 1023: the dominant color of the region is determined to be black.
Substep 1024: the dominant color of the region is determined to be white.
After the dominant color of each region is determined, a first matrix is determined according to the dominant color of each region. Wherein, because the image to be detected only has black and white, the determined first matrix is represented by the number 0 to represent black, and the number 1 to represent white. The following describes in detail a process of performing image processing on the image to be detected and determining a first matrix corresponding to the image to be detected and used for representing the color distribution of the image to be detected, by using a specific example.
Step 103: and comparing the first matrix with a second matrix which is corresponding to a standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment of the door, which is acquired under the condition that the door is in a closed state and no person is outside the door.
Specifically, the standard image is a black-and-white image acquired when the door is closed and no person is outside the door, the standard image is also subjected to image processing, and a second matrix corresponding to the standard image and used for representing the color distribution of the image to be detected is determined. The image processing process is substantially the same as the image processing process in step 102, and it should be noted that the image to be detected is reduced by a preset ratio, where the preset ratio is the same as the preset ratio in the reduction of the standard image by the preset ratio, and the dividing mode also needs to be the same.
In a specific embodiment, comparing the first matrix with a second matrix corresponding to a standard image and used for representing the color distribution of the standard image, and determining a comparison result, a specific process is shown in fig. 3, and includes the following sub-steps:
substep 1031: and counting the number of the elements with the same position in the first matrix and the second matrix, and calculating the proportion value of the counted number in the total number of the elements contained in the first matrix.
Specifically, the first matrix and the second matrix are of the same order, and the element values at the same position in the first matrix and the second matrix are compared to judge whether the element values are equal, so that the number of the equal elements is counted. For example, assume a first matrix
Second matrix
Comparison is performed per bit of the matrix, a111 and b11The comparison is made when the value is 0,a11and b11Are not equal, then compare a in turn12And b12Whether the values of (A) are equal to each other21And b21Whether the values of (A) are equal to each other22And b22Is equal, the number of statistical element values equal is 3, and the ratio of the number obtained by calculation to the total number of elements included in the first matrix is 3/4.
Substep 1032: and taking the ratio of the counted number to the total element number contained in the first matrix as a comparison result.
For example, if the ratio of the counted number to the total number of elements included in the first matrix is 3/4, the comparison result of the comparison between the first matrix and the second matrix is 3/4, which indicates that the similarity between the first matrix and the second matrix is 75%.
Step 104: and judging whether the door is in a closed state or not according to the comparison result.
In one possible embodiment, it is determined whether the comparison result exceeds a threshold, and if so, the door is determined to be in a closed state, otherwise, the door is determined to be in an unclosed state. By judging whether the comparison result exceeds the threshold value, the state of the door can be quickly and accurately determined.
Specifically, the comparison result determined after the comparison between the first matrix and the second matrix can be used to represent the similarity between the first matrix and the second matrix, that is, the comparison result represents the similarity between the image to be detected and the standard image. The threshold may be a preset threshold, for example, the threshold may be 75%, 80%, 90%, etc.
In addition, it is worth mentioning that after the electronic device determines whether the door is in the closed state, if the door is not in the closed state, the electronic device may send a warning to notify the user through the electronic device itself, or notify other intelligent devices to remind the user that the door is not in the closed state.
Compared with the prior art, the embodiment of the invention obtains the black-and-white image of the surrounding environment of the door under the condition that the door is unmanned, takes the black-and-white image as the image to be detected, performs image processing on the image to be detected to obtain the matrix corresponding to the image to be detected, compares the first matrix with the second matrix to determine the comparison result, and determines the state of the door according to the comparison result. The acquired standard image and the image to be detected are black and white images, and the acquired images only have black and white colors and are few in color, so that the difficulty of image processing can be effectively reduced, the image processing speed is improved, meanwhile, the interference caused by other colors can be reduced, and the image processing accuracy is improved. In addition, whether the door is in a closed state or not is judged through comparison between matrixes used for expressing image color distribution, comparison between the images is converted into comparison of a mathematical expression, the judgment difficulty between the image to be detected and the standard image is simplified, the judgment of the image to be detected is accelerated, and therefore the judgment of whether the detection door is in the closed state or not is accelerated. This embodiment is applied to electronic equipment for through this detection method, electronic equipment can confirm promptly that the door is in the closed condition under unmanned state, because the cost of intelligent lock is high, and this embodiment need not to realize judging the state that the door is in the closed condition through installing intelligent lock, has reduced the cost of judging whether the door is in the closed condition, more does benefit to the popularization. In addition, whether the door is in the function of closing state is judged through the electronic equipment, so that the environment around the door can be detected through the electronic equipment, the state of the door can be effectively detected, and potential safety hazards caused by the fact that the door is not closed are effectively reduced. In addition, the image to be detected is reduced according to the proportion, the image to be detected is divided into blocks, the dominant color of each block area is determined, and the speed of determining the first matrix can be increased; meanwhile, the ratio of black or white pixel points in each region to the total pixel points in the region is counted, and the larger ratio is determined as the dominant color of the region, so that the image processing operation and the image color error are further simplified, the image processing speed is increased, and the accuracy of the processed image is ensured.
A second embodiment of the present invention relates to a detection method. The second embodiment is substantially the same as the first embodiment, and mainly differs therefrom in that: in the second embodiment of the present invention, before acquiring a black-and-white image of the surrounding environment where the door is located and taking the black-and-white image as an image to be detected, a camera is further set; the threshold value of the judgment is determined by the standard image set. The specific flow is shown in fig. 4:
step 401: the method comprises the steps of setting the resolution of a camera to be a preset resolution, wherein the preset resolution defines that the number of pixels of an image shot by the camera in the horizontal direction is equal to the number of pixels in the vertical direction.
Specifically, the resolution of a camera in the electronic device may be set in advance, or the resolution of a camera in communication connection with the electronic device may be set in advance, where the preset resolution defines that the number of pixels in the horizontal direction of an image captured by the camera is equal to the number of pixels in the vertical direction, so that the image to be detected is divided in subsequent steps.
Step 402: and setting the camera to enter a black and white shooting mode.
Specifically, the camera is set to be in a black-and-white shooting mode in advance, the shot picture is a black-and-white image, the shot image does not need to be converted into a gray image, image processing steps of the shot image are reduced, and image distortion caused by image processing is reduced.
Step 403: and under the condition that no person is detected outside the door, acquiring a black-and-white image of the surrounding environment where the door is located, and taking the black-and-white image as an image to be detected.
Step 404: and carrying out image processing on the image to be detected, and determining a first matrix which is corresponding to the image to be detected and is used for expressing the color distribution of the image to be detected.
Step 405: and comparing the first matrix with a second matrix which is corresponding to a standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment of the door, which is acquired under the condition that the door is in a closed state and no person is outside the door.
Step 406: and judging whether the door is in a closed state or not according to the comparison result.
Specifically, step 406 is substantially the same as step 104 in the first embodiment, and the process of determining whether the door is in the closed state is the same, except that the method of determining the threshold used in the determination process is different.
In one possible embodiment, the standard image belongs to any one of a standard image set, where the standard image set includes M images, and M is an integer greater than 2; before determining whether the comparison result exceeds a threshold, the detection method further includes: determining a threshold value; a specific flow for determining the threshold is shown in fig. 5, and specifically includes the following sub-steps:
substeps 4061: and selecting any one image in the standard image set as a reference image, carrying out image processing on the reference image, and determining a third matrix corresponding to the reference image and used for expressing the color distribution of the reference image.
Specifically, the standard image set includes M standard images. Due to the difference of the light intensity, when the door is in a closed state and no person is outside the door, the black and white color distribution in the images shot at different time points is different, and therefore, the M standard images are not the same. Selecting any one image in the standard image set as a reference image, and carrying out image processing on the reference image, wherein the processing process comprises the following steps: reducing the reference image according to a preset proportion; dividing the reduced reference image into N multiplied by N areas, wherein N is an integer larger than 1, and the sizes of any two areas are the same; determining the dominant color of each area, wherein the dominant color is a color with a larger proportion in the area, and the dominant color is black or white; and determining a third matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the third matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N. The determination of the third matrix is substantially the same as the determination of the first matrix, and will not be described herein.
Substeps 4062: and performing image processing on each standard image except the reference image in the standard image set, and determining a matrix which is corresponding to each standard image except the reference image and is used for expressing the color distribution of the standard image.
Specifically, each standard image except for the reference image in the standard image set is subjected to image processing, and the process of image processing of each standard image is substantially the same as that of reference image processing, which is not described herein again. At this time, M-1 matrixes are obtained, and the M-1 matrixes respectively correspond to one standard image.
Substep 4063: calculating each standard image except the reference image in the standard image set respectively: counting the number of the third matrix which is equal to the element value of the element at the same position in the matrix which is corresponding to the standard image and used for representing the color distribution of the standard image, calculating the proportion value of the counted number in the total element number contained in the third matrix, and taking the proportion value of the counted number in the total element number contained in the third matrix as the comparison result of the standard image.
Specifically, the process of comparing the third matrix with the matrix corresponding to the standard image and used for representing the color distribution of the standard image is substantially the same as the process of comparing the first matrix with the second matrix corresponding to the standard image and used for representing the color distribution of the standard image in step 405, and this step will not be repeated again. The following will explain with specific examples.
For example, assume that the standard image set includes 3 standard images, which are respectively a standard image 1, a standard image 2, and a standard image 3, the standard image 2 is selected as a reference image, the reference image is subjected to image processing, a third matrix B corresponding to the reference image and used for representing the color distribution of the reference image is determined, a matrix a corresponding to the standard image 1 and used for representing the color distribution of the standard image 1, and a matrix C corresponding to the standard image 3 and used for representing the color distribution of the standard image 3 are determined. Then, the comparison result is determined to be that each standard image except the reference image in the standard image set is calculated respectively, the number of the same position element values in the third matrix B and the matrix a is counted, the ratio value a of the counted number to the total element number of the third matrix B is calculated, and the ratio value a of the counted number to the total element number included in the third matrix B is used as the comparison result a of the standard image. And counting the number of the elements with the same position in the third matrix B and the matrix C, calculating a ratio value B of the counted number to the total number of the elements in the third matrix B, and taking the ratio value B of the counted number to the total number of the elements in the third matrix B as a comparison result B of the standard image. 2 comparison results for representing 2 standard images are determined, namely a comparison result a and a comparison result b.
Substeps 4064: and calculating the average value of the comparison results of the M-1 standard images, and taking the average value as a threshold value.
Specifically, an average of M-1 comparison results is calculated, for example, assuming that the standard image set includes 3 standard images, and the comparison results of 2 standard images are calculated, that is, the comparison result a is 79% and the comparison result b is 98%, then the comparison result a and the comparison result b are averaged, the calculated average is 88.5%, and the determined threshold is 88.5%.
After the threshold is determined, it is determined whether the comparison result obtained in step 405 exceeds the threshold, if so, the door is determined to be in the closed state, otherwise, the door is determined to be in the unclosed state.
It should be noted that steps 403 to 405 in this embodiment are substantially the same as steps 101 to 103 in the first embodiment, and steps 403 to 405 will not be described herein again.
According to the detection method provided by the embodiment, before the black-and-white image of the surrounding environment where the door is located is obtained, the resolution of the camera is set to be the preset resolution, so that the number of pixels of the image shot by the camera in the horizontal direction is equal to that of pixels in the vertical direction, and the subsequent image processing on the image is facilitated. In addition, the camera is set to be in a black-and-white shooting mode, so that the picture shot by the camera is black and white, and the black-and-white picture is obtained without other software processing, the processing steps of the picture are reduced, the distortion of the color of the picture caused by the software processing can be prevented, and the accuracy of the obtained picture is improved. In addition, one image is selected from the standard image set as a reference image, the matrix corresponding to the reference image is compared with the matrices corresponding to the other standard images, M-1 comparison results are determined, the average value of the M-1 comparison results is calculated and is used as a threshold value, the comparison result with the reference image is different due to different brightness in each standard image, and the average value is obtained after the reference image is compared with the different standard images, so that the more accurate threshold value can be obtained, and the door state can be more accurately judged.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
A third embodiment of the present invention relates to a detection device 60 including: the specific structure of the acquiring module 601, the matrix determining module 602, the comparing module 603, and the determining module 604 is as shown in fig. 6:
the acquiring module 601 is configured to acquire a black-and-white image of an environment around a door when no person outside the door is detected, and use the black-and-white image as an image to be detected.
A matrix determining module 602, configured to perform image processing on the image to be detected, and determine a first matrix corresponding to the image to be detected and used for representing color distribution of the image to be detected.
In a possible implementation, the matrix determining module 602 is specifically configured to: reducing the image to be detected according to a preset proportion; dividing the reduced image to be detected into N multiplied by N areas, wherein N is an integer greater than 1, and the sizes of any two areas are the same; determining the dominant color of each area, wherein the dominant color is a color with a larger proportion in the area, and the dominant color is black or white; and determining a first matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the first matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N. The method comprises the steps of reducing an image to be detected according to a proportion, partitioning the image to be detected, determining the dominant color of each block area, reducing the error of the determined dominant color of each block area, and enabling the determined matrix corresponding to the image to be detected to be accurate.
In a possible implementation, the matrix determining module 602 is further specifically configured to: calculating the proportion value of the number of black pixels in each region to the total number of pixels in the region and the proportion value of the number of white pixels to the total number of pixels in the region; and judging whether the proportion value of the number of black pixels in each region to the total number of pixels in the region is larger than the proportion value of the number of white pixels to the total number of pixels in the region, if so, determining that the dominant color of the region is black, and otherwise, determining that the dominant color of the region is white. The ratio value of the black and white pixel points in each region to the total pixel points in the region is counted, the larger ratio value is determined as the dominant color of the region, the image operation and the image color error are further simplified, the image processing speed is increased, and the accuracy of the processed image is guaranteed.
The comparing module 603 is configured to compare the first matrix with a second matrix, which is corresponding to the standard image and used for representing the color distribution of the standard image, and determine a comparison result, where the standard image is a black-and-white image of an environment around the door, where the black-and-white image is acquired when the door is in a closed state and no person is outside the door.
In a possible embodiment, the comparing module 603 is specifically configured to count the number of elements in the first matrix and the second matrix, where the element values of the elements in the same position are equal, and calculate a ratio of the counted number to the total number of elements included in the first matrix. And taking the ratio of the counted number to the total number of the elements contained in the first matrix as the comparison result.
The determining module 604 is configured to determine whether the door is in a closed state according to the comparison result.
In a possible implementation manner, the determining module 604 is specifically configured to determine whether the comparison result exceeds a threshold, if so, determine that the door is in a closed state, and otherwise, determine that the door is in an unclosed state. By judging whether the comparison result exceeds the threshold value, the state of the door can be quickly and accurately determined.
It is worth mentioning that the matrix determination module 602 is further configured to determine a second matrix for representing the color distribution of the standard image.
Compared with the prior art, the method and the device have the advantages that under the condition that the door is unmanned, the acquisition module acquires a black-and-white image of the surrounding environment where the door is located and serves as an image to be detected, the matrix determining module determines a matrix for representing the color distribution of the image, the comparison module compares the first matrix with the second matrix, and a comparison result is determined; and the judging module determines the state of the door according to the comparison result. The acquired standard image and the image to be detected are black and white images, and the acquired images are only black and white images, so that the types of the colors in the images are few, the difficulty of image processing can be effectively reduced, the speed of image processing is improved, meanwhile, the interference caused by other colors can be reduced, and the accuracy of image processing is improved. In addition, whether the door is in a closed state or not is judged through comparison between matrixes corresponding to the images, the comparison between the images is converted into comparison in a mathematical mode, the judgment difficulty between the image to be detected and the standard image is simplified, the judgment of the image to be detected is accelerated, and therefore the judgment of the state of the detection door is accelerated. Through the detection device in this embodiment, can realize being in the judgement of closed condition to the door, and need not to judge whether the door is in the state of closing through the installation intelligence lock, reduced the cost of judging whether the door is in closed condition, more do benefit to the popularization. In addition, the detection device in the embodiment can also effectively detect the state of the door, and effectively reduces the potential safety hazard caused by the fact that the door is not closed. In addition, the image to be detected is reduced according to the proportion, the image to be detected is divided into blocks, the dominant color of each block area is determined, and the speed of determining the first matrix can be increased; meanwhile, the ratio of black or white pixel points in each region to the total pixel points in the region is counted, and the larger ratio is determined as the dominant color of the region, so that the image processing operation and the image color error are further simplified, the image processing speed is increased, and the accuracy of the processed image is ensured.
It should be understood that this embodiment is an example of the apparatus corresponding to the first embodiment, and may be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment.
It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.
The fourth embodiment of the present invention relates to a detection device 70. As shown in fig. 7, the specific structure of the detecting device 70 includes: the obtaining module 701, the matrix determining module 702, the comparing module 703, the determining module 704, and the setting module 705, where the obtaining module 701, the matrix determining module 702, the comparing module 703, and the determining module 704 are substantially the same as the obtaining module 601, the matrix determining module 602, the comparing module 603, and the determining module 604 in the fourth embodiment, and in order to reduce repetition, details of this embodiment will not be repeated.
The setting module 705 is specifically configured to set the resolution of the camera to a preset resolution before acquiring a black-and-white image of an ambient environment where the door is located and taking the black-and-white image as an image to be detected, where the preset resolution defines that the number of pixels of an image shot by the camera in the horizontal direction is equal to the number of pixels in the vertical direction; and setting the camera to enter a black and white shooting mode.
It should be noted that, in the present embodiment, the standard image belongs to any one of the images in the standard image set, where the standard image set includes M images, and M is an integer greater than 2. The judging module 704 is further configured to determine a threshold before judging whether the comparison result exceeds the threshold, specifically, select any one of the images in the standard image set as a reference image, perform image processing on the reference image, and determine a third matrix corresponding to the reference image and used for representing color distribution of the reference image; performing image processing on each standard image except the reference image in the standard image set, and determining a matrix which is corresponding to each standard image except the reference image and is used for expressing the color distribution of the standard image; calculating each standard image except the reference image in the standard image set respectively: counting the number of the third matrix which is equal to the element value of the element at the same position in the matrix which is corresponding to the standard image and used for representing the color distribution of the standard image, calculating the proportion value of the counted number in the total element number contained in the third matrix, and taking the proportion value of the counted number in the total element number contained in the third matrix as the comparison result of the standard image; and calculating the average value of the comparison results of the M-1 standard images, and taking the average value as the threshold value.
In the detection method provided by this embodiment, before the setting module obtains the black-and-white image of the surrounding environment where the door is located, the resolution of the camera is set to the preset resolution, so that the number of pixels of the image shot by the camera in the horizontal direction is equal to that of pixels in the vertical direction, and the subsequent image processing on the image is facilitated. In addition, the setting module sets the camera to be in a black-and-white shooting mode, so that the picture shot by the camera is black and white, and the black-and-white picture is obtained without other software processing, the processing steps of the picture are reduced, the distortion of the color of the picture caused by the software processing can be prevented, and the accuracy of the picture is improved. In addition, the judging module selects one image from the standard image set as a reference image, compares a matrix corresponding to the reference image with matrices corresponding to other standard images to determine M-1 comparison results, calculates an average value of the M-1 comparison results and uses the average value as a threshold value, the comparison results with the reference image are different due to different brightness in each standard image, and the average value is obtained after the reference image is compared with different standard images, so that a more accurate threshold value can be obtained, and the door state is more accurately judged.
Since the second embodiment corresponds to the present embodiment, the present embodiment can be implemented in cooperation with the second embodiment. The related technical details mentioned in the second embodiment are still valid in this embodiment, and the technical effects that can be achieved in the second embodiment can also be achieved in this embodiment, and are not described herein again in order to reduce the repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the second embodiment.
A fifth embodiment of the present invention relates to an electronic apparatus, as shown in fig. 8, including: at least one processor 801; and a memory 802 communicatively coupled to the at least one processor 801; the memory 802 stores instructions executable by the at least one processor 801, and the instructions are executed by the at least one processor 801, so that the at least one processor 801 can perform the detection method.
The memory 802 and the processor 801 are coupled by a bus, which may include any number of interconnected buses and bridges that link one or more of the various circuits of the processor 801 and the memory 802. The bus may also link various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 801 is transmitted over a wireless medium through an antenna, which receives the data and transmits the data to the processor 801.
The processor 801 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And the memory 802 may be used to store data used by the processor in performing operations.
A sixth embodiment of the present invention relates to a computer-readable storage medium storing a computer program that, when executed by a processor, is capable of implementing the method for reading and writing a magnetic disk mentioned in the first or second embodiment.
Those skilled in the art can understand that all or part of the steps in the method of the foregoing embodiments may be implemented by a program to instruct related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (9)
1. A method of detection, comprising:
under the condition that no person is detected outside the door, acquiring a black-and-white image of the surrounding environment where the door is located, and taking the black-and-white image as an image to be detected;
performing image processing on the image to be detected, and determining a first matrix which corresponds to the image to be detected and is used for representing the color distribution of the image to be detected;
comparing the first matrix with a second matrix which corresponds to a standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment where the door is located, the black-and-white image is acquired when the door is in a closed state and no person is outside the door;
judging whether the door is in a closed state or not according to the comparison result;
the image processing method includes the steps of performing image processing on an image to be detected, determining a first matrix corresponding to the image to be detected and used for representing color distribution of the image to be detected, and specifically including:
reducing the image to be detected according to a preset proportion;
dividing the reduced image to be detected into N multiplied by N areas, wherein N is an integer greater than 1, and the sizes of any two areas are the same;
determining the dominant color of each region, wherein the dominant color is a color with a higher proportion in the region, and the dominant color is black or white;
and determining the first matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the first matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N.
2. The inspection method according to claim 1, wherein before acquiring the black-and-white image of the environment around the door and using the black-and-white image as the image to be inspected, the inspection method further comprises:
setting the resolution of a camera to be a preset resolution, wherein the preset resolution defines that the number of pixels of an image shot by the camera in the horizontal direction is equal to the number of pixels in the vertical direction;
and setting the camera to enter a black and white shooting mode.
3. The detection method according to claim 1, wherein the determining the dominant color of each region specifically comprises:
calculating the proportion value of the number of black pixels in each region to the total number of pixels in the region and the proportion value of the number of white pixels to the total number of pixels in the region;
and judging whether the proportion value of the number of the black pixels in each region to the total number of the pixels in the region is larger than the proportion value of the number of the white pixels to the total number of the pixels in the region, if so, determining that the dominant color of the region is black, otherwise, determining that the dominant color of the region is white.
4. The detection method according to claim 3, wherein comparing the first matrix with a second matrix corresponding to a standard image and used for representing the color distribution of the standard image, and determining a comparison result specifically includes:
counting the number of the elements with the same position in the first matrix and the second matrix, and calculating the ratio of the counted number to the total number of the elements in the first matrix;
and taking the ratio of the counted number to the total element number contained in the first matrix as the comparison result.
5. The detecting method according to claim 4, wherein determining whether the door is in a closed state according to the comparison result specifically includes:
and judging whether the comparison result exceeds a threshold value, if so, determining that the door is in a closed state, and otherwise, determining that the door is in an unclosed state.
6. The detection method according to claim 5, wherein the standard image belongs to any one of a set of standard images, the set of standard images includes M images, M is an integer greater than 2;
before determining whether the comparison result exceeds a threshold, the detection method further includes: determining the threshold;
the determining the threshold specifically includes:
selecting any one image in the standard image set as a reference image, carrying out image processing on the reference image, and determining a third matrix corresponding to the reference image and used for representing the color distribution of the reference image;
performing image processing on each standard image except for the reference image in the standard image set, and determining a matrix which is corresponding to each standard image except for the reference image and is used for expressing the color distribution of the standard image;
calculating each standard image except the reference image in the standard image set respectively: counting the number of the third matrix which is equal to the element value of the element at the same position in the matrix which is corresponding to the standard image and used for representing the color distribution of the standard image, calculating the proportion value of the counted number in the total element number contained in the third matrix, and taking the proportion value of the counted number in the total element number contained in the third matrix as the comparison result of the standard image;
and calculating the average value of the comparison results of the M-1 standard images, and taking the average value as the threshold value.
7. An apparatus for testing, comprising; the device comprises an acquisition module, a matrix determination module, a comparison module and a judgment module;
the acquisition module is used for acquiring a black-and-white image of the surrounding environment where the door is located under the condition that no person is detected outside the door, and taking the black-and-white image as an image to be detected;
the matrix determining module is configured to perform image processing on the image to be detected, and determine a first matrix corresponding to the image to be detected and used for representing color distribution of the image to be detected, and specifically includes: reducing the image to be detected according to a preset proportion; dividing the reduced image to be detected into N multiplied by N areas, wherein N is an integer greater than 1, and the sizes of any two areas are the same; determining the dominant color of each region, wherein the dominant color is a color with a higher proportion in the region, and the dominant color is black or white; determining the first matrix according to the dominant color of each region, wherein the element value of the ith row and jth column position in the first matrix represents the dominant color of the region of the ith row and jth column position corresponding to the image to be detected, i is more than or equal to 1 and less than or equal to N, and j is more than or equal to 1 and less than or equal to N;
the comparison module is used for comparing the first matrix with a second matrix which corresponds to a standard image and is used for representing the color distribution of the standard image, and determining a comparison result, wherein the standard image is a black-and-white image of the surrounding environment where the door is located, the black-and-white image is acquired when the door is in a closed state and no person is outside the door;
and the judging module is used for judging whether the door is in a closed state or not according to the comparison result.
8. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of detecting as claimed in any one of claims 1 to 6.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method of detection according to any one of claims 1 to 6.
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| CN109460771B (en) * | 2018-09-21 | 2021-02-02 | 广州企图腾科技有限公司 | Trademark similarity judging method and device based on sliding window and storage medium |
| CN113177939A (en) * | 2021-05-25 | 2021-07-27 | 浙江大华技术股份有限公司 | Lamp panel detection method and device, electronic equipment and storage medium |
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