CN114881978A - Target detection method, electronic device and intelligent control system - Google Patents
Target detection method, electronic device and intelligent control system Download PDFInfo
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Abstract
The application discloses a target detection method, electronic equipment and an intelligent control system, wherein the electronic equipment can generate a gray image based on infrared image data acquired by an infrared sensor, and process the gray image by adopting a plurality of different gray threshold values so as to obtain a plurality of binary images for detecting the position of a target object. Wherein the plurality of gray level thresholds are determined based on an average of energy values of a plurality of pixels in the infrared image data. Because the energy values of the plurality of pixels are related to the ambient temperature, the interference of the ambient temperature to the binarization processing can be effectively avoided. Furthermore, the temperature of each subarea in the detection area can be accurately reflected by the binary image, and the accuracy of target detection is further ensured.
Description
Technical Field
The present disclosure relates to the field of electronic technologies, and in particular, to a target detection method, an electronic device, and an intelligent control system.
Background
An infrared sensor is widely applied to the field of target detection as a non-contact sensor. For example, in an intelligent home scene, the position of a user can be detected through an infrared sensor, and the working state of home equipment can be adjusted according to the position of the user. For example, the wind direction of the air conditioner may be adjusted.
In the related art, an infrared image captured by an infrared sensor may be converted into a binarized image, and the position of a target object (e.g., a user) may be determined based on the binarized image.
However, the infrared sensor is susceptible to the influence of the ambient temperature when collecting data, so that the accuracy of target detection is poor.
Disclosure of Invention
The application provides a target detection method, electronic equipment and an intelligent control system, which can solve the problem of poor accuracy of target detection in the related art. The technical scheme is as follows:
in one aspect, a target detection method is provided, where the method includes:
acquiring infrared image data of a detection area acquired by an infrared sensor, wherein the infrared image data comprises energy values of a plurality of pixels, the plurality of pixels are in one-to-one correspondence with a plurality of sub-areas of the detection area, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel;
generating a gray image according to the infrared image data;
determining a plurality of gray level threshold values according to the average value of the energy values of the plurality of pixels, wherein the gray level threshold values are different from each other and are positively correlated with the average value of the energy values of the plurality of pixels;
performing binarization processing on the gray level image by respectively adopting each gray level threshold value to obtain a plurality of binarization images;
and determining the position of the target object in the detection area according to the plurality of binary images.
In another aspect, an electronic device is provided that includes an infrared sensor and a processor;
the infrared sensor is used for acquiring infrared image data of a detection area, the infrared image data comprises energy values of a plurality of pixels, the plurality of pixels are in one-to-one correspondence with a plurality of sub-areas of the detection area, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel;
the processor is configured to:
generating a gray image according to the infrared image data;
determining a plurality of gray level threshold values according to the average value of the energy values of the plurality of pixels, wherein the gray level threshold values are different from each other;
performing binarization processing on the gray level image by respectively adopting each gray level threshold value to obtain a plurality of binarization images;
and determining the position of the target object in the detection area according to the plurality of binary images.
Optionally, the processor is configured to:
determining a plurality of energy thresholds according to the mean value of the energy values of the plurality of pixels;
obtaining a plurality of gray level threshold values corresponding to the plurality of energy threshold values according to the conversion relation between the energy values and the gray level values;
wherein each energy threshold satisfies any one of the following conditions:
greater than or equal to the mean value and less than a maximum of the energy values of the plurality of pixels;
is less than the mean value and the difference from the mean value is less than a difference threshold.
Optionally, the number of the plurality of energy thresholds is N, where N is an integer greater than 1;
wherein the ith energy threshold P i Satisfies the following conditions: p i ＝P ave +x i ×(P max -P ave )；
i is a positive integer not greater than N, x i Weight coefficient, P, representing the ith energy threshold max Representing a maximum value, P, of the energy values of the plurality of pixels ave Represents an average of energy values of the plurality of pixels.
Optionally, the processor is configured to:
processing the energy value of each pixel in the infrared image data by adopting the conversion relation between the energy value and the temperature value to obtain temperature image data, wherein the temperature image data comprises the temperature values of a plurality of pixels;
processing the temperature value of each pixel in the temperature image data by adopting the conversion relation between the temperature value and the gray value to obtain a gray image;
wherein the conversion relation between the temperature value and the gray value is determined based on the ambient temperature.
Optionally, the conversion relationship between the temperature value and the gray scale value satisfies:
G＝(T-T min )/(T max -T min )×255；
wherein G represents a gray value, T represents a temperature value, T min Is a first temperature threshold, T max Is a second temperature threshold, and the first temperature threshold and the second temperature threshold are both positively correlated with the ambient temperature.
Optionally, the conversion relationship of the energy value and the temperature value satisfies:
T＝(P-K)/R e +T B ；
wherein T represents a temperature value, P represents an energy value, K represents a reference energy value, R e A conversion coefficient, T, representing an energy value and a temperature value B Representing the temperature of the infrared sensor.
Optionally, the processor is configured to:
generating an initial image according to the infrared image data, wherein the initial image comprises gray values of a plurality of pixels, and the number of the pixels in the initial image is equal to that of the pixels in the infrared image data;
and sequentially filtering and interpolating the initial image to obtain a gray image, wherein the number of pixels in the gray image is greater than that of the pixels in the initial image.
Optionally, the processor is configured to:
determining at least one candidate binary image from the plurality of binary images, wherein the area of a target region in each candidate binary image is larger than an area threshold value, and the target region is a region with a gray value as a target value;
and determining the position of a target object in the target area according to the target area in the at least one candidate binarization image.
In yet another aspect, an electronic device is provided, the electronic device including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the object detection method as described in the above aspect when executing the computer program.
In yet another aspect, a computer-readable storage medium is provided, in which a computer program is stored, the computer program being loaded and executed by a processor to implement the object detection method according to the above aspect.
In a further aspect, there is provided a computer program product comprising instructions which, when run on the computer, cause the computer to perform the object detection method of the above aspect.
In yet another aspect, an intelligent control system is provided, the system comprising: a controlled device, and the electronic device of the above aspect;
the electronic equipment is used for controlling the working state of the controlled equipment according to the position of the target object in the detection area.
The beneficial effect that technical scheme that this application provided brought includes at least:
the application provides a target detection method, electronic equipment and an intelligent control system, wherein the electronic equipment can generate a gray image based on infrared image data acquired by an infrared sensor, and process the gray image by adopting a plurality of different gray threshold values so as to obtain a plurality of binary images for detecting the position of a target object. Wherein the plurality of gray level thresholds are determined based on an average of energy values of a plurality of pixels in the infrared image data. Because the energy values of the plurality of pixels are related to the ambient temperature, the interference of the ambient temperature to the binarization processing can be effectively avoided. Furthermore, the temperature of each subarea in the detection area can be accurately reflected by the binary image, and the accuracy of target detection is further ensured.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an intelligent control system provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of a target detection method according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of another target detection method provided in the embodiments of the present application;
fig. 4 is a schematic diagram of an electronic device that processes an initial image according to an embodiment of the present application;
fig. 5 is a schematic diagram of a plurality of binarized images obtained after a grayscale image binarization process according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
Fig. 1 is a schematic structural diagram of an intelligent control system according to an embodiment of the present application. Referring to fig. 1, the system may include an electronic device 10 and a controlled device 20. A wired or wireless communication connection is established between the electronic device 10 and the controlled device 20.
The electronic device 10 is a device having a target detection function, and the electronic device 10 can adjust the operating state of the controlled device 20 according to the detected position of the target object. The controlled device 20 may be an air conditioner, a lamp, a television, a door lock, a fan, a range hood, or other intelligent home devices, and correspondingly, the intelligent control system may be an intelligent home system. Alternatively, the controlled device 20 may be other types of devices such as an in-vehicle device.
In the embodiment of the present application, the infrared sensor in the electronic device 10 can acquire infrared image data of a detection area thereof, and process the infrared image data to determine whether a target object exists in the detection area.
For example, if the controlled device 20 is an air conditioner, the target object for the electronic device 10 to perform target detection may be a user. When the electronic device 10 determines that the user exists in the detection area thereof based on the infrared image data collected by the infrared sensor, the on-off state, the wind direction, the temperature and the like of the air conditioner may be controlled based on the position of the user in the detection area.
Fig. 2 is a flowchart of an object detection method provided in an embodiment of the present application, where the method may be applied to the electronic device shown in fig. 1. Referring to fig. 2, the method includes the steps of:
In the embodiment of the application, an infrared sensor is arranged in the electronic equipment. The infrared sensor can detect the detection area of the infrared sensor in real time and generate infrared image data of the detection area. The infrared image data comprises energy values of a plurality of pixels, the plurality of pixels correspond to a plurality of sub-areas of the detection area in a one-to-one mode, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel. That is, the energy value of each of the plurality of pixels can reflect the temperature of the corresponding one of the sub-regions, for example, the energy value of each pixel can be positively correlated with the temperature of the sub-region corresponding to the pixel.
And 102, generating a gray image according to the infrared image data.
In the embodiment of the application, the electronic device can convert the energy value of each pixel in the infrared image data into the gray value based on the conversion relationship between the pre-configured energy value and the gray value, so as to obtain the gray image. The grayscale image includes grayscale values for a plurality of pixels.
Optionally, the conversion relationship between the energy value and the gray-scale value may include: the conversion relation between the energy value and the temperature value and the conversion relation between the temperature value and the gray value. Correspondingly, the electronic device may convert the energy values of the plurality of pixels into temperature values, and then convert the temperature values into gray scale values to obtain a gray scale image.
In this embodiment, the electronic device may calculate an average value of energy values of a plurality of pixels in the infrared image data, and determine a plurality of mutually different gray level threshold values based on the average value. Wherein each gray level threshold is positively correlated with the mean of the energy values.
For example, the electronic device may first determine a plurality of mutually different energy thresholds based on an average of the energy values of the plurality of pixels. Then, based on the conversion relationship between the energy value and the gray value, a plurality of gray threshold values corresponding to the plurality of energy threshold values are determined.
And step 104, performing binarization processing on the gray level images by respectively adopting each gray level threshold value to obtain a plurality of binarized images.
Each binarized image in the plurality of binarized images is derived based on a gray scale threshold. In the process of carrying out binarization processing on the gray image by adopting any gray threshold value, the electronic equipment can set the gray value of the pixel of which the gray value is greater than or equal to the gray threshold value in the gray image as a first gray value and set the gray value of the pixel of which the gray value is less than the gray threshold value in the gray image as a second gray value. The first gray scale value may be 255, and the second gray scale value may be 0. Alternatively, the first gray scale value may be 0, and the second gray scale value may be 255.
It is to be understood that, since the plurality of gradation threshold values determined by the electronic device are different from each other, the plurality of binarized images determined based on the plurality of gradation threshold values are also different from each other.
In the embodiment of the present application, the grayscale threshold value used when the electronic device performs binarization processing on the grayscale image is not a fixed value, but is determined based on an average value of a plurality of energy values in the infrared image data, and the plurality of energy values are related to temperature. It can be seen that the gray level thresholds are also related to the ambient temperature of the environment in which the infrared sensor is located. Therefore, the binary processing is carried out on the gray level image based on the plurality of gray level thresholds, and the interference of the external environment temperature to the binary processing can be effectively reduced.
And 105, determining the position of the target object in the detection area according to the plurality of binary images.
The electronic device may determine a target region in each binarized image, where the target region is a region with a gray value as a target value. The target value may be a first gray value. Thereafter, the electronic device may determine the position of the target object within the detection area based on the overlapping area of the target areas in the plurality of binarized images. For example, the electronic device may determine the location of the overlap region as the location of the target object.
It will be appreciated that the temperature of an object (e.g. a user) detected by the electronic device is typically higher than the ambient temperature of the environment in which the object is located. In the conversion relationship between the energy value and the temperature value, the temperature value is positively correlated with the energy value, and in the conversion relationship between the temperature value and the gray value, the gray value is positively correlated with the temperature value. Therefore, the gray value and the energy value are also positively correlated. If an object exists in the detection area of the electronic device, the gray scale value of the area where the object exists is relatively high in the gray scale image generated by the electronic device. Therefore, after converting the grayscale image into a binarized image, a region formed by pixels having a grayscale value equal to the target value in the binarized image can be determined as a target region. The probability that the target object exists in the target area is greater than that of other areas except the target area in the binary image.
It can also be understood that, since the electronic device can determine the plurality of binary images based on different grayscale thresholds and determine the position of the target object based on the overlapping area of the target areas of the plurality of binary images, it can be ensured that the position of the target object determined by the electronic device is more accurate.
In summary, the embodiment of the present application provides a target detection method, in which an electronic device can generate a grayscale image based on infrared image data acquired by an infrared sensor, and process the grayscale image by using a plurality of different grayscale thresholds, so as to obtain a plurality of binary images for detecting a position of a target object. Wherein the plurality of gray level thresholds are determined based on an average of energy values of a plurality of pixels in the infrared image data. Because the energy values of the plurality of pixels are related to the ambient temperature, the interference of the ambient temperature to the binarization processing can be effectively avoided. Furthermore, the temperature of each subarea in the detection area can be accurately reflected by the binary image, and the accuracy of target detection is further ensured.
Fig. 3 is a schematic flowchart of another object detection method provided in an embodiment of the present application, where the method may be applied to the electronic device shown in fig. 1. Referring to fig. 3, the method includes the steps of:
In the embodiment of the application, an infrared sensor is arranged in the electronic equipment. The infrared sensor can detect the detection area of the infrared sensor in real time and generate infrared image data of the detection area. The infrared image data comprises energy values of a plurality of pixels, the plurality of pixels correspond to a plurality of sub-areas of the detection area in a one-to-one mode, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel. That is, the energy value of each of the plurality of pixels can reflect the temperature of the corresponding one of the sub-regions, for example, the energy value of each pixel can be positively correlated with the temperature of the sub-region corresponding to the pixel.
Wherein, this infrared sensor can be infrared thermopile sensor, and this infrared thermopile sensor includes the thermocouple of a plurality of array arrangements, can realize two-dimensional regional temperature detection from this. For example, assuming that the infrared thermopile sensor includes N thermocouple line arrays each including P thermocouples, the N × P thermocouples included in the infrared thermopile sensor may form an area array of P rows and N columns. Wherein N and P are both integers greater than 1. For example, N-80 and P-60. Accordingly, the detection area of the infrared sensor can be divided into N × P sub-areas, each thermocouple corresponds to one sub-area, and the energy value of the corresponding sub-area can be detected. That is, the infrared image data may include energy values of N × P pixels, and the energy value of each pixel is an energy value detected by one thermocouple. In the embodiment of the present application, the energy value detected by each thermocouple may also be referred to as a lumen value, and the value of the lumen value detected by each thermocouple may be a number greater than or equal to 7000 and less than 8500.
Step 202, processing the energy value of each pixel in the infrared image data by adopting the conversion relation between the energy value and the temperature value to obtain temperature image data.
In the embodiment of the application, the electronic device can convert the energy value of each pixel in the infrared image data into the temperature value based on the conversion relationship between the pre-configured energy value and the temperature value, so as to obtain the temperature image data, wherein the temperature image data comprises the temperature values of a plurality of pixels. For example, if the infrared sensor includes 80 × 60 thermocouples, the temperature image data includes temperature values of 80 × 60 pixels. The conversion relation between the energy value and the temperature value can satisfy the following conditions:
T＝(P-K)/R e +T B formula (1)
In formula (1), T represents a temperature value, P represents an energy value, and K represents a preset reference energy value, and a value thereof may be determined based on a performance parameter of the infrared sensor. For example, the reference energy value may be 8191. R e A conversion coefficient between a preset energy value and a temperature value is represented, and the conversion coefficient can be determined based on the performance parameter of the infrared sensor and the ambient temperature of the application scene of the electronic device. The conversion coefficient R e The value of (d) may be 20 or more and less than 60, for example, 30 or more. T is B Representing a reference temperature that is related to the ambient temperature. For example, the reference temperature T B Temperature of substrate which may be an infrared sensorOr may be ambient temperature. In the embodiment of the present application, the temperature of the substrate may be detected by providing a temperature sensor on the substrate.
And 203, processing the temperature value of each pixel in the temperature image data by adopting the conversion relation between the temperature value and the gray value to obtain an initial image.
After obtaining the temperature image, the electronic device may convert the temperature value of each pixel in the temperature image data into a gray value based on a conversion relationship between a preset temperature value and a gray value, thereby obtaining an initial image. The initial image comprises gray values of a plurality of pixels, and the number of the pixels in the initial image is equal to the number of the pixels in the temperature image data. For example, the initial image may comprise a grey value of 80 × 60 pixels.
In the embodiment of the present application, the conversion relationship between the temperature value and the gray scale value may be determined based on the ambient temperature, that is, the conversion relationship between the temperature value and the gray scale value is different at different ambient temperatures. The conversion relation between the temperature value of each pixel in the temperature image data and the gray value of each pixel in the corresponding initial image satisfies the following conditions: :
G＝(T-T min )/(T max -T min ) X255 formula (2)
In formula (2), G represents a gray scale value, and the value thereof may be an integer of 0 or more and 255 or less. T represents a temperature value, T min Is a first temperature threshold, T max Is the second temperature threshold. The second temperature threshold T max Greater than a first temperature threshold T min And the first temperature threshold T min And a second temperature threshold T max Are all positively correlated with ambient temperature. That is, the higher the ambient temperature, the higher the first temperature threshold T min And a second temperature threshold T max The higher.
Optionally, when the minimum value of the temperature values of the plurality of pixels in the temperature image data is smaller than the first temperature value, the first temperature threshold T is set min May be equal to the first temperature value, the second temperature threshold value T max May be a second temperature value that is greater than the first temperature value.When the minimum value of the temperature values of the plurality of pixels in the temperature image data is greater than the second temperature value, the first temperature threshold value T min May be equal to the second temperature value, second temperature threshold T max May be a third temperature value, which is greater than the second temperature value.
For example, the first temperature value may be 20 degrees celsius (° c), the second temperature value may be 32 ℃, and the third temperature value may be 38 ℃.
It is understood that the environment in which the electronic device performs target detection is typically indoors, the temperature value of the environment is typically in a range between 20 ℃ and 30 ℃, and the temperature value of the target (e.g., human) is typically between 35 ℃ and 38 ℃. When a cold airflow exists in the environment, the temperature values of the plurality of pixels in the temperature image data are influenced by the cold airflow and are lower. When there is a hot air flow in the environment, the temperature values of the pixels in the temperature image data are affected by the hot air flow and are higher. Therefore, in converting the temperature values of the plurality of pixels in the temperature image data into the gray values, the first temperature threshold T is determined based on the minimum value of the current ambient temperature min And a second temperature threshold T max The influence of external environmental factors on the conversion process can be effectively reduced.
And step 204, sequentially filtering and interpolating the initial image to obtain a gray image.
In the embodiment of the application, the electronic device may perform filtering processing on the initial image to reduce noise in the initial image. Thereafter, the electronic device may perform interpolation processing on the initial image to enlarge the size of the initial image, resulting in a grayscale image. The number of pixels in the gray image is larger than that of pixels in the initial image.
Optionally, in order to preserve the detail features of the initial image during the filtering process, the electronic device may perform the filtering process on the initial image by using a median filtering method. For example, for the gray value of each pixel, the gray values of the pixels in its 3 × 3 neighborhood may be used for median filtering. For example, referring to fig. 4, (a) in fig. 4 is an initial image obtained based on infrared image data, and (b) in fig. 4 is an initial image after filtering processing.
In order to make the target object more prominent in the initial image, the filtered initial image may be enlarged by using a bicubic interpolation algorithm. Fig. 4 (c) shows a grayscale image obtained after the interpolation processing. For example, for an initial image with a length of 80 pixels and a width of 60 pixels, i.e., an initial image with a resolution of 80 × 60, the resolution is 320 × 240 after being amplified by a factor of 4 by the bicubic interpolation algorithm. It is understood that the larger the size of the initial image is, the larger the number of pixels included in the target object in the initial image is, and the easier it is to perform image processing.
After step 201, the electronic device may calculate an average value of energy values of a plurality of pixels in the infrared image data, and determine a plurality of mutually different energy threshold values based on the average value. Wherein each energy threshold may satisfy any one of the following conditions:
condition 1: greater than or equal to the mean value and less than the maximum value of the energy values of the plurality of pixels;
condition 2: is less than the mean value and the difference from the mean value is less than a difference threshold.
As can be seen from the above condition 1, the electronic device can determine a plurality of energy thresholds different from each other between the average value and the maximum value of the energy values of the plurality of pixels. Assuming that the electronic device determines N energy thresholds, where N is an integer greater than 1, an ith energy threshold P of the N energy thresholds i Satisfies the following conditions:
P i ＝P ave +x i ×(P max -P ave ) Formula (3)
In the above formula (3), i is a positive integer not greater than N, and x i Weight coefficient, P, representing the ith energy threshold max Representing the maximum value of the energy values of a plurality of pixels, P ave Representing the mean of the energy values of a plurality of pixels. Wherein the weighting coefficients of the N energy threshold values are preset N different coefficientsThe energy thresholds determined based on the N weight coefficients are also different from each other. For example, assuming that N is equal to 5, the weighting coefficients of the 5 energy thresholds can refer to table 1.
TABLE 1
| Energy threshold | i＝1 | i＝2 | i＝3 | i＝4 | i＝5 |
| Weight coefficient | 0.8 | 0.6 | 0.4 | 0.2 | 0.1 |
In the above condition 2, the electronic device may determine, from among the energy values having energy values smaller than the mean value, a plurality of energy thresholds having a difference value smaller than the difference threshold from the mean value. The difference threshold is a preset smaller value, so that the determined energy thresholds are close to the average value. For example, the energy threshold may be 200. If the mean of the energy values is 7800, then multiple energy thresholds may be determined between energy values 7600 and 7800.
And step 206, obtaining a plurality of gray level thresholds corresponding to the plurality of energy thresholds according to the conversion relation between the energy values and the gray level values.
In this embodiment, the electronic device may convert the determined multiple energy thresholds into the grayscale thresholds respectively based on a pre-configured conversion relationship between the energy value and the grayscale value. Since the energy thresholds are different from each other, the gray thresholds corresponding to the energy thresholds are also different from each other.
Referring to step 202 and step 203, the conversion relationship between the energy value and the gray-level value may include: the conversion relation between the energy value and the temperature value and the conversion relation between the temperature value and the gray value. Accordingly, the electronic device may convert the plurality of energy thresholds into the temperature threshold, and then convert the temperature threshold into the grayscale threshold. For example, the energy thresholds may be converted into corresponding temperature thresholds according to the above formula (1), and then the temperature thresholds may be converted into corresponding grayscale thresholds according to the formula (2).
And step 207, performing binarization processing on the gray level images by respectively adopting each gray level threshold value to obtain a plurality of binarized images.
Each binarized image in the plurality of binarized images is derived based on a gray scale threshold. In the process of carrying out binarization processing on the gray image by using any gray threshold value, the electronic equipment can set the gray value of the pixel of which the gray value is greater than or equal to the gray threshold value in the gray image as a first gray value and set the gray value of the pixel of which the gray value is less than the gray threshold value in the gray image as a second gray value, so that the binarization image only comprising the first gray value and the second gray value can be obtained. The first gray scale value may be 255, and the second gray scale value may be 0. Alternatively, the first gray scale value may be 0, and the second gray scale value may be 255.
It is understood that, since the plurality of gradation threshold values determined by the electronic device are different from each other, the plurality of binarized images determined based on the plurality of gradation threshold values are also different from each other. Since the grayscale value is positively correlated with the temperature value, the plurality of binarized images can be understood as binarized images at different temperatures.
For example, if 5 grayscale threshold values are determined in step 206, 5 binarized images determined based on the 5 grayscale threshold values may be as shown in (a) to (e) of fig. 5. The gray level threshold corresponding to (a) in fig. 5 is determined based on the energy threshold with the weight coefficient of 0.8, the gray level threshold corresponding to (b) in fig. 5 is determined based on the energy threshold with the weight coefficient of 0.6, the gray level threshold corresponding to (c) in fig. 5 is determined based on the energy threshold with the weight coefficient of 0.4, the gray level threshold corresponding to (d) in fig. 5 is determined based on the energy threshold with the weight coefficient of 0.2, and the gray level threshold corresponding to (e) in fig. 5 is determined based on the energy threshold with the weight coefficient of 0.1.
In the embodiment of the present application, the grayscale threshold used when the electronic device performs binarization processing on the grayscale image is not a fixed value, but is determined based on an average value of a plurality of energy values in the infrared image data, and the plurality of energy values are related to temperature. It can be seen that the gray level thresholds are also related to the ambient temperature of the environment in which the infrared sensor is located. Therefore, the binary processing is carried out on the gray level image based on the plurality of gray level thresholds, and the interference of the external environment temperature to the binary processing can be effectively reduced.
At step 208, at least one candidate binarized image is determined from the plurality of binarized images.
After the electronic device determines the plurality of binary images, a target area can be determined in each binary image, and the target area is an area with a gray value as a target value. After that, the electronic device may determine the binarized image in which the area of the target region is larger than the area threshold value as the candidate binarized image. Wherein the area threshold may be an area value pre-stored in the electronic device, and the target value may be the first gray value.
It will be appreciated that the temperature of an object (e.g. a user) detected by the electronic device is typically higher than the ambient temperature of the environment in which the object is located. In the conversion relationship between the energy value and the temperature value, the temperature value is positively correlated with the energy value, and in the conversion relationship between the temperature value and the gray value, the gray value is positively correlated with the temperature value. Therefore, the gray value and the energy value are also positively correlated. If an object exists in the detection area of the electronic device, the gray scale value of the area where the object exists is relatively high in the gray scale image generated by the electronic device. Therefore, after the grayscale image is converted into a binarized image, the region composed of pixels with the grayscale value of the first grayscale value in the binarized image can be determined as the region where the target object is located, i.e., the target region. The probability that the target object exists in the target area is greater than that of other areas except the target area in the binary image.
For example, if the first grayscale value is 255 and the second grayscale value is 0 in the 5 binarized images shown in fig. 5, the region (i.e., white region) composed of the pixels with grayscale values of 255 in each binarized image is the target region. Referring to fig. 5, it can be seen that, in the binarized image corresponding to the energy threshold with the larger weight coefficient, the smaller the area of the white region, that is, the larger the grayscale threshold, the smaller the area of the target region in the binarized image determined based on the grayscale threshold. Further, 5 white regions in the 5 binarized images have overlapping regions.
It is also understood that when the area of the target region in the binarized image is small, the electronic device may determine that the target object is not present in the detection region corresponding to the binarized image. Therefore, no further processing is required on the binarized image. When the areas of the target areas in the multiple binarized images determined by the electronic device are smaller than the area threshold value, it is determined that no target object exists in the detection area, and the electronic device does not need to process the multiple binarized images.
And 209, determining the position of the target object in the target area according to the target area in the at least one candidate binary image.
In this embodiment, the electronic device may first determine an overlapping region of the target region in the at least one candidate binarized image, and determine the position of the overlapping region as the position of the target object.
Alternatively, the electronic device may determine the intersection ratio of the target region in the at least one candidate binarized image, and determine whether the intersection ratio is greater than a preset ratio (e.g., 0.5). The intersection and union ratio refers to the area ratio of the intersection and the union of the target areas of the alternative binary images. If the intersection ratio is greater than the preset ratio, the electronic device may determine an overlapping region of the target region (i.e., an intersection of the target regions) in the at least one candidate binarized image as the region where the target object is located. Further, the position of the target object can be determined.
If the intersection ratio of the target areas in the at least one candidate binary image is smaller than a preset ratio, the electronic device may determine that an interfering object other than the target object exists in the detection area. In order to accurately determine the position of the target object, the electronic device may process an overlapping region of the target region in the at least one candidate binarized image based on a pre-stored target detection algorithm to determine the position of the target object.
For example, a reference shape is stored in the electronic device in advance, and the reference shape may be determined based on the shape of the object. The electronic device may determine an area of the overlapping area having a shape matching the reference shape as an area where the object is located. Alternatively, the electronic device stores a reference temperature value in advance, and the reference temperature value may be determined based on the temperature of the target object (e.g., the face temperature). The electronic device may determine an area in which the temperature value matches a pre-stored reference temperature value in the overlap area as an area in which the object is located. Or, the electronic device may combine the shape and the temperature, and determine an area in which the shape matches the reference shape and the temperature matches the reference temperature value as the area where the target object is located.
In this embodiment, the electronic device may further control the operating state of the controlled device based on the determined position of the target object. For example, the controlled device may be controlled to turn on, or the orientation of the controlled device may be adjusted.
Optionally, after the electronic device determines the position of the target object, the electronic device may further obtain the temperature of the area corresponding to the position of the target object in the temperature image data (i.e., the temperature of the target object), and then control the operating state of the controlled device based on the temperature of the area.
For example, it is assumed that the controlled device is an air conditioner. The electronic device may control the air conditioner to be switched from the default off state to the on state after detecting that the target object (i.e., the user) exists in the detection area of the electronic device. Alternatively, the electronic device may control the wind direction of the air conditioner to be directed toward the user or to be deviated from the user according to the position of the user. Still alternatively, the electronic device may adjust the temperature of the air conditioner according to the detected temperature of the user. Therefore, the experience effect of the user can be effectively ensured.
In the embodiment of the application, the electronic device can determine a plurality of binary images based on a plurality of different gray threshold values, and determine the position of the target object based on the target area of at least one candidate binary image in the plurality of binary images. Therefore, the determined position of the target object can be ensured to be more accurate.
It should be understood that the order of the steps of the target detection method provided in the embodiments of the present application may be appropriately adjusted. For example, steps 205 and 206 described above may be performed before step 202. Alternatively, step 205 and step 202 may be performed synchronously. Still alternatively, the step 204 may be eliminated as appropriate, i.e., the electronic device does not need to perform filtering processing and interpolation processing on the initial image. Still alternatively, the above step 208 may be deleted as the case may be, i.e., the electronic device may directly determine the position of the target object based on the target area in the plurality of binarized images. Any method that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application is covered by the protection scope of the present application, and thus the detailed description thereof is omitted.
In summary, the embodiment of the present application provides a target detection method, in which an electronic device can generate a grayscale image based on infrared image data acquired by an infrared sensor, and process the grayscale image by using a plurality of different grayscale thresholds, so as to obtain a plurality of binary images for detecting a position of a target object. Wherein the plurality of gray level thresholds are determined based on an average of energy values of a plurality of pixels in the infrared image data. Because the energy values of the plurality of pixels are related to the ambient temperature, the interference of the ambient temperature to the binarization processing can be effectively avoided. Furthermore, the temperature of each subarea in the detection area can be accurately reflected by the binary image, and the accuracy of target detection is further ensured.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 6, the electronic device includes: an infrared sensor 110 and a processor 120.
The infrared sensor 110 is configured to acquire infrared image data of the detection area, where the infrared image data includes energy values of a plurality of pixels, the plurality of pixels are in one-to-one correspondence with a plurality of sub-areas of the detection area, and the energy value of each pixel is related to a temperature of the sub-area corresponding to the pixel.
The processor 120 is configured to:
generating a gray image according to the infrared image data;
determining a plurality of gray level threshold values according to the average value of the energy values of the plurality of pixels, wherein the gray level threshold values are different from each other;
performing binarization processing on the gray level image by adopting each gray level threshold value respectively to obtain a plurality of binarization images;
and determining the position of the target object in the detection area according to the plurality of binary images.
Optionally, the processor 120 is configured to:
determining a plurality of energy thresholds according to the mean value of the energy values of a plurality of pixels;
obtaining a plurality of gray level thresholds corresponding to the plurality of energy thresholds according to the conversion relation between the energy values and the gray level values;
wherein each energy threshold satisfies any one of the following conditions:
greater than or equal to the mean value and less than the maximum value of the energy values of the plurality of pixels;
is less than the mean value and the difference from the mean value is less than a difference threshold.
Optionally, the number of the plurality of energy thresholds is N, where N is an integer greater than 1;
wherein the ith energy threshold P i Satisfies the following conditions:
P i ＝P ave +x i ×(P max -P ave ) Formula (3)
i is a positive integer not greater than N, x i Weight coefficient, P, representing the ith energy threshold max Representing the maximum value of the energy values of a plurality of pixels, P ave Representing the mean of the energy values of a plurality of pixels.
Optionally, the processor 120 is configured to:
processing the energy value of each pixel in the infrared image data by adopting the conversion relation between the energy value and the temperature value to obtain temperature image data, wherein the temperature image data comprises the temperature values of a plurality of pixels;
processing the temperature value of each pixel in the temperature image data by adopting the conversion relation between the temperature value and the gray value to obtain a gray image;
wherein the conversion relation between the temperature value and the gray value is determined based on the ambient temperature.
Optionally, the conversion relationship between the temperature value and the gray value satisfies:
G＝(T-T min )/(T max -T min ) X255 formula (2)
Wherein G represents a gray value, T represents a temperature value, T min Is a first temperature threshold, T max The first temperature threshold and the second temperature threshold are both positively correlated with the ambient temperature.
Optionally, the conversion relationship of the energy value and the temperature value satisfies:
T＝(P-K)/R e +T B formula (1)
Wherein T represents a temperature value, P represents an energy value, K represents a reference energy value, R e A conversion coefficient, T, representing an energy value and a temperature value B Indicating the temperature of the infrared sensor.
Optionally, the processor 120 is configured to:
generating an initial image according to the infrared image data, wherein the initial image comprises gray values of a plurality of pixels, and the number of the pixels in the initial image is equal to that of the pixels in the infrared image data;
and sequentially filtering and interpolating the initial image to obtain a gray image, wherein the number of pixels in the gray image is greater than that of the pixels in the initial image.
Optionally, the processor 120 is configured to:
determining at least one candidate binary image from the multiple binary images, wherein the area of a target region in each candidate binary image is larger than an area threshold value, and the target region is a region with a gray value as a target value;
and determining the position of the target object in the target area according to the target area in the at least one candidate binary image.
In summary, the present application provides an electronic device, which is capable of generating a grayscale image based on infrared image data collected by an infrared sensor, and processing the grayscale image by using a plurality of different grayscale thresholds to obtain a plurality of binary images for detecting a position of a target object. Wherein the plurality of gray level thresholds are determined based on an average of energy values of a plurality of pixels in the infrared image data. Because the energy values of the plurality of pixels are related to the ambient temperature, the interference of the ambient temperature to the binarization processing can be effectively avoided. Furthermore, the temperature of each subarea in the detection area can be accurately reflected by the binary image, and the accuracy of target detection is further ensured.
It is to be understood that the electronic device provided in the foregoing embodiment is only illustrated by the division of the functional modules, and in practical applications, the above functions may be distributed by different functional modules according to needs, that is, the internal structure of the electronic device is divided into different functional modules to complete all or part of the functions described above.
In addition, the electronic device and the target detection method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are referred to as method embodiments and are not described herein again.
An embodiment of the present application provides an electronic device, which includes: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the object detection method provided by the above embodiments when executing the computer program, such as the method shown in fig. 2 or fig. 3.
The embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored, and the computer program is loaded and executed by a processor to implement the object detection method provided in the above embodiment, for example, the method shown in fig. 2 or fig. 3.
Embodiments of the present application further provide a computer program product containing instructions, which when run on the computer, cause the computer to execute the object detection method provided by the above embodiments, for example, the method shown in fig. 2 or fig. 3.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
It is to be understood that the term "at least one" in this application means one or more, and the term "plurality" in this application means two or more.
The terms "first," "second," and the like in this application are used for distinguishing between similar items and items that have substantially the same function or similar functionality, and it should be understood that "first," "second," and "nth" do not have any logical or temporal dependency or limitation on the number or order of execution.
The above description is only exemplary of the present application and should not be taken as limiting the present application, and any modifications, equivalents, improvements and the like that are made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of object detection, the method comprising:
acquiring infrared image data of a detection area acquired by an infrared sensor, wherein the infrared image data comprises energy values of a plurality of pixels, the plurality of pixels are in one-to-one correspondence with a plurality of sub-areas of the detection area, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel;
generating a gray image according to the infrared image data;
determining a plurality of gray level threshold values according to the average value of the energy values of the plurality of pixels, wherein the gray level threshold values are different from each other and are positively correlated with the average value of the energy values of the plurality of pixels;
performing binarization processing on the gray level image by respectively adopting each gray level threshold value to obtain a plurality of binarization images;
and determining the position of the target object in the detection area according to the plurality of binary images.
2. The method of claim 1, wherein determining a plurality of gray scale thresholds from the mean of the energy values of the plurality of pixels comprises:
determining a plurality of energy thresholds according to the mean value of the energy values of the plurality of pixels;
obtaining a plurality of gray level threshold values corresponding to the plurality of energy threshold values according to the conversion relation between the energy values and the gray level values;
wherein each energy threshold satisfies any one of the following conditions:
greater than or equal to the mean value and less than a maximum of the energy values of the plurality of pixels;
is less than the mean value and the difference from the mean value is less than a difference threshold.
3. The method of claim 2, wherein the plurality of energy thresholds is N, where N is an integer greater than 1;
wherein the ith energy threshold P i Satisfies the following conditions: p i ＝P ave +x i ×(P max -P ave )；
i is a positive integer not greater than N, x i Weight coefficient, P, representing the ith energy threshold max Energy representing the plurality of pixelsMaximum value of magnitude, P ave Represents an average of energy values of the plurality of pixels.
4. The method of any of claims 1 to 3, wherein said generating a gray scale image from said infrared image data comprises:
processing the energy value of each pixel in the infrared image data by adopting the conversion relation between the energy value and the temperature value to obtain temperature image data, wherein the temperature image data comprises the temperature values of a plurality of pixels;
processing the temperature value of each pixel in the temperature image data by adopting the conversion relation between the temperature value and the gray value to obtain a gray image;
wherein the conversion relation between the temperature value and the gray value is determined based on the ambient temperature.
5. The method of claim 4, wherein the conversion relationship between the temperature value and the gray-scale value satisfies:
G＝(T-T min )/(T max -T min )×255；
wherein G represents a gray value, T represents a temperature value, T min Is a first temperature threshold, T max Is a second temperature threshold, and the first temperature threshold and the second temperature threshold are both positively correlated with the ambient temperature.
6. The method of claim 4, wherein the energy value to temperature value conversion relationship satisfies:
T＝(P-K)/R e +T B ；
wherein T represents a temperature value, P represents an energy value, K represents a reference energy value, R e A conversion coefficient, T, representing an energy value and a temperature value B Representing the temperature of the infrared sensor.
7. The method of any of claims 1 to 3, wherein generating a grayscale image from the infrared image data comprises:
generating an initial image according to the infrared image data, wherein the initial image comprises gray values of a plurality of pixels, and the number of the pixels in the initial image is equal to that of the pixels in the infrared image data;
and sequentially filtering and interpolating the initial image to obtain a gray image, wherein the number of pixels in the gray image is greater than that of the pixels in the initial image.
8. The method according to any one of claims 1 to 3, wherein said determining a position of a target object within said target area from said plurality of binarized images comprises:
determining at least one candidate binary image from the plurality of binary images, wherein the area of a target region in each candidate binary image is larger than an area threshold value, and the target region is a region with a gray value as a target value;
and determining the position of a target object in the target area according to the target area in the at least one candidate binarization image.
9. An electronic device, comprising an infrared sensor and a processor;
the infrared sensor is used for acquiring infrared image data of a detection area, the infrared image data comprises energy values of a plurality of pixels, the plurality of pixels are in one-to-one correspondence with a plurality of sub-areas of the detection area, and the energy value of each pixel is related to the temperature of the sub-area corresponding to the pixel;
the processor is configured to:
generating a gray image according to the infrared image data;
determining a plurality of gray level threshold values according to the average value of the energy values of the plurality of pixels, wherein the gray level threshold values are different from each other;
performing binarization processing on the gray level image by respectively adopting each gray level threshold value to obtain a plurality of binarization images;
and determining the position of the target object in the detection area according to the plurality of binary images.
10. An intelligent control system, the system comprising: a controlled device, and an electronic device as claimed in claim 9;
the electronic equipment is used for controlling the working state of the controlled equipment according to the position of the target object in the detection area.
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