CN117806382A - Intelligent wardrobe dehumidification equipment based on air conditioning - Google Patents
Intelligent wardrobe dehumidification equipment based on air conditioning Download PDFInfo
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- 238000007791 dehumidification Methods 0.000 title claims abstract description 40
- 238000004378 air conditioning Methods 0.000 title claims abstract description 16
- 238000007405 data analysis Methods 0.000 claims abstract description 20
- 238000009825 accumulation Methods 0.000 claims description 19
- 238000003708 edge detection Methods 0.000 claims description 16
- 238000010606 normalization Methods 0.000 claims description 10
- 238000012216 screening Methods 0.000 claims description 7
- 238000001035 drying Methods 0.000 claims 10
- 230000000694 effects Effects 0.000 abstract description 14
- 238000004458 analytical method Methods 0.000 abstract description 9
- 230000000007 visual effect Effects 0.000 abstract description 8
- 238000000034 method Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 3
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- 230000000737 periodic effect Effects 0.000 description 2
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Abstract
The invention relates to the technical field of air conditioning and air dehumidification, in particular to intelligent wardrobe dehumidification equipment based on air conditioning, which comprises a clothes airing rod, clothes hangers, a dehumidifier, a camera device and a data analysis module, wherein the clothes hangers are hung on the clothes airing rod, the dehumidifier is used for periodically running to dehumidify the interior of an intelligent wardrobe, the camera device is arranged above the clothes airing rod and is used for shooting overlook images of the clothes airing rod and inputting the overlook images into the data analysis module, and the data analysis module determines the linear characteristic coefficient and the gray characteristic coefficient of each edge line according to the number and the distribution of the clothes hangers in the overlook images, so that the clothes stacking degree in the intelligent wardrobe is obtained through analysis, and the dehumidifier is convenient to dehumidify the intelligent wardrobe according to the clothes stacking degree auxiliary control; the intelligent wardrobe dehumidification control system can provide an effective visual scheme for adjustment of dehumidification strategies, improve stability and reliability of intelligent wardrobe dehumidification control, and enhance dehumidification effect of the intelligent wardrobe.
Description
Technical Field
The invention relates to the technical field of air conditioning and air dehumidification, in particular to intelligent wardrobe dehumidification equipment based on air conditioning.
Background
The clothes in the intelligent wardrobe generally have larger humidity due to accumulation effect, and the damage of the larger humidity to the clothes is serious, so that the clothes in the intelligent wardrobe need to be dehumidified by air conditioning.
In the related art, through setting up fixed dehumidifier, the periodic operation is in order to realize the dehumidification effect to the air conditioning of intelligent wardrobe interior clothing, under this kind of mode, because the quantity of piling up clothing in the intelligent wardrobe is different, and intelligent wardrobe underwear thing piles up the condition different promptly, therefore, simple periodic operation dehumidifier makes dehumidification control's stability and reliability not enough easily, and intelligent wardrobe's dehumidification effect is relatively poor.
Disclosure of Invention
In order to solve the technical problems that the stability and the reliability of dehumidification control are insufficient due to the fact that the characteristics of clothes piled in the intelligent wardrobe are not considered in the related art, and the dehumidification effect of the intelligent wardrobe is poor, the invention provides intelligent wardrobe dehumidification equipment based on air conditioning, and the adopted technical scheme is as follows:
the invention provides intelligent wardrobe dehumidification equipment based on air conditioning, which comprises a clothes hanger 1, clothes hangers 2, a dehumidifier 3, a camera device 4 and a data analysis module 5, wherein the clothes hangers 2 are hung on the clothes hanger 1, the dehumidifier 3 is used for periodically running to dehumidify the inside of the intelligent wardrobe, the camera device 4 is arranged above the clothes hanger 1 and is used for shooting overlook images of the clothes hanger 1 and inputting the overlook images into the data analysis module 5, and the data analysis module 5 is used for assisting in controlling the dehumidifier 3 to dehumidify the intelligent wardrobe according to the quantity and the distribution of the clothes hangers 2 in the overlook images;
wherein, according to overlook in the image quantity and the distribution of clothes hanger that dries in air, auxiliary control the dehumidifier carries out dehumidification processing to intelligent wardrobe, include:
acquiring a gray level image of the overlook image, carrying out edge detection on the gray level image, determining edge lines which intersect the clothes-horse and have different directions in the gray level image, and determining a linear characteristic coefficient of each edge line according to the distribution of all pixel points on each edge line;
according to the gray values of the pixel points on each edge line and other pixel points in a preset neighborhood range, determining gray characteristic coefficients of the edge lines, screening target edge lines from the edge lines according to the linear characteristic coefficients and the gray characteristic coefficients, and determining distribution characteristic coefficients of the clothes hangers on the clothes airing rod according to the distances between different target edge lines;
according to the number of the target edge lines and the distribution characteristic coefficients of the clothes hangers, determining the clothes stacking degree in the intelligent wardrobe, and adjusting the dehumidification strategy of the dehumidifier on the intelligent wardrobe according to the clothes stacking degree.
Further, the determining the linear characteristic coefficient of each edge line according to the distribution of all the pixel points on each edge line includes:
performing straight line fitting on all pixel points on any edge line to obtain a fitting straight line of the edge line;
and determining the linear characteristic coefficient of the edge line according to the distance between the fitting straight line and all the pixel points on the edge line.
Further, the determining the linear characteristic coefficient of the edge line according to the distance between the fitting straight line and all the pixel points on the edge line includes:
and calculating Euclidean distances between all pixel points on the edge line and the fitting straight line as fitting distances, and taking a normalized value of the mean value of the fitting distances as a straight line characteristic coefficient of the edge line.
Further, the determining the gray characteristic coefficient of the edge line according to the gray values of the pixel point on each edge line and other pixels in the preset neighborhood range includes:
calculating the sum of the absolute values of the gray value difference values of each pixel point on any edge line and other pixels in a preset neighborhood range, and normalizing the sum to obtain an edge gray difference coefficient;
and calculating the normalized value of the average value of the edge gray scale difference coefficients of all pixel points on each edge line as the gray scale characteristic coefficient of the edge line.
Further, the screening the target edge line from the edge line according to the linear characteristic coefficient and the gray characteristic coefficient includes:
calculating a product normalization value of the linear characteristic coefficient and the gray characteristic coefficient as an edge judgment index;
judging whether the edge judging index meets a preset condition or not;
taking the edge line of which the edge judgment index meets a preset condition as a target edge line;
and taking the edge line of which the edge judgment index does not meet a preset condition as a noise edge line.
Further, the determining whether the edge determination index meets a preset condition includes:
when the edge judgment index is larger than a preset index threshold, determining that the edge judgment index meets a preset condition;
and when the edge judgment index is smaller than or equal to a preset index threshold, determining that the edge judgment index does not meet a preset condition.
Further, the determining the distribution characteristic coefficient of the clothes hanger on the clothes hanger according to the distances between different target edge lines includes:
calculating Euclidean distance between midpoints of two adjacent target edge lines as edge distance, and taking edge distance which is larger than a preset distance threshold value in all the edge distances as effective distance; and taking the average value of all the effective distances as a distribution characteristic coefficient.
Further, the determining the clothes stacking degree in the intelligent wardrobe according to the number of the target edge lines and the distribution characteristic coefficients of the clothes hangers comprises the following steps:
calculating the normalized value of the number of all the target edge lines as a number characteristic coefficient;
and calculating the product of the quantity characteristic coefficient and the distribution characteristic coefficient as the clothes accumulation degree.
Further, the adjusting the dehumidification strategy of the dehumidifier to the intelligent wardrobe according to the clothes accumulation degree comprises:
and when the clothes accumulation degree is larger than a preset accumulation degree threshold value, reducing the running interval time of the dehumidifier.
Further, the edge detection for the gray level image, determining the edge line intersecting the clothes-horse and having different directions in the gray level image, includes:
and carrying out edge detection processing on the gray level image based on a Canny edge detection operator, and determining edge lines which intersect the clothes-horse and have different directions in the gray level image.
The invention has the following beneficial effects:
according to the intelligent clothes hanger, the image in the intelligent clothes hanger is acquired based on the image pick-up device and the data analysis module, then the number and distribution of the clothes hangers on the clothes hanger in the image are identified and analyzed, and the auxiliary control dehumidifier is used for dehumidifying the intelligent clothes hanger. The linear characteristic coefficient of each edge line is determined through the distribution of all pixel points on the edge line of the gray level image, the linear characteristic coefficient can represent the linear degree of the edge line, the gray level characteristic coefficient of the edge line is determined through the gray values of the pixel points on the edge line and other pixel points in a preset neighborhood range, the linear characteristic coefficient and the gray level characteristic coefficient are characteristic parameters of a clothes hanger hung on a clothes hanger in the gray level image, the form and the gray level characteristic of the clothes hanger can be effectively represented, the linear characteristic coefficient and the gray level characteristic coefficient are combined to determine the target edge line, namely, the edge line which is more in line with the clothes hanger is selected as the target edge line, the quantity and the distribution of the clothes hangers are accurately represented through the distribution and the quantity of all the target edge lines, the clothes stacking degree in the intelligent wardrobe is conveniently determined, the visual detection effect of the clothes stacking degree is improved, an effective visual scheme is provided for the adjustment of a follow-up dehumidification strategy, the stability and the reliability of dehumidification control of the intelligent wardrobe are improved, and the dehumidification effect of the intelligent wardrobe is enhanced.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an intelligent wardrobe dehumidification device based on air conditioning according to an embodiment of the present invention;
fig. 2 is a schematic top view of an embodiment of the present invention.
The reference numerals in fig. 1 are: 1. a clothes airing rod; 2. a clothes hanger; 3. a dehumidifier; 4. an image pickup device; 5. and a data analysis module.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of the specific implementation, structure, characteristics and effects of the intelligent wardrobe dehumidification device based on air conditioning according to the invention with reference to the attached drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a specific scheme of intelligent wardrobe dehumidification equipment based on air conditioning, which is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a structure diagram of an intelligent wardrobe dehumidifying apparatus based on air conditioning according to an embodiment of the present invention is shown, including a clothes hanger 1, a clothes hanger 2, a dehumidifier 3, a camera device 4 and a data analysis module 5, wherein the clothes hanger 2 is suspended on the clothes hanger 1, the dehumidifier 3 is used for periodically running to dehumidify the interior of the intelligent wardrobe, the camera device 4 is disposed above the clothes hanger 1, and is used for capturing a top view image of the clothes hanger 1, inputting the top view image into the data analysis module 5, and the data analysis module 5 assists in controlling the dehumidifier 3 to dehumidify the intelligent wardrobe according to the number and distribution of the clothes hangers 2 in the top view image.
It can be appreciated that the image capturing device 4 may be, for example, a camera, and in this embodiment of the present invention, the camera may be controlled to be suspended directly above the clothes-horse for capturing a top view image of the clothes-horse in the intelligent wardrobe, as shown in fig. 2, and fig. 2 is a schematic diagram of the top view image provided by one embodiment of the present invention.
The data analysis module 5 may be, for example, a central processing unit capable of performing data analysis and calculation, and is not limited thereto. The data analysis module 5 in the embodiment of the invention can be connected with the image pickup device 4 in a wired or wireless manner, so that the image pickup device 4 can input the overlook image into the data analysis module 5, and then the data analysis module 5 identifies and analyzes the number and distribution of the clothes hangers in the overlook image, so that the approximate number of clothes put on the intelligent wardrobe, namely the clothes accumulation condition, is determined, and the dehumidifier 3 in the scene is controlled according to the clothes accumulation condition.
Wherein, according to the quantity and the distribution of clothes hanger that dries in air in overlook image, auxiliary control dehumidifier carries out dehumidification processing to intelligent wardrobe, includes:
s101: acquiring a gray level image of the overlook image, carrying out edge detection on the gray level image, determining edge lines intersecting with the clothes airing rod in the gray level image and having different directions, and determining the linear characteristic coefficient of each edge line according to the distribution of all pixel points on each edge line.
In the embodiment of the present invention, the top view image may be specifically, for example, an average gray scale process, which is not limited thereto.
Further, in some embodiments of the present invention, edge detection is performed on a gray image, and determining edge lines intersecting a clothes-horse and having different directions in the gray image includes: and carrying out edge detection processing on the gray level image based on the Canny edge detection operator, and determining edge lines which intersect with the clothes-horse and have different directions in the gray level image.
That is, the gray image is edge-detected by the Canny edge detection operator, however, in other embodiments of the present invention, a variety of edge detection methods, such as, for example, a Sobel edge detection operator, may be used to implement edge detection, which is not limited.
In the embodiment of the invention, the clothes airing rod is in a straight rod shape in the gray level image, and the hanger of the clothes airing rack is arranged on the clothes airing rod, so that the edge lines of the clothes airing rack are intersected with the clothes airing rod and the directions of the edge lines are inconsistent, therefore, the edge lines intersected with the clothes airing rod and different in directions in the gray level image are used as the edge lines corresponding to the clothes airing rack, and the fact that the corresponding edge lines are partially the edge lines generated by the influence of the clothes when the clothes are arranged on the clothes airing rack is required to be screened out. Since the edges of the laundry rack are typically straight edges, the present invention detects straight line characteristics.
Further, in some embodiments of the present invention, determining the straight line feature coefficient of each edge line according to the distribution of all pixel points on each edge line includes: performing straight line fitting on all pixel points on any edge line to obtain a fitting straight line of the edge line; and determining the linear characteristic coefficient of the edge line according to the distance between the fitting line and all the pixel points on the edge line.
In the embodiment of the invention, the least square method can be used for carrying out straight line fitting, or other straight line fitting modes can be used, and after straight line fitting, the fitting straight line of each edge line is obtained.
It can be understood that due to various objective factors such as perspective relation and light during shooting, the edges of the corresponding clothes hangers may generate corresponding distortion, but the clothes parts are more flexible due to softness, so that the method is used for representing the linear characteristics of the edge lines by means of linear fitting to obtain fitting lines.
Further, in some embodiments of the present invention, determining the linear feature coefficient of the edge line according to the distance between the fitting line and all the pixel points on the edge line includes: and calculating Euclidean distances between all pixel points on the edge line and the fitting straight line as fitting distances, and taking a normalized value of the mean value of the fitting distances as a straight line characteristic coefficient of the edge line.
It is understood that when the edge line presents a straight line characteristic, the corresponding edge line coincides with the fitted straight line, and when the difference between the edge line and the fitted straight line is large, the more likely the corresponding edge line is a curved line segment. Therefore, the Euclidean distance between all pixel points on the edge line and the fitting straight line is calculated, the fitting distance is obtained, and the larger the fitting distance is, the larger the interval between the corresponding pixel points on the edge line and the fitting straight line is, namely the larger the interval between the edge line and the fitting straight line is. In the embodiment of the invention, the average value of all fitting distances is calculated for normalization processing, and a normalization value is obtained as a linear characteristic coefficient of an edge line.
In one embodiment of the present invention, the normalization process may specifically be, for example, maximum and minimum normalization processes, and the normalization in the subsequent steps may be performed by using the maximum and minimum normalization processes, and in other embodiments of the present invention, other normalization methods may be selected according to a specific range of values, which will not be described herein.
In the embodiment of the invention, after the straight line characteristics are determined, specific analysis is needed for the gray level characteristics, and the analysis process is described in the subsequent embodiment.
S102: according to the gray values of the pixel points on each edge line and other pixel points in a preset neighborhood range, determining gray characteristic coefficients of the edge lines, screening target edge lines from the edge lines according to the linear characteristic coefficients and the gray characteristic coefficients, and determining distribution characteristic coefficients of the clothes hangers on the clothes airing rod according to the distances between different target edge lines.
Further, in some embodiments of the present invention, determining the gray characteristic coefficient of the edge line according to the gray values of the pixel point on each edge line and other pixels in the preset neighborhood range includes: calculating the sum of the absolute values of the gray value difference values of each pixel point on any edge line and other pixel points in a preset neighborhood range, and normalizing the sum to obtain an edge gray difference coefficient; and calculating the normalized value of the average value of the edge gray scale difference coefficients of all pixel points on each edge line as the gray scale characteristic coefficient of the edge line.
It can be understood that a certain interference texture is generated on a clothes rod in an image, and part of texture influence is also generated on clothes, so that the clothes are misjudged as an edge line, when a clothes hanger is hung on the clothes rod, the corresponding gray level difference is generated on the edges of the corresponding clothes rod and the clothes hanger due to the height difference, and the gray level difference is more obvious compared with the interference noise texture of the clothes rod and the texture on the clothes, therefore, the embodiment of the invention carries out specific analysis according to the gray level characteristics of the pixel points on the edge line in the neighborhood of the pixel points.
In the embodiment of the invention, the preset neighborhood range can be specifically a neighborhood range with the size of 3×3, for example, the embodiment of the invention obtains the edge gray scale difference coefficient by calculating the gray scale value difference absolute value of the pixel point and other pixel points in the 3×3 pixel point and normalizing the sum value of the gray scale value difference absolute value, and calculates the normalized value of the average value of the edge gray scale difference coefficients of all pixel points on each edge line as the gray scale characteristic coefficient of the edge line, that is, the larger the gray scale characteristic coefficient is, the larger the gray scale difference of the pixel points on the edge line in the neighborhood range around the pixel points is, the more obvious the texture of the edge line is, thereby conforming to the texture of the clothes hanger hung on the clothes hanger.
Further, in some embodiments of the present invention, screening the target edge line from the edge line according to the linear characteristic coefficient and the gray characteristic coefficient includes: calculating a product normalization value of the linear characteristic coefficient and the gray characteristic coefficient as an edge judgment index; judging whether the edge judging index meets a preset condition or not; taking an edge line with the edge judgment index meeting a preset condition as a target edge line; and taking the edge line of which the edge judgment index does not meet the preset condition as a noise edge line.
In the embodiment of the invention, as the linear characteristic coefficient is larger, the corresponding edge line is represented to be straighter, the corresponding edge line is more consistent with the morphological characteristics of the hanger hook, and the gray characteristic coefficient is larger, the gray difference between the represented edge line and the periphery thereof is larger, namely, the edge line is more obvious in texture, and the texture of the hanger hung on the hanger is more consistent with the texture of the hanger, the product of the linear characteristic coefficient and the gray characteristic coefficient is calculated, and the product is normalized to obtain the edge judgment index, and the edge judgment index is larger, so that the edge line is more likely to be the texture line corresponding to the edge of the hanger.
In the embodiment of the invention, the preset condition can be set, and then whether the edge judgment index meets the preset condition is judged; when the edge judgment index meets the preset condition, the corresponding edge line is taken as a target edge line, and the edge line of which the edge judgment index does not meet the preset condition is taken as a noise edge line.
The target edge line, namely the edge line corresponding to the clothes hanger, and the noise edge line is the edge line generated by the texture of the clothes hanger, the interference texture of the clothes and the like.
Further, in some embodiments of the present invention, determining whether the edge determination index meets a preset condition includes: when the edge judgment index is larger than a preset index threshold, determining that the edge judgment index meets a preset condition; and when the edge judgment index is smaller than or equal to a preset index threshold, determining that the edge judgment index does not meet a preset condition.
In the embodiment of the present invention, the preset index threshold may specifically be, for example, 0.8, that is, when the edge determination index is greater than 0.8, it is determined that the edge determination index meets the preset condition; when the edge determination index is less than or equal to 0.8, it is determined that the edge determination index does not meet the preset condition, however, in other embodiments of the present invention, the preset index threshold may be adjusted according to the actual analysis requirement, which is not limited.
Further, in other embodiments of the present invention, determining a distribution characteristic of a laundry rack on a laundry rack according to distances between different target edge lines includes: calculating Euclidean distance between midpoints of two adjacent target edge lines as edge distance, and taking edge distance which is larger than a preset distance threshold value in all the edge distances as effective distance; and taking the average value of all the effective distances as a distribution characteristic coefficient.
In the embodiment of the invention, after the target edge lines corresponding to the hanger hooks of the clothes hangers are obtained through screening, the distribution of the clothes hangers can be analyzed according to the distribution among the target edge lines, and it can be understood that the more sparse the distribution of the clothes hangers is, the more likely the corresponding clothes hangers are to be large-sized and large-sized clothes, and the more concentrated the distribution of the clothes hangers is, the more likely the clothes hangers are to be small-sized and even empty clothes, so that the embodiment of the invention calculates Euclidean distance between midpoints of two adjacent target edge lines as the edge distance, and takes the edge distance which is larger than the preset distance threshold value in all the edge distances as the effective distance.
In the embodiment of the present invention, the preset distance threshold may be set to 0.8, that is, when the edge distance is greater than 0.8, the corresponding edge distance is an effective distance, and of course, in other embodiments of the present invention, the preset distance threshold may be adjusted according to the actual situation, which is not limited.
It should be noted that, the electric pushing device is arranged on the clothes airing rod in the embodiment of the invention, and can draw all clothes hangers hung on the clothes airing rod together along one side, that is, the electric pushing device has the function of timing processing the clothes hangers, and the electric pushing device on the clothes airing rod can carry out electric arrangement on the clothes hangers periodically, or can trigger the electric pushing device to operate after the clothes cabinet is closed, so that the clothes hangers are closed as much as possible and gathered together. The invention can analyze the distribution of the clothes hangers on the clothes poles based on the characteristics.
In the embodiment of the invention, the effective distance represents the objectivity distance of the clothes interval, and it can be understood that the clothes airing rod may be provided with an empty clothes hanger, and under normal conditions, the empty clothes hanger can be closely abutted against other clothes hangers after electric arrangement, namely, the edge distances of the two corresponding clothes hangers are smaller, so that the influence of the empty clothes hanger is removed by setting a preset distance threshold value, and the reliability and objectivity of subsequent clothes analysis are improved.
The distribution characteristic coefficient is determined through the average value of the effective distance, the distribution of the clothes hangers is determined according to the distribution characteristic coefficient, when the distribution characteristic coefficient is larger, the distribution of the corresponding clothes hangers is sparse, namely, the possibility that clothes put on the clothes hangers are large and occupy large clothes is larger, and when the distribution characteristic coefficient is smaller, the distribution of the corresponding clothes hangers is concentrated, namely, the possibility that clothes put on the small clothes is larger, so that the volume of clothes put on the intelligent wardrobe can be judged, and the carrying condition of the clothes in the intelligent wardrobe can be truly and effectively reflected in visual directions.
S103: according to the number of the target edge lines and the distribution characteristic coefficients of the clothes hangers, determining the clothes stacking degree in the intelligent wardrobe, and adjusting a dehumidification strategy of the dehumidifier to the intelligent wardrobe according to the clothes stacking degree.
Further, in some embodiments of the present invention, determining the laundry stacking degree in the intelligent wardrobe according to the number of target edge lines and the distribution characteristic coefficient of the laundry rack includes: calculating the normalized value of the number of all the target edge lines as a number characteristic coefficient; the product of the number characteristic coefficient and the distribution characteristic coefficient is calculated as the laundry accumulation degree.
The more target edge lines are, the more clothes hangers for carrying clothes in the corresponding intelligent wardrobe can be represented, and therefore, the normalized value of the number of all the target edge lines is calculated to be used as a number characteristic coefficient. The larger the number characteristic coefficient is, the more the number of the underwear of the corresponding intelligent wardrobe is represented.
In the embodiment of the invention, the product of the quantity characteristic coefficient and the distribution characteristic coefficient is calculated to be used as the clothes stacking degree, and the larger the quantity characteristic coefficient is, the larger the quantity of the corresponding intelligent wardrobe underwear is, the larger the distribution characteristic coefficient is, the larger the volume of the clothes stacked in the intelligent wardrobe is, and the more the distribution is dispersed, the larger the corresponding clothes stacking degree is.
The clothes stacking degree in the embodiment of the invention is the stacking effect of clothes in the intelligent wardrobe, and it can be understood that the clothes stacking degree analysis is performed based on the visual angle, and in other embodiments of the invention, multiple data acquisition means such as visual information, a pressure sensor, three-dimensional space analysis and the like can be combined to realize the multi-data auxiliary analysis of the clothes stacking of the intelligent wardrobe, so that more accurate and effective clothes stacking data can be obtained.
Further, in some embodiments of the present invention, a dehumidifying strategy of the intelligent wardrobe by the dehumidifier is adjusted according to the laundry accumulation degree, comprising: and when the clothes accumulation degree is larger than a preset accumulation degree threshold value, reducing the running interval time of the dehumidifier.
The preset stacking degree threshold is a threshold of the stacking degree of the clothes, and in the embodiment of the invention, the preset stacking degree threshold may be specifically, for example, 0.5, that is, when the stacking degree of the clothes is greater than 0.5, the dehumidifier is controlled to reduce the running interval time. That is, when detecting that the degree of clothes accumulation is great, through reducing the operation interval time of dehumidifier to promote the operating frequency of dehumidifier, strengthen the operation effect of dehumidifier itself, promote the dehumidification efficiency of intelligent wardrobe interior clothing.
Of course, in other embodiments of the present invention, the operation power of the dehumidifier itself may be controlled according to the magnitude of the laundry accumulation degree, that is, when the magnitude of the laundry accumulation degree is greater, the operation power of the corresponding dehumidifier is greater, for example, the rotation speed of the dehumidifier is increased, the operation number of the dehumidifier is increased, so as to achieve the dehumidification effect.
According to the intelligent clothes hanger, the image in the intelligent clothes hanger is acquired based on the image pick-up device and the data analysis module, then the number and distribution of the clothes hangers on the clothes hanger in the image are identified and analyzed, and the auxiliary control dehumidifier is used for dehumidifying the intelligent clothes hanger. The linear characteristic coefficient of each edge line is determined through the distribution of all pixel points on the edge line of the gray level image, the linear characteristic coefficient can represent the linear degree of the edge line, the gray level characteristic coefficient of the edge line is determined through the gray values of the pixel points on the edge line and other pixel points in a preset neighborhood range, the linear characteristic coefficient and the gray level characteristic coefficient are characteristic parameters of a clothes hanger hung on a clothes hanger in the gray level image, the form and the gray level characteristic of the clothes hanger can be effectively represented, the linear characteristic coefficient and the gray level characteristic coefficient are combined to determine the target edge line, namely, the edge line which is more in line with the clothes hanger is selected as the target edge line, the quantity and the distribution of the clothes hangers are accurately represented through the distribution and the quantity of all the target edge lines, the clothes stacking degree in the intelligent wardrobe is conveniently determined, the visual detection effect of the clothes stacking degree is improved, an effective visual scheme is provided for the adjustment of a follow-up dehumidification strategy, the stability and the reliability of dehumidification control of the intelligent wardrobe are improved, and the dehumidification effect of the intelligent wardrobe is enhanced.
Claims (10)
1. The intelligent wardrobe dehumidification equipment based on air conditioning comprises a clothes drying rod (1), clothes drying racks (2), a dehumidifier (3), a camera device (4) and a data analysis module (5), and is characterized in that the clothes drying racks (2) are hung on the clothes drying rods (1), the dehumidifier (3) is used for periodically running to dehumidify the inside of the intelligent wardrobe, the camera device (4) is arranged above the clothes drying rods (1) and is used for shooting overlook images of the clothes drying rods (1) and inputting the overlook images into the data analysis module (5), and the data analysis module (5) is used for assisting in controlling the dehumidifier (3) to dehumidify the intelligent wardrobe according to the quantity and the distribution of the clothes drying racks (2) in the overlook images, and the clothes drying rods (1) are provided with electric pushing devices which can draw all the clothes drying racks (2) hung on the clothes drying rods (1) close to one side;
wherein, according to overlook in the image quantity and the distribution of clothes hanger that dries in air, auxiliary control the dehumidifier carries out dehumidification processing to intelligent wardrobe, include:
acquiring a gray level image of the overlook image, carrying out edge detection on the gray level image, determining edge lines which intersect the clothes-horse and have different directions in the gray level image, and determining a linear characteristic coefficient of each edge line according to the distribution of all pixel points on each edge line;
according to the gray values of the pixel points on each edge line and other pixel points in a preset neighborhood range, determining gray characteristic coefficients of the edge lines, screening target edge lines from the edge lines according to the linear characteristic coefficients and the gray characteristic coefficients, and determining distribution characteristic coefficients of the clothes hangers on the clothes airing rod according to the distances between different target edge lines;
according to the number of the target edge lines and the distribution characteristic coefficients of the clothes hangers, determining the clothes stacking degree in the intelligent wardrobe, and adjusting the dehumidification strategy of the dehumidifier on the intelligent wardrobe according to the clothes stacking degree.
2. An intelligent wardrobe dehumidifying apparatus as claimed in claim 1, wherein the determining of the linear characteristic coefficient of each edge line according to the distribution of all the pixels on each edge line comprises:
performing straight line fitting on all pixel points on any edge line to obtain a fitting straight line of the edge line;
and determining the linear characteristic coefficient of the edge line according to the distance between the fitting straight line and all the pixel points on the edge line.
3. An intelligent wardrobe dehumidifying apparatus as claimed in claim 2, wherein said determining a linear characteristic coefficient of an edge line based on distances between said fitted line and all pixels on said edge line comprises:
and calculating Euclidean distances between all pixel points on the edge line and the fitting straight line as fitting distances, and taking a normalized value of the mean value of the fitting distances as a straight line characteristic coefficient of the edge line.
4. The intelligent wardrobe dehumidifying apparatus according to claim 1, wherein the determining the gray scale characteristic coefficient of each edge line according to the gray scale values of the pixel point on the edge line and other pixels in the preset neighborhood range comprises:
calculating the sum of the absolute values of the gray value difference values of each pixel point on any edge line and other pixels in a preset neighborhood range, and normalizing the sum to obtain an edge gray difference coefficient;
and calculating the normalized value of the average value of the edge gray scale difference coefficients of all pixel points on each edge line as the gray scale characteristic coefficient of the edge line.
5. An intelligent wardrobe dehumidifying apparatus as claimed in claim 1, wherein said screening the target edge line from the edge line according to the linear characteristic coefficient and the gray characteristic coefficient comprises:
calculating a product normalization value of the linear characteristic coefficient and the gray characteristic coefficient as an edge judgment index;
judging whether the edge judging index meets a preset condition or not;
taking the edge line of which the edge judgment index meets a preset condition as a target edge line;
and taking the edge line of which the edge judgment index does not meet a preset condition as a noise edge line.
6. The intelligent wardrobe dehumidifying apparatus according to claim 5, wherein said determining whether the edge determination index satisfies a preset condition comprises:
when the edge judgment index is larger than a preset index threshold, determining that the edge judgment index meets a preset condition;
and when the edge judgment index is smaller than or equal to a preset index threshold, determining that the edge judgment index does not meet a preset condition.
7. An intelligent wardrobe dehumidification apparatus according to claim 1, wherein the determining the distribution characteristic coefficient of the laundry rack on the laundry rack according to the distances between different target edge lines comprises:
calculating Euclidean distance between midpoints of two adjacent target edge lines as edge distance, and taking edge distance which is larger than a preset distance threshold value in all the edge distances as effective distance; and taking the average value of all the effective distances as a distribution characteristic coefficient.
8. An intelligent wardrobe dehumidifying apparatus as claimed in claim 1, wherein said determining the laundry accumulation degree in said intelligent wardrobe based on the number of said target edge lines and the distribution characteristic coefficient of the laundry rack comprises:
calculating the normalized value of the number of all the target edge lines as a number characteristic coefficient;
and calculating the product of the quantity characteristic coefficient and the distribution characteristic coefficient as the clothes accumulation degree.
9. An intelligent wardrobe dehumidification apparatus according to claim 1, wherein said adjusting a dehumidification strategy of said intelligent wardrobe by said dehumidifier according to said laundry accumulation level comprises:
and when the clothes accumulation degree is larger than a preset accumulation degree threshold value, reducing the running interval time of the dehumidifier.
10. The intelligent wardrobe dehumidification device based on air conditioning according to claim 1, wherein the edge detection of the gray level image, and determining edge lines intersecting the clothes poles and having different directions in the gray level image, comprises:
and carrying out edge detection processing on the gray level image based on a Canny edge detection operator, and determining edge lines which intersect the clothes-horse and have different directions in the gray level image.
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