Automatic recognition method and system based on portrait analysis

Abstract

The present invention relates to an automatic recognition method and system based on portrait analysis, and relates to the field of automatic recognition technology. The method and system include: collecting image detection information; performing illumination analysis based on the image detection information to obtain ambient illumination information; determining whether the ambient illumination information meets preset illumination requirement information; if so, generating and outputting recognition result information based on the image detection information; if not, determining illumination brightness deviation information, illumination uniformity deviation information, and illumination color temperature deviation information based on the ambient illumination information and preset illumination requirement information; generating an illumination adjustment plan based on the illumination brightness deviation information, illumination uniformity deviation information, and illumination color temperature deviation information, and executing the illumination adjustment plan to re-collect the image detection information. The present invention has the effect of improving the accuracy of automatic recognition.

Description

Technical Field

[0001] The present invention relates to the field of automatic recognition technology, and in particular to an automatic recognition method and system based on portrait analysis. Background Art

[0002] Automatic recognition refers to the process of using computer technology, sensors, algorithms and other means to enable a system or device to automatically acquire, process and identify information about a target object without human intervention, thereby achieving the classification, matching or understanding of objects.

[0003] Currently, when performing automatic recognition, the image of the object is generally captured by a camera, and key geometric features of the face such as the distance between the eyes, the height of the nose bridge, and the jaw contour are extracted from the captured image. The extracted key geometric features are then compared with the pre-input template, and the final result is identified based on the similarity.

[0004] When a camera captures an image of an object, the image acquisition is easily affected by the environment in which the camera is located, resulting in errors in automatic recognition. Summary of the Invention

[0005] In order to improve the accuracy of automatic recognition, the present invention provides an automatic recognition method and system based on portrait analysis.

[0006] In a first aspect, the present invention provides an automatic recognition method based on portrait analysis, which adopts the following technical solutions:

[0007] An automatic recognition method based on portrait analysis, comprising:

[0008] S1: collect image detection information;

[0009] S2: Performing illumination analysis based on the image detection information to obtain ambient illumination information;

[0010] S3: Determine whether the ambient lighting information meets preset lighting requirement information;

[0011] S4: If yes, generate recognition result information based on the image detection information and output it;

[0012] S5: If no, determining light brightness deviation information, light uniformity deviation information, and light color temperature deviation information based on the ambient light information and preset light requirement information;

[0013] S6: Generate a lighting adjustment plan based on the lighting luminance deviation information, the lighting uniformity deviation information, and the lighting color temperature deviation information, and execute the lighting adjustment plan to re-collect the image detection information.

[0014] Optionally, the method for generating the illumination adjustment solution includes:

[0015] S61: Retrieving the light luminance deviation value and the brightness deviation position information based on the light luminance deviation information;

[0016] S62: Retrieving the illumination uniformity deviation value and uniformity deviation position information based on the illumination uniformity deviation information;

[0017] S63: Retrieving the lighting color temperature deviation value and color temperature deviation position information based on the lighting color temperature deviation information;

[0018] S64: Determine deviation position overlap information based on the brightness deviation position information, the uniform deviation position information, and the color temperature deviation position information;

[0019] S65: Generate an overlap adjustment plan based on the deviation position overlap information, the light luminance deviation value, the light uniformity deviation value, and the light color temperature deviation value, and use the overlap adjustment plan as the light adjustment plan.

[0020] Optionally, the method for generating the overlap adjustment scheme includes:

[0021] S651: Retrieving the overlap type information and the overlap area value based on the offset position overlap information;

[0022] S652: Selecting from the light illuminance deviation value, the light uniformity deviation value, and the light color temperature deviation value based on the overlap type information to form overlap type deviation information;

[0023] S653: Generate selected device information and an overlap type adjustment value based on the overlap type information, the overlap type deviation information, and the overlap area value;

[0024] S654: Generate an overlap area requirement operation value based on the overlap area value and the selected device information;

[0025] S655: Generate overlapping area lighting adjustment information based on the selected device information, the overlapping type adjustment value and the overlapping area requirement running value, and use the overlapping area lighting adjustment information as the overlapping adjustment solution.

[0026] Optionally, the method for selecting device information and generating the overlap type adjustment value includes:

[0027] S6531: Determine the type of device that meets the requirements based on the overlapping type information;

[0028] S6532: Determine area satisfaction device information based on the overlapped area value;

[0029] S6533: Determine comprehensive satisfying device information based on the type satisfying device information and the area satisfying device information;

[0030] S6534: Determine a satisfying device unit value and a satisfying device impact value based on the comprehensive satisfying device information;

[0031] S6535: Determine a satisfactory equipment area achievement value based on the satisfactory equipment unit value and the overlap area value;

[0032] S6536: Generate a category deviation requirement value based on the overlap category deviation information and the satisfied device impact value;

[0033] S6537: Calculate the difference between the achieved equipment area value and the category deviation requirement value and use it as the achieved area deviation value;

[0034] S6538: Sort the area achievement deviation values from small to large, and use the type-satisfying device information corresponding to the first-ranked area achievement deviation value as the selected device information, and use the corresponding type deviation requirement value as the overlap type adjustment value.

[0035] Optionally, the method for generating the type deviation requirement value includes:

[0036] S65361: Retrieve a single category deviation value and a category number value based on the overlap category deviation information;

[0037] S65362: Calculate the average value of the deviation values of the individual categories and use it as the deviation average value;

[0038] S65363: Determine a quantity impact value based on the quantity value of the category;

[0039] S65364: Calculate the product of the deviation average value and the number impact value and use it as the deviation adjustment value;

[0040] S65365: Calculate the sum of the deviation adjustment value and the satisfied device impact value and use it as the category deviation requirement value.

[0041] Optionally, the method for generating the number of values of the overlap area requirement includes:

[0042] S6541: Retrieving selected device specification information based on the selected device information;

[0043] S6542: Determine a specification unit area value and a specification unit parameter value based on the selected device specification information;

[0044] S6543: Calculate the quotient between the overlapped area value and the unit area value of the specification and use it as the initial value of the specification;

[0045] S6544: Determine a standard unit reference value based on the overlap type adjustment value;

[0046] S6545: Calculate the difference between the specification unit parameter value and the specification unit reference value and use it as the specification unit deviation value;

[0047] S6546: Determine a unit deviation impact value based on the specification unit deviation value;

[0048] S6547: Calculate the product value between the initial numerical value of the specification and the unit deviation impact value and use it as the running numerical value of the overlap area requirement.

[0049] Optionally, the method for generating the overlapping area lighting adjustment information includes:

[0050] S6551: Retrieve the selected device location point based on the selected device information;

[0051] S6552: Determine a selection device angle value based on the selection device position point and a preset recognition position point;

[0052] S6553: Determine quantity operation control information based on the required operation quantity value of the overlapped area;

[0053] S6554: Determine an angle reference impact value based on the overlap type information;

[0054] S6555: Calculate the product of the angle reference impact value and the selected device angle value and use it as the actual angle impact value;

[0055] S6556: Generate brightness output control information based on the selected device angle value, the actual angle impact value, and the overlap type adjustment value;

[0056] S6557: Combining the number operation control information with the brightness output control information to form the overlapping area lighting adjustment information.

[0057] Optionally, the method for generating the brightness output control information includes:

[0058] S65561: Determine a brightness adjustment output value based on the actual angle impact value and the overlap type adjustment value;

[0059] S65562: Determine a specification benchmark output value based on the selected device specification information;

[0060] S65563: Determine whether the brightness adjustment output value is less than the specification reference output value;

[0061] S65564: If yes, determine brightness adjustment output control information based on the brightness adjustment output value, and use the brightness adjustment output control information as the brightness output control information;

[0062] S65565: If not, calculating the difference between the brightness adjustment output value and the specification reference output value and using it as the brightness output abnormality value;

[0063] S65566: Determine angle adjustment control information based on the brightness output abnormal value, and combine the angle adjustment control information with preset brightness reference output control information as the brightness output control information.

[0064] Optionally, the method for generating the recognition result information includes:

[0065] S41: performing person feature recognition based on the image detection information to form image feature information;

[0066] S42: Determining feature distinguishing information based on the image feature information and preset reference feature information;

[0067] S43: Retrieving feature type information and feature value based on the feature distinction information;

[0068] S44: Retrieving characteristic category person information based on the characteristic category information;

[0069] S45: Retrieving character feature benchmark values and character result information based on the character information of the feature type;

[0070] S46: Calculate the difference between the character feature reference value and the feature value and use it as the feature number deviation value;

[0071] S47: Sort the features from small to large based on the feature number deviation values, and use the person result information corresponding to the feature number deviation value that ranks first as the recognition result information.

[0072] In a second aspect, the present invention provides an automatic recognition system based on portrait analysis, which adopts the following technical solutions:

[0073] An automatic recognition system based on portrait analysis, comprising:

[0074] An acquisition module, used for acquiring image detection information;

[0075] A memory, configured to store an automatic recognition method based on portrait analysis as described in any one of the first aspects;

[0076] The processor loads and executes the program in the memory.

[0077] In summary, the present invention includes at least one of the following beneficial technical effects:

[0078] 1. By collecting image detection information and retrieving ambient lighting information to determine whether the preset lighting requirements are met, the system directly generates and outputs recognition result information based on the image detection information. If not, it determines the lighting intensity deviation, lighting uniformity deviation, and lighting color temperature deviation information, generates and executes a lighting adjustment plan, and re-collects the image detection information, thereby reducing the impact of the environment in which the acquisition device is located and improving the accuracy of automatic recognition.

[0079] 2. By retrieving the luminance deviation value and luminance deviation position information from the luminance deviation information, the luminance uniformity deviation value and uniformity deviation position information from the luminance uniformity deviation information, and the luminance color temperature deviation value and color temperature deviation position information from the luminance color temperature deviation information, the overlap information of the deviation positions is determined based on the luminance deviation position information, uniformity deviation position information, and color temperature deviation position information, and then an overlap adjustment plan is generated and used as the luminance adjustment plan, thereby improving the accuracy of the obtained luminance adjustment plan;

[0080] 3. Perform character feature recognition through image detection information to form image feature information and determine feature distinction information to retrieve feature category information and feature number values, retrieve feature category character information through feature category information, and then retrieve character feature benchmark number values and character result information, calculate the feature number deviation value and use the character result information corresponding to the feature number deviation value that is sorted first from small to large as the recognition result information, thereby improving the accuracy of the obtained recognition result information. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 is a flow chart of a method for automatic recognition based on portrait analysis according to an embodiment of the present invention;

[0082] Figure 2 is a flow chart of a method for generating a lighting adjustment solution according to an embodiment of the present invention;

[0083] Figure 3 is a flow chart of a method for generating an overlap adjustment solution according to an embodiment of the present invention;

[0084] Figure 4 This is a flow chart of a method for selecting device information and generating an overlap type adjustment value according to an embodiment of the present invention;

[0085] Figure 5 4 is a flow chart of a method for generating a type deviation requirement value according to an embodiment of the present invention. DETAILED DESCRIPTION

[0086] The present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0087] An automatic recognition method based on portrait analysis collects image detection information and then detects the lighting conditions. When the lighting conditions are met, recognition is performed directly. When the lighting conditions are not met, adjustments are made based on the lighting deviation before collecting images for recognition, thereby reducing the impact of the environment in which the acquisition equipment is located and improving the accuracy of automatic recognition.

[0088] Reference Figure 1 , an embodiment of the present invention discloses an automatic recognition method based on portrait analysis, which includes:

[0089] S1: Collect image detection information.

[0090] The image detection information refers to the image information collected from the object to be identified during automatic identification. The image detection information is collected and acquired through a preset collection device, which may be a camera.

[0091] S2: Performing illumination analysis based on the image detection information to obtain ambient illumination information.

[0092] Among them, ambient lighting information refers to information such as the brightness, color temperature, and uniformity of the light corresponding to the environment in which the acquisition device is located.

[0093] By dividing the image in the image detection information into multiple sub-areas, and then calculating the grayscale values of the sub-areas respectively, the light brightness condition is determined according to the grayscale values of each sub-area, and the grayscale value of the sub-area where the identifiable reference object is located is used as the color temperature reference and compared with other sub-areas to obtain the light color temperature condition, and the change in the grayscale value is used as the light uniformity condition, and then the light brightness condition, light color temperature condition and light uniformity condition are combined to obtain the ambient light information, which is convenient for subsequent use.

[0094] S3: Determine whether the ambient lighting information meets the preset lighting requirement information. If yes, execute S4; if not, execute S5.

[0095] The lighting requirement information refers to the corresponding light brightness, color temperature, and uniformity when accurate automatic recognition is possible. The lighting requirement information is obtained through pre-input.

[0096] By judging whether the ambient light information meets the preset light requirement information, it is determined whether the acquisition equipment needs to be adjusted.

[0097] S4: Generate recognition result information based on the image detection information and output it.

[0098] The recognition result information refers to the result information obtained after automatic recognition.

[0099] When the ambient lighting information meets the preset lighting requirement information, it means that there is no need to adjust the acquisition equipment at this time. Therefore, by analyzing the image detection information, the recognition result information is generated and output, reducing the impact of the environment in which the acquisition equipment is located, thereby improving the accuracy of automatic recognition.

[0100] S5: Determine light intensity deviation information, light uniformity deviation information, and light color temperature deviation information based on the ambient light information and preset light requirement information.

[0101] Among them, the light brightness deviation information refers to the deviation information corresponding to the light brightness deviation, the light uniformity deviation information refers to the deviation information corresponding to the light uniformity deviation, and the light color temperature deviation information refers to the deviation information corresponding to the light color temperature deviation.

[0102] When the ambient lighting information does not meet the preset lighting requirement information, it means that the collection equipment needs to be adjusted. Therefore, the light brightness, color temperature and uniformity in the ambient lighting information are compared one by one with the light brightness, color temperature and uniformity in the preset lighting requirement information, and the deviation of the light brightness is used as the light brightness deviation information, the deviation of the uniformity is used as the light uniformity deviation information, and the deviation of the color temperature is used as the light color temperature deviation information, which is convenient for subsequent use.

[0103] S6: Generate a lighting adjustment plan based on the lighting illuminance deviation information, the lighting uniformity deviation information, and the lighting color temperature deviation information, and execute the lighting adjustment plan to re-collect image detection information.

[0104] The lighting adjustment plan refers to the corresponding plan for adjusting the lighting environment around the acquisition device.

[0105] By analyzing the light intensity deviation information, light uniformity deviation information and light color temperature deviation information, a lighting adjustment plan is generated and executed to re-collect image detection information, thereby reducing the impact of the environment in which the collection equipment is located and improving the accuracy of automatic recognition.

[0106] In step S6, in order to further ensure the rationality of the illumination adjustment scheme, it is necessary to perform further separate analysis and calculation on the illumination adjustment scheme, which is specifically described in detail through the following steps.

[0107] Reference Figure 2 ,The method for generating a lighting adjustment scheme includes the following steps:

[0108] S61: Retrieve the light luminance deviation value and the brightness deviation position information based on the light luminance deviation information.

[0109] The light luminance deviation value refers to the deviation value corresponding to when there is a deviation in the light luminance situation, and the brightness deviation position information refers to the coverage range information of the position where the light luminance situation deviates.

[0110] The light luminance deviation information includes the light luminance deviation value and the brightness deviation position information. The light luminance deviation value and the brightness deviation position information are retrieved through the light luminance deviation information, so as to facilitate subsequent use.

[0111] S62: Retrieve the illumination uniformity deviation value and uniformity deviation position information based on the illumination uniformity deviation information.

[0112] The illumination uniformity deviation value refers to a deviation value corresponding to when there is a deviation in the illumination uniformity, and the uniformity deviation position information refers to coverage information of a position where there is a deviation in the illumination uniformity.

[0113] The illumination uniformity deviation information includes the illumination uniformity deviation value and uniformity deviation position information. The illumination uniformity deviation value and uniformity deviation position information are retrieved through the illumination uniformity deviation information, thereby facilitating subsequent use.

[0114] S63: Retrieve the illumination color temperature deviation value and the color temperature deviation position information based on the illumination color temperature deviation information.

[0115] The light color temperature deviation value refers to the deviation value corresponding to when the light color temperature situation deviates, and the color temperature deviation position information refers to the coverage range information of the position where the light color temperature situation deviates.

[0116] The lighting color temperature deviation information includes the lighting color temperature deviation value and the color temperature deviation position information. The lighting color temperature deviation value and the color temperature deviation position information are retrieved through the lighting color temperature deviation information to facilitate subsequent use.

[0117] S64: Determine deviation position overlap information based on the brightness deviation position information, the uniformity deviation position information, and the color temperature deviation position information.

[0118] The deviation position overlap information refers to the overlap type and overlap coverage information corresponding to the overlap between the brightness, uniformity, and color temperature of the illumination.

[0119] By comparing the positions corresponding to the brightness deviation position information, the uniform deviation position information and the color temperature deviation position information, they are combined according to the overlapping positions and the corresponding types to serve as the deviation position overlap information, which is convenient for subsequent use.

[0120] For example, when the positions corresponding to the brightness deviation position information and the uniform deviation position information overlap, the overlapping positions and the brightness and uniformity types are combined to serve as the deviation position overlap information.

[0121] S65: Generate an overlap adjustment plan based on the deviation position overlap information, the light luminance deviation value, the light uniformity deviation value, and the light color temperature deviation value, and use the overlap adjustment plan as the light adjustment plan.

[0122] Among them, the overlap adjustment plan refers to the corresponding adjustment plan when adjusting the lighting environment around the acquisition device based on the overlap position.

[0123] By analyzing the deviation position overlap information, light illuminance deviation value, light uniformity deviation value and light color temperature deviation value, an overlap adjustment plan is generated and used as a light adjustment plan, thereby improving the accuracy of the obtained light adjustment plan.

[0124] In step S65, in order to further ensure the rationality of the overlap adjustment scheme, it is necessary to perform further separate analysis and calculation on the overlap adjustment scheme, which is specifically described in detail through the following steps.

[0125] Reference Figure 3 , the method for generating the overlap adjustment scheme includes the following steps:

[0126] S651: Retrieve the overlap type information and the overlap area value based on the deviation position overlap information.

[0127] The overlap type information refers to the deviation type information of the overlap coverage range, and the overlap area value refers to the area value corresponding to the overlap coverage range.

[0128] The deviation position overlap situation information includes overlap type situation information and overlap area value. The overlap type situation information and overlap area value are retrieved through the deviation position overlap situation information to facilitate subsequent use.

[0129] S652: Select from the light luminance deviation value, the light uniformity deviation value, and the light color temperature deviation value based on the overlap type information to form overlap type deviation information.

[0130] The overlap type deviation information refers to the aggregate information of deviation values corresponding to the deviation types with overlapped coverage.

[0131] The overlapping category information is used to select from the light illuminance deviation value, the light uniformity deviation value and the light color temperature deviation value, thereby forming the overlapping category deviation information for subsequent use.

[0132] S653: Generate selected device information and overlap type adjustment value based on overlap type information, overlap type deviation information and overlap area value.

[0133] Among them, selecting device information refers to selecting device information corresponding to the lighting adjustment of the surrounding environment of the acquisition device, and the overlapping type adjustment value refers to the adjustment value corresponding to controlling the selection device to adjust the lighting of the surrounding environment of the acquisition device.

[0134] By analyzing the overlap type information, overlap type deviation information, and overlap area value, the selected device information and overlap type adjustment value are generated for subsequent use. The specific steps for generating the selected device information and overlap type adjustment value are shown in S6531 to S6538.

[0135] S654: Generate an overlap area requirement operation value based on the overlap area value and the selected device information.

[0136] The overlap area requirement value refers to the value corresponding to the operation of a single lighting component in the control selection device.

[0137] By analyzing the overlap area value and the selected device information, a required overlap area value is generated for subsequent use. The selected device is the selected light panel, which has multiple pre-set individual lighting elements, which can be light-emitting diodes. For the specific steps for generating the required overlap area value, refer to S6541 to S6547.

[0138] S655: Generate overlapping area lighting adjustment information based on the selected device information, the overlap type adjustment value and the overlap area requirement, and use the overlapping area lighting adjustment information as the overlap adjustment solution.

[0139] The overlapping area lighting adjustment information refers to the adjustment information corresponding to the lighting adjustment of the selected device according to the overlapping area control.

[0140] By analyzing the selected device information, the overlap type adjustment value, and the overlap area requirement, overlap area lighting adjustment information is generated and used as the overlap adjustment plan, thereby improving the accuracy of the obtained overlap adjustment plan. The specific steps for generating the overlap area lighting adjustment information are shown in S6551 to S6557.

[0141] In step S653, in order to further ensure the rationality of the selected device information and the overlap type adjustment value, it is necessary to further analyze and calculate the selected device information and the overlap type adjustment value separately, which is specifically described in detail through the following steps.

[0142] Reference Figure 4, the method for selecting device information and generating the overlap type adjustment value includes the following steps:

[0143] S6531: Determine the type of device information based on the overlapping type situation information.

[0144] The category-satisfying device information refers to device information selected based on the overlapping category situation information, and different overlapping category situation information corresponds to different category-satisfying device information.

[0145] By inputting the overlapping category information into a preset category-satisfying device database to match the category-satisfying device information, it is convenient for subsequent use. The category-satisfying device database pre-stores a comparison table of different overlapping category information and corresponding category-satisfying device information, and the category-satisfying device database is obtained after pre-input.

[0146] S6532: Determine whether the area satisfies device information based on the overlapped area value.

[0147] The area satisfying device information refers to device information selected based on the overlapped area, and different overlapped area values correspond to different area satisfying device information.

[0148] By inputting the overlap area value into a preset area satisfaction device database, the area satisfaction device information is matched and obtained for subsequent use. The area satisfaction device database pre-stores a comparison table of different overlap area values and corresponding area satisfaction device information, and the area satisfaction device database is obtained after pre-input.

[0149] S6533: Determine comprehensive satisfying device information based on the type satisfying device information and the area satisfying device information.

[0150] The comprehensive equipment information refers to the equipment information corresponding to the comprehensive satisfaction of the type and area.

[0151] By comparing the type-satisfying device information with the area-satisfying device information, the devices with consistent type-satisfying device information and area-satisfying device information are taken as comprehensive-satisfying device information, which is convenient for subsequent use.

[0152] S6534: Determine the unit value of the satisfied equipment and the impact value of the satisfied equipment based on the comprehensive satisfied equipment information.

[0153] The "unit value" of the device satisfies the adjustment value achieved per unit area, and the "impact value" of the device satisfies the adjustment value. Different comprehensive device satisfies the adjustment information corresponds to different unit values and impact values.

[0154] By inputting the comprehensive satisfied device information into a preset comprehensive satisfied device database to match the satisfied device unit value and satisfied device impact value, it is convenient for subsequent use. The comprehensive satisfied device database pre-stores a comparison table of different comprehensive satisfied device information and corresponding satisfied device unit values and satisfied device impact values. The comprehensive satisfied device database is obtained after pre-input.

[0155] S6535: Determine the device area achievement value based on the device unit value and the overlap area value.

[0156] The device area achievement value refers to the adjustment value that the device can achieve under the overlapping area.

[0157] By calculating the product value between the device unit value and the overlapping area value, the calculated product value is used as the device area achievement value to facilitate subsequent use.

[0158] S6536: Generate a category deviation requirement value based on the overlapping category deviation information and the satisfied device impact value.

[0159] The category deviation requirement value refers to the adjustment value that needs to be achieved based on the overlapping category deviation information.

[0160] By analyzing the overlapped category deviation information and the satisfied device impact value, a category deviation requirement value is generated for subsequent use. For the specific steps of determining the category deviation requirement value, refer to S65361 to S65365.

[0161] S6537: Calculate the difference between the equipment area achievement value and the type deviation requirement value and use it as the area achievement deviation value.

[0162] The area achievement deviation value refers to a deviation value corresponding to a deviation from an adjustment value that can be achieved by the device.

[0163] By calculating the difference between the equipment area achievement value and the type deviation requirement value and using it as the area achievement deviation value, it is convenient for subsequent use.

[0164] S6538: Sort the devices based on the area achievement deviation value from small to large, and use the type-satisfying device information corresponding to the area achievement deviation value ranked first as the selected device information, and use the corresponding type deviation requirement value as the overlapping type adjustment value.

[0165] Among them, by sorting the area achievement deviation values from small to large, and taking the type satisfaction device information corresponding to the first-ranked area achievement deviation value as the selected device information, and taking the type deviation requirement value corresponding to the first-ranked area achievement deviation value as the overlapping type adjustment value, the accuracy of the obtained selected device information and overlapping type adjustment value is improved.

[0166] In step S6536, in order to further ensure the rationality of the category deviation requirement value, it is necessary to further analyze and calculate the category deviation requirement value separately, which is specifically described in detail through the following steps.

[0167] Reference Figure 5 ,The method for generating the type deviation demand value includes the following steps:

[0168] S65361: Retrieve the individual category deviation value and category number value based on the overlapping category deviation information.

[0169] The single category deviation value refers to the deviation value corresponding to a single overlapping category, and the category individual value refers to the individual value corresponding to the overlapping category.

[0170] The overlapping category deviation information includes a single category deviation value and a category number value. The single category deviation value and the category number value are retrieved through the overlapping category deviation information to facilitate subsequent use.

[0171] S65362: Calculate the average value between the deviation values of a single category and use it as the deviation average value.

[0172] The deviation average refers to the average value corresponding to the deviation values of each individual category. By calculating the average value between the deviation values of each individual category and using it as the deviation average, it is convenient for subsequent use.

[0173] S65363: Determine the number impact value based on the number value of the species.

[0174] The number impact value refers to the impact of the number on the average value, and different types of number values correspond to different number impact values.

[0175] By inputting the number of species values into a preset number impact database to match the number impact value, it is convenient for subsequent use. The number impact database pre-stores a comparison table of different number of species values and corresponding number impact values, and the number impact database is obtained after pre-input.

[0176] S65364: Calculate the product of the deviation average and the number impact value and use it as the deviation adjustment value.

[0177] The deviation adjustment value refers to the adjustment value corresponding to the deviation average value.

[0178] The product value between the deviation average value and the number influence value is calculated and used as the deviation adjustment value to facilitate subsequent use.

[0179] S65365: Calculate the sum of the deviation adjustment value and the satisfied equipment impact value and use it as the category deviation requirement value.

[0180] The accuracy of the obtained type deviation requirement value is improved by calculating the sum of the deviation adjustment value and the device impact value and using it as the type deviation requirement value.

[0181] In step S654, in order to further ensure the rationality of the overlap area requirement running value, it is necessary to further analyze and calculate the overlap area requirement running value separately, which is specifically explained in detail through the following steps.

[0182] The method for generating the number of values of the overlap area requirement includes the following steps:

[0183] S6541: Retrieve the selected device specification information based on the selected device information.

[0184] The selecting of device specification information refers to selecting specification information corresponding to the device, and the selecting of device information includes selecting device specification information. The selected device specification information is retrieved by selecting device information for subsequent use.

[0185] S6542: Determine the specification unit area value and specification unit parameter value based on the selected equipment specification information.

[0186] The "Specification Unit Area Value" refers to the area value corresponding to a single lighting fixture of the selected device's specifications, and the "Specification Unit Parameter Value" refers to the operating value corresponding to a single lighting fixture of the selected device's specifications. Different selected device specifications correspond to different Specification Unit Area Values and Specification Unit Parameter Values.

[0187] By inputting the selected equipment specification information into a preset selected equipment specification database to match the specification unit area value and specification unit parameter value, it is convenient for subsequent use. The selected equipment specification database pre-stores a comparison table of different selected equipment specification information and corresponding specification unit area value and specification unit parameter value, and the selected equipment specification database is obtained after pre-input.

[0188] S6543: Calculate the quotient between the overlap area value and the unit area value of the specification and use it as the initial value of the specification.

[0189] The "initial number of specifications" refers to the initial number of lighting fixtures within the specified specifications that must be selected for operation. The quotient between the overlapped area value and the unit area value is calculated and used as the initial number of specifications for subsequent use.

[0190] S6544: Determine the specification unit reference value based on the overlap type adjustment value.

[0191] The standard unit reference value refers to the reference operating value that needs to be applied when illuminating a single lighting component based on the overlap type adjustment value. Different overlap type adjustment values correspond to different standard unit reference values.

[0192] By inputting the overlap type adjustment value into a preset standard unit reference database to match the standard unit reference value, it is convenient for subsequent use. The standard unit reference database pre-stores a comparison table of different overlap type adjustment values and corresponding standard unit reference values, and the standard unit reference database is obtained after pre-input.

[0193] S6545: Calculate the difference between the specification unit parameter value and the specification unit reference value and use it as the specification unit deviation value.

[0194] The unit deviation value of the specification refers to the deviation value corresponding to the deviation when a single lighting component is in operation.

[0195] The difference between the specification unit parameter value and the specification unit benchmark value is calculated and used as the specification unit deviation value to facilitate subsequent use.

[0196] S6546: Determine the unit deviation impact value based on the specification unit deviation value.

[0197] The unit deviation impact value refers to the impact of the specification unit deviation value on the quantity. Different specification unit deviation values correspond to different unit deviation impact values.

[0198] By inputting different unit deviation values into a preset unit deviation impact database, the unit deviation impact value is matched and obtained, which is convenient for subsequent use. The unit deviation impact database pre-stores a comparison table of different unit deviation values of specifications and corresponding unit deviation impact values, and the unit deviation impact database is obtained after pre-input.

[0199] S6547: Calculate the product value between the initial value of the specification and the unit deviation impact value and use it as the running value of the overlap area requirement.

[0200] Among them, the accuracy of the obtained overlapping area requirement running number value is improved by calculating the product value between the initial value of the specification and the unit deviation influence value and taking it as the overlapping area requirement running number value.

[0201] In step S655, in order to further ensure the rationality of the overlapping area lighting adjustment information, it is necessary to perform further separate analysis and calculation on the overlapping area lighting adjustment information, which is specifically described in detail through the following steps.

[0202] The method for generating overlapping area lighting adjustment information includes the following steps:

[0203] S6551: Retrieve the selected device location point based on the selected device information.

[0204] The selected device location point refers to the location point where the selected position is located, and the selected device information includes the selected device location point. The selected device location point is retrieved through the selected device information for easy subsequent use.

[0205] S6552: Determine the angle value of the selected device based on the selected device position point and the preset recognition position point.

[0206] The identification location point refers to the location point corresponding to the area to be identified by the acquisition device. The identification location point is obtained through pre-input. The selected device angle value refers to the angle value between the selected device and the identification area.

[0207] The angle between the selected device position point and the preset identification position point is calculated as the selected device angle value, which is convenient for subsequent use.

[0208] S6553: Determine the number of operation control information based on the number of operation values required for the overlapped area.

[0209] The number operation control information refers to the number control information for controlling the operation of a single lighting element. Different overlapping area required operation number values correspond to different number operation control information.

[0210] By inputting the overlap area requirement operation number value into a preset operation number control database, the operation number control information is matched and obtained for subsequent use. The operation number control database pre-stores a comparison table of different overlap area requirement operation number values and corresponding operation number control information, and the operation number control database is obtained after pre-input.

[0211] S6554: Determine the angle reference impact value based on the overlap type information.

[0212] The angle reference impact value refers to the reference impact value of a unit angle on brightness based on the overlap type information. Different overlap type information corresponds to different angle reference impact values.

[0213] By inputting the overlap type information into a pre-set angle reference impact database, the angle reference impact value is matched and obtained, facilitating subsequent use. The angle reference impact database pre-stores a comparison table of different overlap type information and corresponding angle reference impact values, and the angle reference impact database is obtained after pre-input.

[0214] S6555: Calculate the product of the angle reference impact value and the selected device angle value and use it as the actual angle impact value.

[0215] The actual impact value of the angle refers to the actual impact value of the angle on the brightness.

[0216] The product value between the angle reference impact value and the selected device angle value is calculated and used as the actual angle impact value for easy subsequent use.

[0217] S6556: Generate brightness output control information based on the selected device angle value, the actual angle impact value, and the overlap type adjustment value.

[0218] The brightness output control information refers to the brightness control information for controlling the operation of a single lighting element.

[0219] By analyzing the selected device angle value, the actual angle impact value, and the overlap type adjustment value, brightness output control information is generated for subsequent use. The specific steps for generating brightness output control information refer to S65561 to S65566.

[0220] S6557: Combine the number-based operation control information with the brightness output control information to form overlapping area lighting adjustment information.

[0221] The overlap area lighting adjustment information is formed by combining the number operation control information with the brightness output control information, thereby improving the accuracy of the acquired overlap area lighting adjustment information.

[0222] In step S6556, in order to further ensure the rationality of the brightness output control information, it is necessary to perform further independent analysis and calculation on the brightness output control information, which is specifically described in detail through the following steps.

[0223] The method for generating brightness output control information includes the following steps:

[0224] S65561: Determine a brightness adjustment output value based on the actual angle impact value and the overlap type adjustment value.

[0225] The brightness adjustment output value refers to the output value corresponding to the adjustment of the overlap type adjustment value according to the angle.

[0226] The sum of the actual angle impact value and the overlap type adjustment value is calculated and used as the brightness adjustment output value for easy subsequent use.

[0227] S65562: Determine a specification benchmark output value based on the selected device specification information.

[0228] The specification benchmark output value refers to the maximum value corresponding to the output of the selected device specification. Different selected device specification information corresponds to different specification benchmark output values.

[0229] By inputting the selected equipment specifications into a preset specification benchmark output database, matching the specification benchmark output values, the database is convenient for subsequent use. The specification benchmark output database pre-stores a comparison table of different selected equipment specifications and corresponding specification benchmark output values, and the specification benchmark output database is obtained after pre-input.

[0230] S65563: Determine whether the brightness adjustment output value is less than the specification reference output value. If so, execute S65564; if not, execute S65565.

[0231] Here, whether the angle needs to be adjusted is determined by determining whether the brightness adjustment output value is less than the specification reference output value.

[0232] S65564: Determine brightness adjustment output control information based on the brightness adjustment output value, and use the brightness adjustment output control information as brightness output control information.

[0233] The brightness adjustment output control information refers to control information for controlling the operation of a single lighting element according to the brightness adjustment output value. Different brightness adjustment output values correspond to different brightness adjustment output control information.

[0234] When the brightness adjustment output value is less than the specification reference output value, it means that the angle does not need to be adjusted at this time. Therefore, the brightness adjustment output control information is obtained by inputting the brightness adjustment output value into a preset brightness adjustment output control database to match it, and the brightness adjustment output control information is used as the brightness output control information, thereby improving the accuracy of the obtained brightness output control information.

[0235] The brightness adjustment output control database pre-stores a comparison table of different brightness adjustment output values and corresponding brightness adjustment output control information, and the brightness adjustment output control database is obtained through pre-input.

[0236] S65565: Calculate the difference between the brightness adjustment output value and the specification reference output value and use it as the brightness output abnormality value.

[0237] The abnormal brightness output value refers to an abnormal value corresponding to an abnormality when the brightness output is insufficient.

[0238] When the brightness adjustment output value is not less than the specification reference output value, it means that the angle needs to be adjusted. Therefore, the difference between the brightness adjustment output value and the specification reference output value is calculated and used as the brightness output abnormal value for subsequent use.

[0239] S65566: Determine angle adjustment control information based on the brightness output abnormal value, and combine the angle adjustment control information with preset brightness reference output control information as brightness output control information.

[0240] The angle adjustment control information refers to the control information for controlling the operation of a single lighting element according to the abnormal brightness output value. The brightness reference output control information refers to the control information corresponding to the brightness output according to the maximum power. The brightness reference output control information is obtained through pre-input.

[0241] Different brightness output abnormal values correspond to different angle adjustment control information. The brightness output abnormal value is input into a preset angle adjustment control database to match the angle adjustment control information, and the angle adjustment control information is combined with the preset brightness reference output control information as the brightness output control information, thereby improving the accuracy of the obtained brightness output control information.

[0242] The angle adjustment control database pre-stores a comparison table of different brightness output abnormal values and corresponding angle adjustment control information, and the angle adjustment control database is obtained through pre-input.

[0243] In step S4, in order to further ensure the rationality of the recognition result information, it is necessary to perform further separate analysis and calculation on the recognition result information, which is specifically described in detail through the following steps.

[0244] The method for generating recognition result information includes the following steps:

[0245] S41: Performing person feature recognition based on the image detection information to form image feature information.

[0246] The image feature information refers to the feature information related to the person in the collected image.

[0247] By performing character feature recognition on the image detection information, image feature information is formed for subsequent use. Character feature recognition on images belongs to the prior art and will not be described in detail here.

[0248] S42: Determine feature distinguishing information based on the image feature information and preset reference feature information.

[0249] The reference feature information refers to the reference information of each feature of a person, and the reference feature information is obtained through pre-input. The feature distinction information refers to the distinction information corresponding to the difference in the features of a person in the captured image.

[0250] By comparing the image feature information with the preset reference feature information, when there is a difference, the type of the feature and the number of differences are used as feature difference information to facilitate subsequent use.

[0251] S43: Retrieve feature type information and feature value based on the feature distinction information.

[0252] Feature category information refers to the category information of the distinguishing feature, and feature individual value refers to the individual value corresponding to the difference in the distinguishing feature. Feature distinction information includes feature category information and feature individual value. Feature distinction information allows you to retrieve feature category information and feature individual value for subsequent use.

[0253] S44: Retrieve characteristic category person information based on the characteristic category information.

[0254] The character information of a characteristic type refers to character information having the distinguishing characteristic type, and different character information of a characteristic type corresponds to different character information of a characteristic type.

[0255] By inputting the feature type information into a preset feature type character database to match the feature type character information, it is convenient for subsequent use. The feature type character database pre-stores a comparison table of different feature type information and corresponding feature type character information, and the feature type character database is obtained after pre-input.

[0256] S45: Retrieve character feature benchmark values and character result information based on the character information of the feature type.

[0257] The "character feature baseline value" refers to the number of character features corresponding to a person with that distinguishing feature type, and the character result information refers to the result information corresponding to identifying a person with that distinguishing feature type. Different character feature types correspond to different character feature baseline values and character result information.

[0258] By inputting the feature type character information into a preset feature type character database to match the character feature benchmark values and character result information, the feature type character database also stores a comparison table of different feature type character information and corresponding character feature benchmark values and character result information. The feature type character database is obtained after pre-input.

[0259] S46: Calculate the difference between the character feature reference value and the feature value and use it as the feature number deviation value.

[0260] The feature number deviation value refers to the deviation value corresponding to the deviation in the number of different features.

[0261] By calculating the difference between the character feature baseline value and the feature value and using it as the feature number deviation value, it is convenient for subsequent use.

[0262] S47: Sort the features from small to large based on the feature number deviation value, and use the person result information corresponding to the feature number deviation value that ranks first as the recognition result information.

[0263] The accuracy of the obtained recognition result information is improved by sorting the feature number deviation values from small to large and using the person result information corresponding to the feature number deviation value ranked first as the recognition result information.

[0264] Based on the same inventive concept, an embodiment of the present invention provides an automatic recognition system based on portrait analysis, comprising:

[0265] An acquisition module, used for acquiring image detection information;

[0266] A memory for storing the above-mentioned automatic recognition method based on portrait analysis;

[0267] The processor loads and executes the program in the memory.

[0268] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0269] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. An automatic recognition method based on portrait analysis, characterized in that: include: S1: collect image detection information; S2: Performing illumination analysis based on the image detection information to obtain ambient illumination information; S3: Determine whether the ambient lighting information meets preset lighting requirement information; S4: If yes, generate recognition result information based on the image detection information and output it; S5: If no, determining light brightness deviation information, light uniformity deviation information, and light color temperature deviation information based on the ambient light information and preset light requirement information; S6: generating a lighting adjustment plan based on the lighting illuminance deviation information, the lighting uniformity deviation information, and the lighting color temperature deviation information, and executing the lighting adjustment plan to re-collect the image detection information; The method for generating the illumination adjustment scheme includes: S61: Retrieving the light luminance deviation value and the brightness deviation position information based on the light luminance deviation information; S62: Retrieving the illumination uniformity deviation value and uniformity deviation position information based on the illumination uniformity deviation information; S63: Retrieving the lighting color temperature deviation value and color temperature deviation position information based on the lighting color temperature deviation information; S64: Determine deviation position overlap information based on the brightness deviation position information, the uniform deviation position information, and the color temperature deviation position information; S65: generating an overlap adjustment plan based on the deviation position overlap information, the light luminance deviation value, the light uniformity deviation value, and the light color temperature deviation value, and using the overlap adjustment plan as the light adjustment plan; The method for generating the overlap adjustment scheme includes: S651: Retrieving the overlap type information and the overlap area value based on the offset position overlap information; S652: Selecting from the light illuminance deviation value, the light uniformity deviation value, and the light color temperature deviation value based on the overlap type information to form overlap type deviation information; S653: Generate selected device information and an overlap type adjustment value based on the overlap type information, the overlap type deviation information, and the overlap area value; S654: Generate an overlap area requirement operation value based on the overlap area value and the selected device information; S655: Generate overlapping area lighting adjustment information based on the selected device information, the overlap type adjustment value and the overlap area requirement running value, and use the overlapping area lighting adjustment information as the overlap adjustment solution.

2. The automatic recognition method based on portrait analysis according to claim 1, characterized in that: The method for selecting device information and generating the overlap type adjustment value includes: S6531: Determine the type of device that meets the requirements based on the overlapping type information; S6532: Determine area satisfaction device information based on the overlapped area value; S6533: Determine comprehensive satisfying device information based on the type satisfying device information and the area satisfying device information; S6534: Determine a satisfying device unit value and a satisfying device impact value based on the comprehensive satisfying device information; S6535: Determine a satisfactory equipment area achievement value based on the satisfactory equipment unit value and the overlap area value; S6536: Generate a category deviation requirement value based on the overlap category deviation information and the satisfied device impact value; S6537: Calculate the difference between the achieved equipment area value and the category deviation requirement value and use it as the achieved area deviation value; S6538: Sort the area achievement deviation values from small to large, and use the type-satisfying device information corresponding to the first-ranked area achievement deviation value as the selected device information, and use the corresponding type deviation requirement value as the overlap type adjustment value.

3. The automatic recognition method based on portrait analysis according to claim 2, characterized in that: The method for generating the type deviation requirement value includes: S65361: Retrieve a single category deviation value and a category number value based on the overlap category deviation information; S65362: Calculate the average value of the deviation values of the individual categories and use it as the deviation average value; S65363: Determine a quantity impact value based on the quantity value of the category; S65364: Calculate the product of the deviation average value and the number impact value and use it as the deviation adjustment value; S65365: Calculate the sum of the deviation adjustment value and the satisfied device impact value and use it as the category deviation requirement value.

4. The automatic recognition method based on portrait analysis according to claim 1, characterized in that: The method for generating the number of values of the overlap area requirement includes: S6541: Retrieving selected device specification information based on the selected device information; S6542: Determine a specification unit area value and a specification unit parameter value based on the selected device specification information; S6543: Calculate the quotient between the overlapped area value and the unit area value of the specification and use it as the initial value of the specification; S6544: Determine a standard unit reference value based on the overlap type adjustment value; S6545: Calculate the difference between the specification unit parameter value and the specification unit reference value and use it as the specification unit deviation value; S6546: Determine a unit deviation impact value based on the specification unit deviation value; S6547: Calculate the product value between the initial numerical value of the specification and the unit deviation impact value and use it as the running numerical value of the overlap area requirement.

5. The automatic recognition method based on portrait analysis according to claim 4, characterized in that: The method for generating the overlapping area lighting adjustment information includes: S6551: Retrieve the selected device location point based on the selected device information; S6552: Determine a selection device angle value based on the selection device position point and a preset recognition position point; S6553: Determine quantity operation control information based on the required operation quantity value of the overlapped area; S6554: Determine an angle reference impact value based on the overlap type information; S6555: Calculate the product of the angle reference impact value and the selected device angle value and use it as the actual angle impact value; S6556: Generate brightness output control information based on the selected device angle value, the actual angle impact value, and the overlap type adjustment value; S6557: Combining the number operation control information with the brightness output control information to form the overlapping area lighting adjustment information.

6. The automatic recognition method based on portrait analysis according to claim 5, characterized in that: The method for generating brightness output control information includes: S65561: Determine a brightness adjustment output value based on the actual angle impact value and the overlap type adjustment value; S65562: Determine a specification benchmark output value based on the selected device specification information; S65563: Determine whether the brightness adjustment output value is less than the specification reference output value; S65564: If yes, determine brightness adjustment output control information based on the brightness adjustment output value, and use the brightness adjustment output control information as the brightness output control information; S65565: If not, calculating the difference between the brightness adjustment output value and the specification reference output value and using it as the brightness output abnormality value; S65566: Determine angle adjustment control information based on the brightness output abnormal value, and combine the angle adjustment control information with preset brightness reference output control information as the brightness output control information.

7. The automatic recognition method based on portrait analysis according to claim 1, characterized in that: The method for generating the recognition result information includes: S41: performing person feature recognition based on the image detection information to form image feature information; S42: Determining feature distinguishing information based on the image feature information and preset reference feature information; S43: Retrieving feature type information and feature value based on the feature distinction information; S44: Retrieving characteristic category person information based on the characteristic category information; S45: Retrieving character feature benchmark values and character result information based on the character information of the feature type; S46: Calculate the difference between the character feature reference value and the feature value and use it as the feature number deviation value; S47: Sort the features from small to large based on the feature number deviation values, and use the person result information corresponding to the feature number deviation value that ranks first as the recognition result information.

8. An automatic recognition system based on portrait analysis, characterized in that: include: An acquisition module, used for acquiring image detection information; A memory, configured to store an automatic recognition method based on portrait analysis according to any one of claims 1 to 7; The processor loads and executes the program in the memory.

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