CN108805818B - Content big data density degree analysis method - Google Patents
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- H04M1/00—Substation equipment, e.g. for use by subscribers
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/12—Picture reproducers
- H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
- H04N9/3141—Constructional details thereof
- H04N9/3173—Constructional details thereof wherein the projection device is specially adapted for enhanced portability
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Abstract
The invention relates to a content big data density degree analysis method which comprises the step of determining the density degree of corresponding content data based on the entropy of the content data played by a current mobile phone by using a content data density degree analysis platform so as to further determine whether projection equipment projects the content data.
Description
Technical Field
The invention relates to the field of big data analysis, in particular to a content big data intensity degree analysis method.
Background
For example, compliance with a service level agreement (S L A) may require continuous monitoring and predictive diagnostic capabilities on key performance metrics to detect impending S L A violations in order to enable operations to circumvent S L A violations, or provide faster problem resolution when violations occur.
Reactive fault detection and manual diagnostic techniques of traditional Information Technology (IT) operations may be too labor intensive, require extensive domain expertise, and may be too late to respond, resulting in a disproportionate response involving restarting a large portion of the system instead of isolating and repairing the faulty component, and may not scale properly for the cloud. Efficient cloud system operation may require continuous measurement of vital signs, time series analysis, multivariate system state models, system response models, predictive anomaly detection, machine learning-based classification, automatic diagnosis and prognosis (prognosis), decision support, and various control capabilities.
A projector is an optical instrument that magnifies the contour of a workpiece using an optical element and projects it onto a screen. It can be used for profile measurement by transmitted light, and also can be used for measuring the surface shape of a blind hole and observing the surface of a part by reflected light. The projector is particularly suitable for measuring complex contours and small workpieces, such as clock parts, stamping parts, electronic elements, templates, dies, threads, gears, forming cutters and the like, and has high inspection efficiency and convenient use; the method is widely applied to measuring rooms and production workshops, and is particularly suitable for the industries of instruments and meters and clocks. The projector can be connected with a computer, a VCD, a DVD, a BD, a game machine, a DV and the like through different interfaces to play corresponding video signals.
Because the projector has the advantages of safety, environmental protection and low damage degree, the projector is an effective replacement mode for the current situation that the frequency and time of using the mobile phone are excessive, however, the mobile phone playing also has the characteristic of high definition, and therefore, the current problem is that when to switch to balance various benefits.
Disclosure of Invention
In order to solve the above problems, the present invention provides a content big data density analysis method, which can project content data by using a projection device when a user watches excessively dense content, because the fatigue degree of the eyes of the user is easily increased, wherein, in order to effectively detect the excessively dense content, a corresponding image preprocessing mechanism and an image detection mechanism are customized, thereby providing high-precision reference data for the switching of the projection device.
For this reason, the present invention has the following three important points:
(1) based on the entropy of the content data played by the current mobile phone, determining the density degree of the corresponding content data so as to further determine whether to project the content data by the projection equipment, thereby avoiding the user from watching the excessively dense content and improving the visibility of content playing;
(2) determining each constituent pixel point of the area where the target is located based on the analysis and judgment of the redundancy of the hue component value, the brightness component value and the saturation component value of each pixel point in the image, thereby ensuring the precision of the subsequent target detection;
(3) based on the preliminary statistical result of the pixel values of the pixel points of the image line by line, the contrast enhancement processing with high degree of change is executed on the image with high degree of change, thereby ensuring the contrast enhancement effect on different image contents.
According to an aspect of the present invention, there is provided a content big data density analysis method, the method including using a content data density analysis platform to determine a density of corresponding content data based on an entropy of content data currently played by a mobile phone, so as to further determine whether to perform projection of the content data by a projection device, the content data density analysis platform including:
the content capturing device is arranged on the mobile phone and used for capturing the content currently played by the mobile phone at intervals of preset time to serve as target content data to be output;
the density analysis device is connected with the target capture device and used for receiving the target content data and judging the density degree of the content based on the target content data to output as target content density; wherein the density analysis device judging the density of the content based on the target content data includes: the larger the entropy of the target content data is, the greater the density of the target content data is;
the state switching equipment is connected with the density analysis equipment, and is used for receiving the target content density, sending a working state switching signal when the target content density is greater than or equal to a preset density threshold value, and sending a dormant state switching signal when the target content density is smaller than the preset density threshold value;
the camera shooting component is arranged on the mobile phone, is connected with the state switching equipment, and is used for starting the camera shooting operation performed on the front of the mobile phone to obtain a front shot image when receiving the working state switching signal and stopping the camera shooting operation performed on the front of the mobile phone when receiving the dormant state switching signal;
and the change degree initial detection equipment is connected with the camera shooting assembly and used for receiving the front photographic image, analyzing the jumping degree of the average value of the pixel points of each row in a top-down mode to obtain each jumping row, and outputting the row number of each jumping row as an initial detection change row number.
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Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a projection simulation diagram of a projection device of a content data density analysis platform according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In order to overcome the defects, the invention builds a content big data intensity degree analysis method, the method comprises the steps of using a content data intensity degree analysis platform to determine the intensity degree of corresponding content data based on the entropy of the content data played by the current mobile phone so as to further determine whether projection equipment projects the content data, and the content data intensity degree analysis platform effectively reduces the eye fatigue degree of a mobile phone user.
Fig. 1 is a projection simulation diagram of a projection device of a content data density analysis platform according to an embodiment of the present invention.
The content data density analysis platform shown according to the embodiment of the invention comprises:
the content capturing device is arranged on the mobile phone and used for capturing the content currently played by the mobile phone at intervals of preset time to serve as target content data to be output;
the density analysis device is connected with the target capture device and used for receiving the target content data and judging the density degree of the content based on the target content data to output as target content density; wherein the density analysis device judging the density of the content based on the target content data includes: the larger the entropy of the target content data is, the greater the density of the target content data is;
the state switching equipment is connected with the density analysis equipment, and is used for receiving the target content density, sending a working state switching signal when the target content density is greater than or equal to a preset density threshold value, and sending a dormant state switching signal when the target content density is smaller than the preset density threshold value;
the camera shooting component is arranged on the mobile phone, is connected with the state switching equipment, and is used for starting the camera shooting operation performed on the front of the mobile phone to obtain a front shot image when receiving the working state switching signal and stopping the camera shooting operation performed on the front of the mobile phone when receiving the dormant state switching signal;
the change degree initial detection equipment is connected with the camera shooting assembly and used for receiving the front photographic image, analyzing the jump degree of the average value of the pixel points of each row in a top-to-bottom mode to obtain each jump row, and outputting the row number of each jump row as an initial detection change row number;
the contrast enhancement equipment is connected with the change degree initial detection equipment and used for receiving the front photographic image and the initial detection change line number and executing contrast enhancement processing on the front photographic image based on the initial detection change line number so as to obtain and output a contrast enhancement image;
the pixel value acquisition equipment is connected with the contrast enhancement equipment and is used for acquiring the hue component value, the brightness component value and the saturation component value of each pixel point in the contrast enhancement image;
the redundancy calculation equipment is connected with the pixel value acquisition equipment and is used for receiving the hue component value, the brightness component value and the saturation component value of each pixel point, performing redundancy judgment on the hue component value of each pixel point to determine whether the pixel point is a hue component redundant pixel point or not, performing redundancy judgment on the brightness component value of each pixel point to determine whether the pixel point is a brightness component redundant pixel point or not, and performing redundancy judgment on the saturation component value of each pixel point to determine whether the pixel point is a saturation component redundant pixel point or not;
the pixel point judgment device is connected with the redundancy calculation device and is used for judging the pixel point as a pixel point to be processed when the pixel point belongs to any two types of hue component redundant pixel points, brightness component redundant pixel points and saturation component redundant pixel points;
the personnel detection equipment is connected with the pixel point judgment equipment and is used for sequentially carrying out image corrosion treatment and image expansion treatment on the patterns formed by all to-be-treated pixel points in the contrast enhanced image so as to obtain the to-be-identified patterns, detecting whether the owner characteristic exists in the to-be-identified patterns or not, and sending out an owner use signal when the owner characteristic exists, or sending out other person use signals;
and the projection equipment is connected with the personnel detection equipment, is used for carrying out instant projection on the currently played content of the mobile phone when receiving the owner use signal, and is also used for stopping the instant projection on the currently played content of the mobile phone when receiving the other people use signal.
Next, the detailed structure of the content data density analysis platform of the present invention will be further described.
In the content data density analysis platform:
in the density analysis device, the greater the entropy of the target content data, the greater the density of the target content data includes: when the target content data is video type data, the larger the resolution of the video type data is, the larger the entropy of the target content data is, and the greater the density of the target content data is.
The content data intensity analysis platform may further include:
and the CF storage card is arranged on the mobile phone, is connected with the state switching equipment and is used for storing the preset density threshold value.
In the content data density analysis platform:
the preset density threshold is different based on different types of target content data, and each type of target content data corresponds to one preset density threshold.
In the content data density analysis platform:
in the contrast enhancement apparatus, performing contrast enhancement processing on the forward photographic image based on the initial examination change line count includes: the more the number of initial inspection change lines is, the greater the intensity of the executed contrast enhancement processing is.
In the content data density analysis platform:
the redundancy judgment of the hue component value of each pixel point to determine whether the pixel point is a hue component redundant pixel point comprises the following steps: and determining a pixel point region of a preset shape with the pixel point as the center, and determining whether the pixel point is a hue component redundant pixel point based on hue component values of all the pixel points in the pixel point region.
In the content data density analysis platform:
the redundancy judgment of the brightness component value of each pixel point to determine whether the pixel point is a brightness component redundancy pixel point comprises the following steps: and determining a pixel point region of a preset shape with the pixel point as the center, and determining whether the pixel point is a brightness component redundant pixel point based on the brightness component values of all the pixel points in the pixel point region.
And in the content data intensity analysis platform:
the redundancy judgment of the saturation component value of each pixel point to determine whether the pixel point is a saturation component redundant pixel point comprises the following steps: and determining a pixel point region of a preset shape with the pixel point as the center, and determining whether the pixel point is a saturation component redundant pixel point based on the saturation component values of all the pixel points in the pixel point region.
In addition, the camera assembly can also comprise an infrared thermal imaging unit which is used for carrying out infrared thermal imaging in a dark environment.
Due to the existence of blackbody radiation, any object is radiated with electromagnetic waves according to different temperatures. The portion having a wavelength of 2.0 to 1000 μm is called thermal infrared. The thermal infrared imaging can reflect the temperature field on the surface of an object by imaging the object through the thermal infrared sensitive CCD. Thermal infrared has wide application in military, industry, automobile auxiliary driving and medical fields.
The infrared thermal imaging principle is not mysterious, and the human body is a natural biological infrared radiation source and can continuously emit and absorb infrared radiation to the surroundings through physical principle analysis. The temperature distribution of a normal human body has certain stability and characteristics, and different temperatures of all parts of the body form different thermal fields. When a disease or a function change occurs at a certain part of a human body, the blood flow at the part changes correspondingly, so that the local temperature of the human body changes, which is expressed by higher or lower temperature. According to the principle, the infrared radiation of the human body is collected through the thermal imaging system and converted into digital signals to form a pseudo color thermal image, and the special analysis equipment is utilized, so that convenience can be provided for various application fields such as human body identification, human body medical treatment and the like.
By adopting the content data density degree analysis platform of the invention, aiming at the technical problem that the fatigue of eyes is easily aggravated when a mobile phone with over-dense content is watched in the prior art, the density degree of the corresponding content data is determined based on the entropy of the content data played by the current mobile phone so as to further determine whether to project the content data by a projection device, thereby avoiding the user from watching the over-dense content and improving the visibility of the content playing, wherein, the content data density degree analysis platform also determines each constituent pixel point of the area where the target is located based on the analysis and judgment of the redundancy of the hue component value, the brightness component value and the saturation component value of each pixel point in the image, thereby ensuring the precision of the subsequent target detection, and executes the powerful contrast enhancement processing on the image with large change degree based on the preliminary statistical result of the pixel values of the image pixel points line by line, thereby realizing high-precision identification of the density of the content data.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (1)
1. A content big data intensity analyzing method comprises the steps of using a content data intensity analyzing platform to determine the intensity of corresponding content data based on the entropy of content data played by a current mobile phone so as to further determine whether projection of the content data by a projection device is carried out, wherein the content data intensity analyzing platform comprises:
the content capturing device is arranged on the mobile phone and used for capturing the content currently played by the mobile phone at intervals of preset time to serve as target content data to be output;
the density analysis device is connected with the content capture device and used for receiving the target content data and judging the density degree of the content based on the target content data to output as target content density; wherein the density analysis device judging the density of the content based on the target content data includes: the larger the entropy of the target content data is, the greater the density of the target content data is;
the state switching equipment is connected with the density analysis equipment, and is used for receiving the target content density, sending a working state switching signal when the target content density is greater than or equal to a preset density threshold value, and sending a dormant state switching signal when the target content density is smaller than the preset density threshold value;
the camera shooting component is arranged on the mobile phone, is connected with the state switching equipment, and is used for starting the camera shooting operation performed on the front of the mobile phone to obtain a front shot image when receiving the working state switching signal and stopping the camera shooting operation performed on the front of the mobile phone when receiving the dormant state switching signal;
the change degree initial detection equipment is connected with the camera shooting assembly and used for receiving the front photographic image, analyzing the jump degree of the average value of the pixel points of each row in a top-to-bottom mode to obtain each jump row, and outputting the row number of each jump row as an initial detection change row number;
the contrast enhancement equipment is connected with the change degree initial detection equipment and used for receiving the front photographic image and the initial detection change line number and executing contrast enhancement processing on the front photographic image based on the initial detection change line number so as to obtain and output a contrast enhancement image;
the pixel value acquisition equipment is connected with the contrast enhancement equipment and is used for acquiring the hue component value, the brightness component value and the saturation component value of each pixel point in the contrast enhancement image;
the redundancy calculation equipment is connected with the pixel value acquisition equipment and is used for receiving the hue component value, the brightness component value and the saturation component value of each pixel point, performing redundancy judgment on the hue component value of each pixel point to determine whether the pixel point is a hue component redundant pixel point or not, performing redundancy judgment on the brightness component value of each pixel point to determine whether the pixel point is a brightness component redundant pixel point or not, and performing redundancy judgment on the saturation component value of each pixel point to determine whether the pixel point is a saturation component redundant pixel point or not;
the pixel point judgment device is connected with the redundancy calculation device and is used for judging the pixel point as a pixel point to be processed when the pixel point belongs to any two types of hue component redundant pixel points, brightness component redundant pixel points and saturation component redundant pixel points;
the personnel detection equipment is connected with the pixel point judgment equipment and is used for sequentially carrying out image corrosion treatment and image expansion treatment on the patterns formed by all to-be-treated pixel points in the contrast enhanced image so as to obtain the to-be-identified patterns, detecting whether the owner characteristic exists in the to-be-identified patterns or not, and sending out an owner use signal when the owner characteristic exists, or sending out other person use signals;
the projection equipment is connected with the personnel detection equipment, is used for carrying out instant projection on the currently played content of the mobile phone when receiving the owner use signal, and is also used for stopping the instant projection on the currently played content of the mobile phone when receiving the other people use signal;
in the contrast enhancement apparatus, performing contrast enhancement processing on the forward photographic image based on the initial examination change line count includes: the more the number of the initial detection change lines is, the greater the intensity of the executed contrast enhancement processing is;
in the density analysis device, the greater the entropy of the target content data, the greater the density of the target content data includes: when the target content data is video type data, the larger the resolution of the video type data is, the larger the entropy of the target content data is, and the larger the density of the target content data is;
the CF storage card is arranged on the mobile phone, is connected with the state switching equipment and is used for storing the preset density threshold value;
the preset density threshold values are different based on different types of target content data, and each type of target content data corresponds to one preset density threshold value;
the redundancy judgment of the hue component value of each pixel point to determine whether the pixel point is a hue component redundant pixel point comprises the following steps: determining a pixel point region of a preset shape with the pixel point as a center, and determining whether the pixel point is a hue component redundant pixel point based on hue component values of all the pixel points in the pixel point region;
the redundancy judgment of the brightness component value of each pixel point to determine whether the pixel point is a brightness component redundancy pixel point comprises the following steps: determining a pixel point region of a preset shape with the pixel point as a center, and determining whether the pixel point is a brightness component redundant pixel point based on the brightness component values of all the pixel points in the pixel point region;
the redundancy judgment of the saturation component value of each pixel point to determine whether the pixel point is a saturation component redundant pixel point comprises the following steps: and determining a pixel point region of a preset shape with the pixel point as the center, and determining whether the pixel point is a saturation component redundant pixel point based on the saturation component values of all the pixel points in the pixel point region.
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| CN1319014C (en) * | 2005-03-16 | 2007-05-30 | 沈阳工业大学 | Personal identity recognising method based on pinna geometric parameter |
| CN100533541C (en) * | 2006-01-19 | 2009-08-26 | 财团法人工业技术研究院 | Device and method for automatic adjusting parameters of display based on visual performance |
| US8700097B2 (en) * | 2009-02-05 | 2014-04-15 | Samsung Electronics Co., Ltd. | Method and system for controlling dual-processing of screen data in mobile terminal having projector function |
| US20110032341A1 (en) * | 2009-08-04 | 2011-02-10 | Ignatov Artem Konstantinovich | Method and system to transform stereo content |
| FR2959839A1 (en) * | 2010-05-06 | 2011-11-11 | France Telecom | TERMINAL INCORPORATING A VIDEOPROJECTOR AND A SCREEN WITH A ZONE ALLOWING THE CONTROL OF A REMOTE POINTER PROJECTED BY THIS VIDEOPROJECTOR |
| TWI545947B (en) * | 2011-04-08 | 2016-08-11 | 南昌歐菲光電技術有限公司 | Display device with image capture and analysis module |
| KR101813035B1 (en) * | 2011-10-10 | 2017-12-28 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
| CN202512468U (en) * | 2012-04-05 | 2012-10-31 | 黑河学院 | Probability distribution list querier |
| CN104636097B (en) * | 2013-11-12 | 2017-09-29 | 广州华久信息科技有限公司 | A kind of font size self-adapting regulation method and mobile terminal based on eyes |
| JP7064333B2 (en) * | 2015-03-23 | 2022-05-10 | オラクル・インターナショナル・コーポレイション | Knowledge-intensive data processing system |
| CN105630167B (en) * | 2015-12-24 | 2019-01-29 | 浙江吉利控股集团有限公司 | Screen self-adapting regulation method, screen self-adapting adjusting apparatus and terminal device |
| CN105577945A (en) * | 2016-03-11 | 2016-05-11 | 厦门美图移动科技有限公司 | Eyesight protection control method and device and mobile terminal |
| CN106998374A (en) * | 2017-04-12 | 2017-08-01 | 江苏农林职业技术学院 | It is a kind of can touch-control projection mobile phone |
| CN107491302A (en) * | 2017-07-31 | 2017-12-19 | 广东欧珀移动通信有限公司 | terminal control method and device |
-
2018
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|---|
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