CN114708500A - Big data enhanced signal analysis system and method - Google Patents
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Abstract
The invention relates to a big data enhancement type signal analysis system, which comprises: the rear-mounted camera is arranged behind a goal of the ice hockey field and used for executing image capturing action on a scene in front of the goal; the big data processing mechanism is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture; and the line crossing processing equipment is used for determining whether the ice hockey ball is successfully crossed based on the imaging depth of field corresponding to each pixel point in the ball identification area and the imaging depth of field corresponding to each pixel point in the boundary identification area. The invention also relates to a big data enhanced signal analysis method. The big data enhancement type signal analysis system and the method thereof have reliable judgment and compact logic. On the basis of providing an image optimization mechanism for big data processing, a double-stage analysis mechanism is adopted to effectively judge whether the ice hockey ball body is out of range or not, so that the intelligent level of ice hockey field management is improved.
Description
Technical Field
The invention relates to the field of big data, in particular to a big data enhanced signal analysis system and a big data enhanced signal analysis method.
Background
Big data can not be processed without leaving the cloud, and the cloud processing provides elastically expandable basic equipment for the big data, and is one of platforms for generating the big data. Since 2013, big data technology is closely combined with cloud computing technology, and the relation between the big data technology and the cloud computing technology is expected to be closer in the future. In addition, emerging computing forms such as the Internet of things and the mobile internet can also help big data revolution together, so that big data marketing can exert greater influence. At present, in the concrete application of big data, confirm effectual localization solution, lead to can't carrying out accurate judgement to the spheroid in puck place whether off-limits, produce the scene of erroneous judgement easily, and then reduced the fairness of whole puck match. Therefore, a reliable big data application scheme is needed to reliably judge whether the ice hockey ball body of the ice hockey game field is out of range or not.
Disclosure of Invention
In order to solve the technical problems in the related field, the invention provides a big data enhancement type signal analysis system and a big data enhancement type signal analysis method.
According to an aspect of the present invention, there is provided a big data enhanced signal analysis system, the system including:
the rear-mounted camera is arranged behind a goal of the ice hockey field and used for executing image capturing action on a scene in front of the goal to obtain a goal foreground image, and the goal foreground image is defaulted to be a standard clear picture;
the data judgment mechanism is connected with the rear-mounted camera and used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
the first identification mechanism is connected with the big data processing mechanism through a network and is used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
the second identification mechanism is connected with the big data processing mechanism through a network and is used for identifying the boundary lines of the goal for the double-stage enhanced picture so as to obtain the boundary line identification area in the ultra-high definition picture;
the coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
the line crossing processing device is connected with the coefficient identification device and used for determining whether the sphere is crossed successfully or not based on the imaging depth of field corresponding to each pixel point in the sphere identification region and the imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
According to another aspect of the present invention, there is also provided a big data enhanced signal analysis method, the method including:
the method comprises the following steps of using a rear-mounted camera, arranging the rear-mounted camera behind a goal of an ice hockey field, and executing image capturing action on a scene in front of the goal to obtain a goal foreground image, wherein the goal foreground image is defaulted to be a standard clear picture;
the use data judgment mechanism is connected with the rear-mounted camera and is used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
a first identification mechanism is connected with the big data processing mechanism through a network and used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
using a second identification mechanism which is connected with the big data processing mechanism through a network and is used for executing identification actions of goal boundary lines on the double-stage enhanced picture so as to obtain boundary line identification areas in the ultra-high definition picture;
the use coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
using a line crossing processing device connected with the coefficient identification device for determining whether the sphere is successfully crossed based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification area and each imaging depth of field corresponding to each pixel point in the boundary identification area comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
The big data enhancement type signal analysis system and the method thereof have reliable judgment and compact logic. On the basis of providing an image optimization mechanism for big data processing, a double-stage analysis mechanism is adopted to effectively judge whether the ice hockey ball body is out of range or not, so that the intelligent level of ice hockey field management is improved.
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Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is a block diagram illustrating an external view of a rear camera used in a big data enhanced signal analysis system and method according to an embodiment of the present invention.
Detailed Description
Embodiments of the big data enhanced signal analysis system and method of the present invention will be described in detail below with reference to the accompanying drawings.
Modern ice hockey originated in canada, and it is documented that as early as 1855, sports enthusiasts in the Kingston (Kingston) area of canada often gathered on iced lake surfaces, held a hockey stick in their hands, bound an ice skate blade on their feet, and pursued each other to hit balls made of wood chips, etc. Early in canada, the hockey game has no unified rules and the game lacks a strict organization. The number of persons participating in the match is not limited, and at most, 30 persons are played in each team, so that the scene is very disordered. The referee can be selected by the athlete and changed at will. At present, in the concrete application of big data, confirm effectual localization solution, lead to can't cross the border and carry out accurate judgement to the spheroid in puck place, the scene of misjudgement has been produced easily, and then has reduced the fairness of whole puck match. Therefore, a reliable big data application scheme is needed to reliably judge whether the ice hockey ball body of the ice hockey game field is out of range or not.
In order to overcome the defects, the invention builds a big data enhanced signal analysis system and a big data enhanced signal analysis method, and can effectively solve the corresponding technical problem.
The invention has the following remarkable technical effects:
when a rear-mounted camera arranged behind a goal of an ice hockey field detects that a captured picture with low resolution has a human body outline with a large area, setting a current scene as a potential attack scene to trigger conversion processing of the same content from a standard definition picture to an ultra-high definition picture;
and intelligently comparing the depth of field data of the ice hockey ball body in the ultra-high definition picture with the depth of field data of the goal boundary line to judge whether the ball body integrally crosses the goal boundary line based on the comparison result, thereby ensuring the accuracy of ice hockey field judgment.
Fig. 1 is a block diagram illustrating an external view of a rear camera used in a big data enhanced signal analysis system and method according to an embodiment of the present invention.
The big data enhanced signal analysis system shown according to the embodiment of the present invention includes:
the rear-mounted camera is arranged behind a goal of the ice hockey field and used for executing image capturing action on a scene in front of the goal to obtain a goal foreground image, and the goal foreground image is defaulted as a clear-marking picture;
the data judgment mechanism is connected with the rear-mounted camera and used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
the first identification mechanism is connected with the big data processing mechanism through a network and is used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
the second identification mechanism is connected with the big data processing mechanism through a network and is used for identifying the boundary lines of the goal for the double-stage enhanced picture so as to obtain the boundary line identification area in the ultra-high definition picture;
the coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
the line crossing processing device is connected with the coefficient identification device and used for determining whether the sphere is crossed successfully or not based on the imaging depth of field corresponding to each pixel point in the sphere identification region and the imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
Next, a detailed structure of the big data enhanced signal analysis system according to the present invention will be described.
The big data enhanced signal analysis system may further include:
and the content adjusting mechanism is connected with the rear-mounted camera and is used for adjusting the quality of the goal foreground image between the standard definition picture and the ultra-high definition picture.
In the big-data enhanced signal analysis system:
the step of adjusting the quality of the goal foreground image between a standard definition picture and an ultra-high definition picture comprises the following steps: the contents of the goal foreground image of the standard definition picture and the goal foreground image of the ultra-high definition picture are consistent.
In the big-data enhanced signal analysis system:
the content adjusting mechanism is also connected with the data judging mechanism and used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be an ultra-high definition picture when receiving a first judging signal;
and the content adjusting mechanism is further used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be a standard-definition picture when receiving a second judgment signal.
In the big-data enhanced signal analysis system:
determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere fails to cross the line when the proportion of the pixel points in the sphere identification area having the imaging depth of field smaller than the reference depth of field value does not exceed the set proportion threshold value.
The big data enhanced signal analysis method according to the embodiment of the invention comprises the following steps:
the method comprises the following steps that a rear-mounted camera is arranged behind a goal of an ice hockey field and used for executing image capturing action on a scene in front of the goal to obtain a goal foreground image, and the goal foreground image is defaulted to be a standard clear picture;
the use data judgment mechanism is connected with the rear-mounted camera and is used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
a first identification mechanism is connected with the big data processing mechanism through a network and used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
using a second identification mechanism which is connected with the big data processing mechanism through a network and is used for executing identification actions of goal boundary lines on the double-stage enhanced picture so as to obtain boundary line identification areas in the ultra-high definition picture;
the use coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
using a line crossing processing device connected with the coefficient identification device for determining whether the sphere is successfully crossed based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
Next, the detailed steps of the big data enhanced signal analysis method of the present invention will be further described.
The big data enhanced signal analysis method may further include:
and the content adjusting mechanism is connected with the rear-mounted camera and is used for adjusting the quality of the goal foreground image between a standard definition picture and an ultrahigh definition picture.
In the big data enhanced signal analysis method:
the step of adjusting the quality of the goal foreground image between a standard definition picture and an ultra-high definition picture comprises the following steps: the contents of the goal foreground image of the standard definition picture and the goal foreground image of the ultra-high definition picture are consistent.
In the big data enhanced signal analysis method:
the content adjusting mechanism is also connected with the data judging mechanism and used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be an ultra-high definition picture when receiving a first judging signal;
and the content adjusting mechanism is further used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be a standard-definition picture when receiving a second judgment signal.
In the big data enhanced signal analysis method:
determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere fails to cross the line when the proportion of the pixel points in the sphere identification area having the imaging depth of field smaller than the reference depth of field value does not exceed the set proportion threshold value.
In addition, in the big data enhanced signal analysis system and method, alternatively, determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: determining the integral imaging depth of field of the sphere identification area based on the imaging depth of field corresponding to each pixel point in the sphere identification area, determining the integral imaging depth of field of the boundary identification area based on the imaging depth of field corresponding to each pixel point in the boundary identification area, and determining that the line crossing of the sphere is successful when the integral imaging depth of the sphere identification area is less than the integral imaging depth of field of the boundary identification area;
and determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: determining the integral imaging depth of field of the sphere identification area based on the imaging depth of field corresponding to each pixel point in the sphere identification area, determining the integral imaging depth of field of the boundary identification area based on the imaging depth of field corresponding to each pixel point in the boundary identification area, and determining that the sphere is failed to cross the line when the integral imaging depth of field of the sphere identification area is deeper than or equal to the integral imaging depth of field of the boundary identification area.
The foregoing description of the exemplary embodiments of the invention has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations will be apparent to practitioners skilled in the art. The exemplary embodiments were chosen and described in order to best explain the principles of the invention and its practical application, to thereby enable others skilled in the art to understand the invention for various embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the following claims and their equivalents.
Claims (10)
1. A big data enhanced signal analysis system, the system comprising:
the rear-mounted camera is arranged behind a goal of the ice hockey field and used for executing image capturing action on a scene in front of the goal to obtain a goal foreground image, and the goal foreground image is defaulted to be a standard clear picture;
the data judgment mechanism is connected with the rear-mounted camera and used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
the first identification mechanism is connected with the big data processing mechanism through a network and is used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
the second identification mechanism is connected with the big data processing mechanism through a network and is used for identifying the boundary lines of the goal for the double-stage enhanced picture so as to obtain the boundary line identification area in the ultra-high definition picture;
the coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
the line crossing processing device is connected with the coefficient identification device and used for determining whether the sphere is crossed successfully or not based on the imaging depth of field corresponding to each pixel point in the sphere identification region and the imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
2. The big-data enhanced signal analysis system of claim 1, wherein the system further comprises:
and the content adjusting mechanism is connected with the rear-mounted camera and is used for adjusting the quality of the goal foreground image between the standard definition picture and the ultra-high definition picture.
3. The big-data enhanced signal analysis system of claim 2, wherein:
the step of adjusting the quality of the goal foreground image between a standard definition picture and an ultra-high definition picture comprises the following steps: the contents of the goal foreground image of the standard definition picture and the goal foreground image of the ultra-high definition picture are consistent.
4. The big-data enhanced signal analysis system of claim 3, wherein:
the content adjusting mechanism is also connected with the data judging mechanism and used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be an ultra-high definition picture when receiving a first judging signal;
and the content adjusting mechanism is further used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be a standard-definition picture when receiving a second judgment signal.
5. The big-data enhanced signal analysis system according to any of claims 1-4, wherein:
determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary line identification area as a reference depth of field value, and determining that the sphere fails to cross the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area does not exceed the set proportion threshold value.
6. A big data enhanced signal analysis method, the method comprising:
the method comprises the following steps of using a rear-mounted camera, arranging the rear-mounted camera behind a goal of an ice hockey field, and executing image capturing action on a scene in front of the goal to obtain a goal foreground image, wherein the goal foreground image is defaulted to be a standard clear picture;
the use data judgment mechanism is connected with the rear-mounted camera and is used for judging whether a human body outline with a larger area exists in a goal foreground image captured at the current moment, sending a first judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be an ultra-high-definition picture when judging that the human body outline exists, and sending a second judgment signal to trigger the goal foreground image captured at the next moment of the rear-mounted camera to be a standard-definition picture when judging that the human body outline does not exist;
the big data processing mechanism is arranged at a wireless network end, is connected with the rear-mounted camera through a network and is used for carrying out salt and pepper noise filtering and edge sharpening on the ultrahigh-definition picture so as to obtain a two-stage enhanced picture;
a first identification mechanism is connected with the big data processing mechanism through a network and used for executing ice hockey ball identification action on the two-stage enhanced picture so as to obtain a ball identification area in the ultra-high definition picture;
using a second identification mechanism which is connected with the big data processing mechanism through a network and is used for executing identification actions of goal boundary lines on the double-stage enhanced picture so as to obtain boundary line identification areas in the ultra-high definition picture;
the use coefficient identification equipment is respectively connected with the first identification mechanism and the second identification mechanism and is used for identifying each imaging depth of field corresponding to each pixel point in the sphere identification area and identifying each imaging depth of field corresponding to each pixel point in the boundary identification area;
using a line crossing processing device connected with the coefficient identification device for determining whether the sphere is successfully crossed based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region;
wherein determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification area and each imaging depth of field corresponding to each pixel point in the boundary identification area comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere is successful in crossing the line when the proportion of the pixel points with the imaging depth of field smaller than the reference depth of field value in the sphere identification area exceeds a set proportion threshold value.
7. The big data enhanced signal analysis method of claim 6, wherein the method further comprises:
and the content adjusting mechanism is connected with the rear-mounted camera and is used for adjusting the quality of the goal foreground image between a standard definition picture and an ultrahigh definition picture.
8. The big-data enhanced signal analysis method of claim 7, wherein:
the step of adjusting the quality of the goal foreground image between a standard definition picture and an ultra-high definition picture comprises the following steps: the contents of the goal foreground image of the standard definition picture and the goal foreground image of the ultra-high definition picture are consistent.
9. The big-data enhanced signal analysis method of claim 8, wherein:
the content adjusting mechanism is also connected with the data judging mechanism and used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be an ultra-high definition picture when receiving a first judging signal;
and the content adjusting mechanism is further used for triggering a goal foreground image captured by the rear-mounted camera at the next moment to be a standard-definition picture when receiving a second judgment signal.
10. The big-data enhanced signal analysis method as claimed in any of claims 6 to 9, wherein:
determining whether the sphere successfully crosses the line based on each imaging depth of field corresponding to each pixel point in the sphere identification region and each imaging depth of field corresponding to each pixel point in the boundary identification region comprises: and taking the intermediate value of each imaging depth of field corresponding to each pixel point in the boundary identification area as a reference depth of field value, and determining that the sphere fails to cross the line when the proportion of the pixel points in the sphere identification area having the imaging depth of field smaller than the reference depth of field value does not exceed the set proportion threshold value.
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| CN118279288A (en) * | 2024-05-08 | 2024-07-02 | 南京特皓发机械设备有限公司 | AI analysis system for silicon steel plate surface |
| CN119667386A (en) * | 2024-02-29 | 2025-03-21 | 南京欧舒达建筑工程有限公司 | Power transmission cable safety monitoring system |
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| CN118279288A (en) * | 2024-05-08 | 2024-07-02 | 南京特皓发机械设备有限公司 | AI analysis system for silicon steel plate surface |
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