CN110401763B - Mobile terminal action triggering system based on mode detection - Google Patents
Mobile terminal action triggering system based on mode detection Download PDFInfo
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- CN110401763B CN110401763B CN201910296665.4A CN201910296665A CN110401763B CN 110401763 B CN110401763 B CN 110401763B CN 201910296665 A CN201910296665 A CN 201910296665A CN 110401763 B CN110401763 B CN 110401763B
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- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- G06V20/00—Scenes; Scene-specific elements
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- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
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- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
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- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72454—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to context-related or environment-related conditions
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Abstract
The invention relates to an action triggering system based on mode detection, which comprises: the area extraction device is positioned in the mobile phone and used for identifying each electric vehicle area where each electric vehicle object in the instant correction image is respectively positioned based on the electric vehicle imaging characteristics and outputting the electric vehicle area with the largest area as a target area; the parameter identification device is used for sending a collision early warning signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is less than or equal to a preset depth of field threshold value; and the rear camera is used for starting the camera shooting operation of the scene in front of the vehicle when receiving the first driving instruction so as to obtain and output a corresponding image of the scene in front of the vehicle. The action triggering system based on the mode detection is reasonable in design and wide in application. Due to the fact that the target detection is carried out on the electric vehicle object in front of the vehicle, corresponding signal early warning operation is executed when the nearest electric vehicle object approaches, and therefore the probability of traffic accidents is reduced as far as possible.
Description
Technical Field
The invention relates to the field of handheld terminals, in particular to a mobile terminal action triggering system based on mode detection.
Background
According to the field of use, the handheld terminals can be divided into the following two main types: (1) an industrial handheld terminal; the industrial handheld terminal comprises an industrial PDA, a bar code handheld terminal, an RFID handheld middle-distance all-in-one machine and the like. The industrial characteristic is that the product is firm and durable, can be used in a plurality of places with severe environment, and simultaneously, a plurality of optimization are carried out according to the industrial use characteristic. The industrial-grade hand-held terminal can simultaneously support RFID reading and writing and bar code scanning functions, and has an IP64 industrial grade, which are not possessed by the consumer hand-held terminal. (2) A consumer handheld terminal; the consumer handheld terminal mainly refers to a smart phone, a palm computer, a tablet computer and the like.
Disclosure of Invention
The invention has at least the following two important points:
(1) based on the characteristics of flexibility and high speed of the electric vehicle, the target of the electric vehicle in front of the vehicle is detected in a targeted manner, so that corresponding signal early warning operation is executed when the nearest electric vehicle target approaches, and the probability of traffic accidents is reduced as much as possible;
(2) and carrying out consistency matching on each contour of each target sub-image in which each target is respectively positioned in the image, determining the corresponding consistency degree based on the matching result, and determining that the image data volume is small when the consistency degree is high so as to increase bilateral filtering fuzzy processing and improve the self-adaptive capacity of image processing.
According to an aspect of the present invention, there is provided a motion triggering system based on pattern detection, the system including: the mobile phone comprises a mode detection device, a first driving device and a second driving device, wherein the mode detection device is arranged in the mobile phone and used for sending a first driving instruction when detecting that the mobile phone currently enters a navigation mode, and the mobile phone is placed on a vehicle instrument panel and is arranged facing a driver; and the mode detection equipment is also used for sending a second driving instruction when detecting that the mobile phone exits the navigation mode currently.
More specifically, in the pattern detection-based action triggering system: in the mode detection device, when the navigation APP is detected to be started currently by the mobile phone, the mobile phone is determined to enter the navigation mode currently.
More specifically, in the pattern detection-based action triggering system: in the mode detection device, when detecting that the mobile phone does not start any navigation APP currently, determining that the mobile phone exits the navigation mode currently.
More specifically, in the motion trigger system based on pattern detection, the method further includes: the area extraction device is positioned in the mobile phone, is connected with the gamma correction device, and is used for identifying each electric vehicle area where each electric vehicle object in the instant correction image is respectively positioned based on the electric vehicle imaging characteristics and outputting the electric vehicle area with the largest area as a target area; the parameter identification device is connected with the area extraction device and is used for sending a collision early warning signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is less than or equal to a preset depth of field threshold value; the rear camera is positioned in the mobile phone, is connected with the mode detection equipment and is used for starting the camera shooting operation of the scene in front of the vehicle when receiving the first driving instruction so as to obtain and output a corresponding image of the scene in front of the vehicle; the rear camera is also used for stopping the camera shooting operation of the scene in front of the vehicle when the second driving instruction is received.
The action triggering system based on the mode detection is reasonable in design and wide in application. Due to the fact that the target detection is carried out on the electric vehicle object in front of the vehicle, corresponding signal early warning operation is executed when the nearest electric vehicle object approaches, and therefore the probability of traffic accidents is reduced as far as possible.
Drawings
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
fig. 1 is an exemplary schematic diagram illustrating an electric vehicle identified by a motion trigger system based on pattern detection according to an embodiment of the present invention.
Detailed Description
Embodiments of a motion trigger system based on mode detection according to the present invention will be described in detail below with reference to the accompanying drawings.
The mobile phones are classified into Smart phones (Smart phones) and non-Smart phones (Feature phones), the performance of the Smart phones is generally better than that of the non-Smart phones, but the performance of the non-Smart phones is more stable than that of the Smart phones, and most of the non-Smart phones and the Smart phones use a CPU of the british ARM company architecture. The smart phone has higher dominant frequency, high running speed, faster program task processing and more convenience in daily life (for example, the dominant frequency of Nokia n81 is 369 megahertz); the dominant frequency of the non-smart phone is lower, and the running speed is also lower (for example, the dominant frequency of Nokia 5000 is 50 MHz).
The smart phone (Smartphone) is a personal computer which is provided with an independent operating system, most of smartphones are large-screen machines, touch capacitive screens are used, and part of smartphones are resistive screens, so that the Smartphone is powerful in function and high in practicability. The user can install programs provided by third-party service providers such as games, the functions of the mobile phone can be continuously expanded through the programs, and the general name of the mobile phone with wireless network access can be realized through a mobile communication network. The popular one is a simple formula of "1 +1 ═ and" palmtop + mobile phone ═ smart phone ". In a broad sense, the smart phone has most functions of the PDA, especially personal information management and browser and e-mail functions based on wireless data communication, in addition to the call function of the phone. The smart phone provides enough screen size and bandwidth for users, is convenient to carry about, and provides a wide stage for software operation and content service. Many value added services can be deployed as follows: stock, news, weather, traffic, merchandise, application downloads, music picture downloads, etc.
At present, it is common to use a mobile phone as a navigation device in a vehicle, however, when the mobile phone is used as a navigation device, there are no other compatible auxiliary electronic functions except the navigation function, so that a waste of hardware resources of the mobile phone is caused.
In order to overcome the defects, the invention builds an action triggering system based on mode detection, and can effectively solve the corresponding technical problem.
Fig. 1 is an exemplary schematic diagram illustrating an electric vehicle identified by a motion trigger system based on pattern detection according to an embodiment of the present invention.
A pattern detection based action triggering system is shown according to an embodiment of the invention comprising:
the mobile phone comprises a mode detection device, a first driving device and a second driving device, wherein the mode detection device is arranged in the mobile phone and used for sending a first driving instruction when detecting that the mobile phone currently enters a navigation mode, and the mobile phone is placed on a vehicle instrument panel and is arranged facing a driver;
and the mode detection equipment is also used for sending a second driving instruction when detecting that the mobile phone exits the navigation mode currently.
Next, a specific configuration of the operation trigger system based on pattern detection according to the present invention will be further described.
In the pattern detection based action triggering system:
in the mode detection device, when the navigation APP is detected to be started currently by the mobile phone, the mobile phone is determined to enter the navigation mode currently.
In the pattern detection based action triggering system:
in the mode detection device, when detecting that the mobile phone does not start any navigation APP currently, determining that the mobile phone exits the navigation mode currently.
In the motion trigger system based on pattern detection, the method further includes:
the area extraction device is positioned in the mobile phone, is connected with the gamma correction device, and is used for identifying each electric vehicle area where each electric vehicle object in the instant correction image is respectively positioned based on the electric vehicle imaging characteristics and outputting the electric vehicle area with the largest area as a target area;
the parameter identification device is connected with the area extraction device and is used for sending a collision early warning signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is less than or equal to a preset depth of field threshold value;
the rear camera is positioned in the mobile phone, is connected with the mode detection equipment and is used for starting the camera shooting operation of the scene in front of the vehicle when receiving the first driving instruction so as to obtain and output a corresponding image of the scene in front of the vehicle;
the rear camera is also used for stopping the camera shooting operation of the scene in front of the vehicle when the second driving instruction is received;
the self-adaptive recursive filtering equipment is connected with the rear camera and is used for receiving the image of the scene in front of the vehicle, executing self-adaptive recursive filtering processing on the image of the scene in front of the vehicle to obtain a recursive filtering image and outputting the recursive filtering image;
the target separation equipment is used for receiving the recursive filtering image and executing a target identification action on the recursive filtering image so as to obtain each target sub-image in which each target in the recursive filtering image is respectively positioned;
the contour identification device is connected with the target separation device and used for obtaining the contour of each target sub-image and performing consistency matching on each contour of each target sub-image so as to determine the corresponding consistency degree based on the matching result;
the signal extraction equipment is connected with the contour recognition equipment and is used for sending out a first driving signal when the consistency degree exceeds the limit, and otherwise, sending out a second driving signal;
the customized smoothing equipment is respectively connected with the signal extraction equipment and the self-adaptive recursive filtering equipment and is used for executing bilateral filtering fuzzy processing on the recursive filtering image when the second driving signal is received so as to obtain a corresponding customized smoothing image;
the customized smoothing equipment is also used for not executing bilateral filtering fuzzy processing on the recursive filtering image when receiving the first driving signal and directly outputting the recursive filtering image as a customized smoothing image;
a gamma correction device connected to the custom smoothing device for performing gamma correction processing on the received custom smoothed image to obtain an instantaneous corrected image;
the parameter identification equipment is further used for sending a normal state signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is larger than the preset depth of field threshold value;
wherein, in the contour identification device, performing consistency matching on each contour of each target sub-image to determine a corresponding consistency degree based on a matching result comprises: the more consistent each contour of each target sub-image is, the higher the corresponding consistency degree is determined to be;
wherein the customized smoothing device comprises a signal receiving sub-device, a smoothing sub-device and a signal output sub-device.
In the pattern detection based action triggering system:
in the customized smoothing device, the smoothing processing sub-device is respectively connected with the signal receiving sub-device and the signal output sub-device;
the smoothing processing sub-device is configured to execute bilateral filtering fuzzy processing on the recursive filtering image to obtain a corresponding customized smooth image when receiving the second driving signal, and is further configured to execute no bilateral filtering fuzzy processing on the recursive filtering image when receiving the first driving signal, and directly output the recursive filtering image as the customized smooth image.
In the motion trigger system based on pattern detection, the method further includes:
the pixel point identification equipment is connected with the gamma correction equipment and used for receiving the instant correction image and carrying out the following operations on each pixel point of the instant correction image: and determining gradient values of all directions of the pixel points based on the pixel values of the pixel points and all pixel values of all pixel points nearby the pixel points, and determining the gradient values of all directions as contour pixel points when the gradient values of all directions exceed a limited amount.
In the motion trigger system based on pattern detection, the method further includes:
the contour analysis device is connected with the pixel point identification device and is used for receiving each contour pixel point in the instant correction image, forming one or more object contours in the instant correction image by using each contour pixel point in the instant correction image, and outputting a pattern in the instant correction image, which corresponds to each of the one or more object contours, as one or more object patterns;
and the pattern analysis equipment is connected with the contour analysis equipment and used for receiving the one or more object patterns, analyzing the contrast of each object pattern and determining the overall contrast of the instant correction image based on the contrast of each object pattern.
In the motion trigger system based on pattern detection, the method further includes:
the coefficient mapping equipment is connected with the pattern analysis equipment and used for receiving the overall contrast and determining the corresponding decomposition layer number based on the overall contrast, wherein the higher the overall contrast is, the smaller the corresponding decomposition layer number is;
and the image decomposition equipment is respectively connected with the pixel point identification equipment and the coefficient mapping equipment and is used for receiving the instant correction image and the decomposition layer number and carrying out wavelet decomposition on the instant correction image based on the decomposition layer number so as to obtain a low-frequency coefficient of the highest layer and a high-frequency coefficient of each layer.
In the motion trigger system based on pattern detection, the method further includes:
the coefficient correction equipment is connected with the image decomposition equipment and used for receiving the low-frequency coefficient of the highest layer and the layer-by-layer high-frequency coefficient, setting the high-frequency coefficient with the numerical value smaller than a preset coefficient threshold value to be zero, and keeping the high-frequency coefficient with the numerical value larger than or equal to the preset coefficient threshold value to be an original value so as to output the corrected layer-by-layer high-frequency coefficient;
the image reconstruction device is respectively connected with the area extraction device and the coefficient correction device, and is used for receiving the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient, reconstructing based on the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient to obtain a reconstructed image corresponding to the instant correction image, and replacing the instant correction image with the reconstructed image and sending the reconstructed image to the area extraction device;
wherein, in the coefficient correction apparatus, the preset coefficient threshold is inversely proportional to the overall contrast of the immediate correction image.
In the pattern detection based action triggering system:
the coefficient correction device comprises a data receiving unit, a data correction unit and a data output unit, wherein the data receiving unit is connected with the data correction unit, and the data output unit is connected with the data correction unit;
the image reconstruction device is realized by a DSP processing chip, wherein a built-in memory of the DSP processing chip stores a reconstruction mode used for reconstructing based on the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient.
In addition, the DSP processing chip adopts a Harvard structure with separated programs and data, is provided with a special hardware multiplier, widely adopts pipeline operation, provides special DSP instructions and can be used for quickly realizing various digital signal processing algorithms.
According to the requirement of digital signal processing, a DSP processing chip generally has some main features as follows: (1) one multiply and one add may be done in one instruction cycle. (2) The program and data spaces are separate and instructions and data may be accessed simultaneously. (3) On-chip with fast RAM, it is usually accessible in two blocks simultaneously via separate data buses. (4) Hardware support with low or no overhead loops and jumps. (5) Fast interrupt handling and hardware I/O support. (6) There are multiple hardware address generators operating in a single cycle. (7) Multiple operations may be performed in parallel. (8) And pipeline operation is supported, so that the operations of fetching, decoding, executing and the like can be executed in an overlapping way.
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 motion-triggering system based on pattern detection, comprising:
the mobile phone comprises a mode detection device, a first driving device and a second driving device, wherein the mode detection device is arranged in the mobile phone and used for sending a first driving instruction when detecting that the mobile phone currently enters a navigation mode, and the mobile phone is placed on a vehicle instrument panel and is arranged facing a driver;
the mode detection equipment is further used for sending a second driving instruction when detecting that the mobile phone exits the navigation mode currently;
in the mode detection equipment, when the navigation APP is detected to be started currently by the mobile phone, the mobile phone is determined to enter a navigation mode currently;
in the mode detection equipment, when detecting that the mobile phone does not start any navigation APP currently, determining that the mobile phone exits from a navigation mode currently;
the area extraction device is positioned in the mobile phone, is connected with the gamma correction device, and is used for identifying each electric vehicle area where each electric vehicle object in the instant correction image is respectively positioned based on the electric vehicle imaging characteristics and outputting the electric vehicle area with the largest area as a target area;
the parameter identification device is connected with the area extraction device and is used for sending a collision early warning signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is less than or equal to a preset depth of field threshold value;
the rear camera is positioned in the mobile phone, is connected with the mode detection equipment and is used for starting the camera shooting operation of the scene in front of the vehicle when receiving the first driving instruction so as to obtain and output a corresponding image of the scene in front of the vehicle;
the rear camera is also used for stopping the camera shooting operation of the scene in front of the vehicle when the second driving instruction is received;
the self-adaptive recursive filtering equipment is connected with the rear camera and is used for receiving the image of the scene in front of the vehicle, executing self-adaptive recursive filtering processing on the image of the scene in front of the vehicle to obtain a recursive filtering image and outputting the recursive filtering image;
the target separation equipment is used for receiving the recursive filtering image and executing a target identification action on the recursive filtering image so as to obtain each target sub-image in which each target in the recursive filtering image is respectively positioned;
the contour identification device is connected with the target separation device and used for obtaining the contour of each target sub-image and performing consistency matching on each contour of each target sub-image so as to determine the corresponding consistency degree based on the matching result;
the signal extraction equipment is connected with the contour recognition equipment and is used for sending out a first driving signal when the consistency degree exceeds the limit, and otherwise, sending out a second driving signal;
the customized smoothing equipment is respectively connected with the signal extraction equipment and the self-adaptive recursive filtering equipment and is used for executing bilateral filtering fuzzy processing on the recursive filtering image when the second driving signal is received so as to obtain a corresponding customized smoothing image;
the customized smoothing equipment is also used for not executing bilateral filtering fuzzy processing on the recursive filtering image when receiving the first driving signal and directly outputting the recursive filtering image as a customized smoothing image;
a gamma correction device connected to the custom smoothing device for performing gamma correction processing on the received custom smoothed image to obtain an instantaneous corrected image;
the parameter identification equipment is further used for sending a normal state signal when the depth of field of the electric vehicle object corresponding to the target area in the instant correction image is larger than the preset depth of field threshold value;
wherein, in the contour identification device, performing consistency matching on each contour of each target sub-image to determine a corresponding consistency degree based on a matching result comprises: the more consistent each contour of each target sub-image is, the higher the corresponding consistency degree is determined to be;
wherein the customized smoothing device comprises a signal receiving sub-device, a smoothing sub-device and a signal output sub-device;
in the customized smoothing device, the smoothing processing sub-device is respectively connected with the signal receiving sub-device and the signal output sub-device;
the smoothing processing sub-device is used for executing bilateral filtering fuzzy processing on the recursive filtering image when receiving the second driving signal so as to obtain a corresponding customized smooth image, and is also used for executing no bilateral filtering fuzzy processing on the recursive filtering image when receiving the first driving signal so as to directly output the recursive filtering image as the customized smooth image;
the pixel point identification equipment is connected with the gamma correction equipment and used for receiving the instant correction image and carrying out the following operations on each pixel point of the instant correction image: determining gradient values of all directions of the pixel points based on the pixel values of the pixel points and all pixel values of all pixel points nearby the pixel points, and determining the gradient values of all directions as contour pixel points when the gradient values of all directions exceed a limited amount;
the contour analysis device is connected with the pixel point identification device and is used for receiving each contour pixel point in the instant correction image, forming one or more object contours in the instant correction image by using each contour pixel point in the instant correction image, and outputting a pattern in the instant correction image, which corresponds to each of the one or more object contours, as one or more object patterns;
the pattern analysis equipment is connected with the contour analysis equipment and used for receiving the one or more object patterns, analyzing the contrast of each object pattern and determining the overall contrast of the instant correction image based on the contrast of each object pattern;
the coefficient mapping equipment is connected with the pattern analysis equipment and used for receiving the overall contrast and determining the corresponding decomposition layer number based on the overall contrast, wherein the higher the overall contrast is, the smaller the corresponding decomposition layer number is;
the image decomposition equipment is respectively connected with the pixel point identification equipment and the coefficient mapping equipment and is used for receiving the instant correction image and the decomposition layer number and carrying out wavelet decomposition on the instant correction image based on the decomposition layer number so as to obtain a low-frequency coefficient of the highest layer and a high-frequency coefficient of each layer;
the coefficient correction equipment is connected with the image decomposition equipment and used for receiving the low-frequency coefficient of the highest layer and the layer-by-layer high-frequency coefficient, setting the high-frequency coefficient with the numerical value smaller than a preset coefficient threshold value to be zero, and keeping the high-frequency coefficient with the numerical value larger than or equal to the preset coefficient threshold value to be an original value so as to output the corrected layer-by-layer high-frequency coefficient;
the image reconstruction device is respectively connected with the area extraction device and the coefficient correction device, and is used for receiving the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient, reconstructing based on the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient to obtain a reconstructed image corresponding to the instant correction image, and replacing the instant correction image with the reconstructed image and sending the reconstructed image to the area extraction device;
wherein, in the coefficient modification device, the preset coefficient threshold is inversely proportional to the overall contrast of the immediate correction image;
the coefficient correction device comprises a data receiving unit, a data correction unit and a data output unit, wherein the data receiving unit is connected with the data correction unit, and the data output unit is connected with the data correction unit;
the image reconstruction device is realized by a DSP processing chip, wherein a built-in memory of the DSP processing chip stores a reconstruction mode used for reconstructing based on the low-frequency coefficient of the highest layer and the corrected layer-by-layer high-frequency coefficient;
the DSP processing chip adopts a Harvard structure with separated programs and data, is provided with a hardware multiplier, adopts pipeline operation, provides DSP instructions and is used for realizing various digital signal processing algorithms, and has the following characteristics: (1) one multiplication and one addition can be completed in one instruction cycle; (2) the program and the data space are separated, and the instruction and the data can be accessed simultaneously; (3) the chip is provided with a fast RAM which can be accessed in two blocks simultaneously through independent data buses; (4) hardware support with low or no overhead loops and jumps; (5) have fast interrupt handling and hardware I/O support; (6) having a plurality of hardware address generators operating in a single cycle; (7) capable of performing multiple operations in parallel; (8) pipelining is supported to enable operations including fetching, decoding, and execution to be performed overlapping.
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