CN104834928B - The definite method and device of identification region in picture - Google Patents
The definite method and device of identification region in picture Download PDFInfo
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- CN104834928B CN104834928B CN201510232574.6A CN201510232574A CN104834928B CN 104834928 B CN104834928 B CN 104834928B CN 201510232574 A CN201510232574 A CN 201510232574A CN 104834928 B CN104834928 B CN 104834928B
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- G06V10/20—Image preprocessing
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Abstract
The disclosure is directed to a kind of definite method and devices of identification region in picture.The described method includes：Target Photo is divided into the first image section and the second image section according to first axis；Described first image part is determined in the second axial corresponding first histogram and determines that second image section is axial vertical with the first axis in the described second axial corresponding second histogram, described second；The extreme coordinates of identification region in the picture are determined by first histogram and second histogram.Disclosed technique scheme is conducive to the object in identification object region, so that image identification has more specific aim, avoids unnecessary calculation amount in image recognition processes.
Description
Technical field
This disclosure relates in technical field of image processing more particularly to a kind of picture identification region definite method and dress
It puts.
Background technology
By image identification to information extracts included in card when, it is necessary to be to captured card correction
Smooth vertical and horizontal rectangle, so as to preferably be cut to the target area where information included in card.Therefore right
Before card is identified, how to determine that the target area in card becomes correlation technique and must solve the problems, such as.
The content of the invention
To overcome the problems, such as present in correlation technique, the embodiment of the present disclosure provides a kind of definite side of identification region in picture
Method and device to determine the identification region in picture by histogram, make the object in more favourable identification object region.
According to the embodiment of the present disclosure in a first aspect, provide a kind of definite method of identification region in picture, including：
Target Photo is divided into the first image section and the second image section according to first axis；
Described first image part is determined in the second axial corresponding first histogram and determines second image portion
Divide axial vertical with the first axis in the described second axial corresponding second histogram, described second；
The extreme coordinates of identification region in the picture are determined by first histogram and second histogram.
In one embodiment, the definite described first image part can be wrapped in the second axial corresponding first histogram
It includes：
Determine the corresponding first group of weight coefficient of brightness value of described first image part along the first axis, it is described
First group of weight coefficient successively decreases along the first axis；
According to described first image part along right in the brightness value and first group of weight coefficient of the first axis
The weight coefficient answered determines corresponding first histogram of described first image subdivision.
It is in one embodiment, described to determine second image section in the described second axial corresponding second histogram,
It may include：
Determine the corresponding second group of weight coefficient of brightness value of the second image section along the first axis, it is described
Second group of weight coefficient is incremented by along the first axis；
According to second image section along right in the brightness value and second group of weight coefficient of the first axis
The weight coefficient answered determines corresponding second histogram of second subsection.
In one embodiment, it is described that the identification region is determined by first histogram and second histogram
Extreme coordinates, it may include：
Determine first edge in first histogram in described second axial the first location of pixels point and described the
Second edge in one histogram is in described second the second axial location of pixels point；
Determine the 3rd edge in second histogram in the described second axial the 3rd location of pixels point and described the
The 4th edge in two histograms is in the described second the 4th axial location of pixels point, the first location of pixels point, described the
The endpoint that 2 location of pixels points, the 3rd location of pixels point and the 4th location of pixels point form the identification region is sat
Mark.
In one embodiment, the method may also include：
The angle of inclination of the identification region is determined by the extreme coordinates；
The identification region is adjusted to by horizontality from heeling condition according to the angle of inclination.
According to the second aspect of the embodiment of the present disclosure, a kind of determining device of identification region in picture is provided, including：
Split module, be configured as Target Photo being divided into the first image section and the second image portion according to first axis
Point；
First determining module is configured to determine that the described first image part after the segmentation module segmentation in the second axis
To corresponding first histogram and determine that second image section after the segmentation module segmentation is axial described second
Corresponding second histogram, described second is axial vertical with the first axis；
Second determining module is configured as first histogram determined by first determining module and described
Two histograms determine the extreme coordinates of identification region in the picture.
In one embodiment, first determining module may include：
First determination sub-module is configured to determine that brightness value pair of the described first image part along the first axis
The first group of weight coefficient answered, first group of weight coefficient successively decrease along the first axis；
Second determination sub-module, be configured as according to described first image part along the first axis brightness value and
Corresponding weight coefficient determines described first image in first group of weight coefficient that first determination sub-module determines
Corresponding first histogram in part.
In one embodiment, first determining module may include：
3rd determination sub-module is configured to determine that brightness value pair of second image section along the first axis
The second group of weight coefficient answered, second group of weight coefficient are incremented by along the first axis；
4th determination sub-module, be configured as according to second image section along the first axis brightness value and
Corresponding weight coefficient determines the second image in second group of weight coefficient that 3rd determination sub-module determines
Corresponding second histogram in part.
In one embodiment, second determining module may include：
5th determination sub-module, be configured to determine that in first histogram that first determining module determines
Second edge of one edge in the described second axial the first location of pixels point and first histogram is in second axis
To the second location of pixels point；
6th determination sub-module, be configured to determine that in second histogram that first determining module determines
Fourth edge of three edges in the described second axial the 3rd location of pixels point and second histogram is in second axis
To the 4th location of pixels point, the first location of pixels point, the second location of pixels point, the 3rd location of pixels point and
The 4th location of pixels point forms the extreme coordinates of the identification region.
In one embodiment, described device may also include：
3rd determining module is configured as determining the knowledge by the extreme coordinates that second determining module determines
The angle of inclination in other region；
Module is adjusted, is configured as the identification region according to the angle of inclination that the 3rd determining module determines
Horizontality is adjusted to from heeling condition.
According to the third aspect of the embodiment of the present disclosure, a kind of determining device of identification region in picture is provided, including：
Processor；
For storing the memory of processor-executable instruction；
Wherein, the processor is configured as：
Target Photo is divided into the first image section and the second image section according to first axis；
Described first image part is determined in the second axial corresponding first histogram and determines second image portion
Divide axial vertical with the first axis in the described second axial corresponding second histogram, described second；
The extreme coordinates of identification region in the picture are determined by first histogram and second histogram.
The technical scheme provided by this disclosed embodiment can include the following benefits：By Target Photo according to first axle
To the first image section and the second image section is divided into, determine the first image section in the second axial corresponding first histogram
And determine that the second image section in the second axial corresponding second histogram, is determined by the first histogram and the second histogram
The extreme coordinates of identification region in picture, are conducive to the object in identification object region, so that image identification is more directed to
Property, avoid unnecessary calculation amount in image recognition processes.
It should be appreciated that above general description and following detailed description are only exemplary and explanatory, not
The disclosure can be limited.
Description of the drawings
Attached drawing herein is merged in specification and forms the part of this specification, shows the implementation for meeting the present invention
Example, and the principle for explaining the present invention together with specification.
Figure 1A is the flow chart according to the definite method of identification region in the picture shown in an exemplary embodiment.
Figure 1B is the schematic diagram in the target figure shown in an exemplary embodiment.
Fig. 1 C are the schematic diagrames according to the first image section shown in an exemplary embodiment.
Fig. 1 D are the schematic diagrames according to the second image section shown in an exemplary embodiment.
Fig. 1 E are the schematic diagrames according to the first histogram shown in an exemplary embodiment.
Fig. 1 F are the schematic diagrames according to the second histogram shown in an exemplary embodiment.
Fig. 1 G are the schematic diagrames according to the extreme coordinates of the identification region shown in an exemplary embodiment.
Fig. 2 is the flow chart according to the definite method of identification region in the picture shown in an exemplary embodiment one.
Fig. 3 A are the flow charts according to the definite method of identification region in the picture shown in an exemplary embodiment two.
Fig. 3 B are the schematic diagrames according to the identification region after the adjustment shown in an exemplary embodiment two.
Fig. 4 is the block diagram according to the determining device of identification region in a kind of picture shown in an exemplary embodiment.
Fig. 5 is the block diagram according to the determining device of identification region in another picture shown in an exemplary embodiment.
Fig. 6 is the frame according to a kind of determining device of identification region suitable for picture shown in an exemplary embodiment
Figure.
Specific embodiment
Here exemplary embodiment will be illustrated in detail, example is illustrated in the accompanying drawings.Following description is related to
During attached drawing, unless otherwise indicated, the same numbers in different attached drawings represent the same or similar element.Following exemplary embodiment
Described in embodiment do not represent and the consistent all embodiments of the present invention.On the contrary, they be only with it is such as appended
The example of the consistent apparatus and method of some aspects being described in detail in claims, of the invention.
Figure 1A is according to the flow chart of the definite method of identification region in the picture shown in an exemplary embodiment, Tu1BShi
The schematic diagram in target figure according to an exemplary embodiment, Fig. 1 C are according to the first figure shown in an exemplary embodiment
As the schematic diagram of part, Fig. 1 D are according to the schematic diagram of the second image section shown in an exemplary embodiment, and Fig. 1 E are bases
The schematic diagram of the first histogram shown in one exemplary embodiment, Fig. 1 F are according to the second Nogata shown in an exemplary embodiment
The schematic diagram of figure, Fig. 1 G are the schematic diagrames according to the extreme coordinates of the identification region shown in an exemplary embodiment；In the picture
The definite method of identification region can be applied to terminal device (such as：Smart mobile phone, tablet computer, desktop computer) on, it can
In the way of software is installed in a manner of by installing application on smart mobile phone either tablet computer or on the desktop
It realizes, as shown in Figure 1A, the definite method of identification region comprises the following steps S101-S103 in the picture：
In step S101, Target Photo is divided into the first image section and the second image section according to first axis.
In one embodiment, first axis can be the horizontal direction (that is, x-axis) of Target Photo.In one embodiment, may be used
Target Photo to be divided equally along first axis, the first image section and the second image section are obtained, it can also be by target
Picture is split along first axis with any proportion, obtains the first image section and the second image section.As shown in Figure 1B, it is mesh
It marks on a map the schematic diagram of piece 10, from Target Photo 10 as can be seen that the object in target area is the identification card number on identity card
Code, due to shooting angle, captured ID card No. is in target area and non-standard state, but the right is compared on the left side
Low heeling condition.As shown in Fig. 1 C and Fig. 1 D, the first image section 111 is the left-half of the Target Photo shown in Figure 1B,
Second image section 112 is the right half part of the Target Photo shown in Figure 1B, by the way that Target Photo 10 is divided into the first image
111 and second image section 112 of part, consequently facilitating to the first image section 111 and the second image section 112 into column hisgram
Statistics.It will be appreciated by those skilled in the art that thing, shown in Figure 1B to Fig. 1 G only using ID card No. as object as this
A disclosed exemplary illustration, the object in the disclosure can also be word etc..
In step s 102, the first image section is determined in the second axial corresponding first histogram and determines the second figure
As part is axial vertical with first axis in the second axial corresponding second histogram, second.
In one embodiment, second can be axially the vertical direction (that is, y-axis) of Target Photo.In one embodiment,
As referring to figure 1E, can sum along the brightness value of second axial every a line to the first image section 111, so as to obtain first
First histogram 121 of the image section 111 along the second axial direction.In one embodiment, in order to enable close to Target Photo 10
The part at edge (for example, left side) obtains the information of bigger, can be successively decreased by first group of weight coefficient along first axis
Mode adjusts the sum of the brightness value of the first image section 111, so that the left-hand component of the first image section 111 obtains bigger
Weight.As shown in fig. 1F, can sum along the brightness value of second axial every a line to the second image section 112, so as to
The second histogram 122 to the second image section 112 along the second axial direction.In one embodiment, in order to enable by close-target figure
The part at the edge (for example, right side) of piece 10 obtains the information of bigger, can be by second group of weight coefficient along first axis
Incremental mode adjusts the sum of the brightness value of the second image section 112, so that the right-hand component of the second image section 112 obtains
The weight of bigger.
In step s 103, the extreme coordinates of identification region in picture are determined by the first histogram and the second histogram.
In one embodiment, can cog region be determined by the marginal position of the first histogram 121 and the second histogram 122
The extreme coordinates in domain, for example, as shown in Figure 1 G, the position of the endpoint of the both sides of the edge up and down by determining the first histogram 121
Coordinate, you can the first location of pixels point 131 and the second location of pixels point 132 are determined, above and below definite second histogram 122
The position coordinates of the endpoint of both sides of the edge, you can determine the 3rd location of pixels point 133 and the 4th location of pixels point 134.
In the present embodiment, Target Photo is divided into the first image section and the second image section according to first axis, really
Fixed first image section is in the second axial corresponding first histogram and determines that the second image section is axial corresponding second
Second histogram is determined the extreme coordinates of identification region in picture by the first histogram and the second histogram, is conducive to identify
Object in target area so that image identification has more specific aim, avoids unnecessary calculation amount in image recognition processes.
In one embodiment, determine the first image section in the second axial corresponding first histogram, it may include：
Determine the corresponding first group of weight coefficient of brightness value of the first image section along first axis, first group of weight system
Number successively decreases along first axis；
According to the first image section along corresponding weight coefficient in the brightness value of first axis and first group of weight coefficient
Determine corresponding first histogram of the first subsection.
In one embodiment, determine the second image section in the second axial corresponding second histogram, it may include：
Determine the corresponding second group of weight coefficient of brightness value of the second image section along first axis, second group of weight system
Number is incremented by along first axis；
According to the second image section along corresponding weight coefficient in the brightness value of first axis and second group of weight coefficient
Determine corresponding second histogram of the second subsection.
In one embodiment, the extreme coordinates of identification region are determined by the first histogram and the second histogram, it may include：
Determine the first edge in the first histogram in the second axial the first location of pixels point and the first histogram
Second edge is in second the second axial location of pixels point；
Determine the 3rd edge in the second histogram in the second axial the 3rd location of pixels point and the second histogram
4th edge is in the second the 4th axial location of pixels point, the first location of pixels point, the second location of pixels point, the 3rd location of pixels
Point and the 4th location of pixels point form the extreme coordinates of identification region.
In one embodiment, method may also include：
The angle of inclination of identification region is determined by extreme coordinates；
Identification region is adjusted to by horizontality from heeling condition according to angle of inclination.
Specifically how to determine identification region in picture, refer to following embodiment.
So far, the above method that the embodiment of the present disclosure provides, can be conducive to the object in identification object region, make figure
As identification more specific aim, unnecessary calculation amount in image recognition processes is avoided.
The technical solution of embodiment of the present disclosure offer is provided below with specific embodiment.
Fig. 2 is the flow chart according to the definite method of identification region in the picture shown in an exemplary embodiment one；This reality
The above method that example utilizes the embodiment of the present disclosure to provide is applied, how to determine corresponding first histogram of the first image section and the
It is illustrated exemplified by corresponding second histogram of two image sections and with reference to Figure 1B to Fig. 1 G, as shown in Fig. 2, including such as
Lower step：
In step s 201, Target Photo is divided into the first image section and the second image section according to first axis.
The description of step S201 refers to the description of above-mentioned steps S101, and this will not be detailed here.
In step S202, the corresponding first group of weight system of brightness value of the first image section along first axis is determined
Number, first group of weight coefficient successively decrease along first axis.
In step S203, according to the first image section along right in the brightness value of first axis and first group of weight coefficient
The weight coefficient answered determines corresponding first histogram of the first subsection.
In above-mentioned steps S202 and step S203, in one embodiment, first group of weight coefficient can include at least one
A weight coefficient, for example, can the first image section 111 be divided at least two subsections, Ge Getu along first axis
As the corresponding weight coefficient of subdivision successively decreases since edge side along the first image section successively, so as to so that close to first
Proportion shared by the brightness value of the pixel at the edge of image section 111 increases, for example, the left side by the first image section 111
It is 2 to divide imparting weight coefficient, and the right half part of the first image section assigns weight 1, so as to the every of the first image section 111
When a line is summed, make the left-hand component of the first image section 111 that can obtain the weight of bigger.It will be appreciated by those skilled in the art that
, when dividing the first image section 111 subsection for three or more, can power be determined by the above method according to this
Weight coefficient is 2,1.5,1 so that close to the edge of first image section 111 image brightness value histogram statistics
Shared weight is maximum in journey, make edge away from the first image section 111 image brightness value histogram statistics
Shared weight is minimum in journey, and then makes the statistics of the first histogram 121 more accurate.
In step S204, the corresponding second group of weight system of brightness value of the second image section along first axis is determined
Number, second group of weight coefficient are incremented by along first axis.
In step S205, according to the second image section along right in the brightness value of first axis and second group of weight coefficient
The weight coefficient answered determines corresponding second histogram of the second subsection.
In above-mentioned steps S204 and step S205, in one embodiment, second group of weight coefficient can include at least one
A weight coefficient, for example, can the second image section 112 be divided at least two subsections, Ge Getu along first axis
As the corresponding weight coefficient of subdivision is incremented by successively since edge side along the second image section 112, so as to so that close to
Proportion shared by the brightness value of the pixel at the edge of the second image section 112 increases, for example, the right side by the second image section 112
It is 2 that half part, which assigns weight coefficient, and the left-half of the second image section assigns weight 1, so as to the second image section 112
Every a line summation when, make the right-hand component of the second image section 112 that can obtain the weight of bigger.Those skilled in the art can be with
Understand, it, can be true according to this by the above method when dividing the second image section 112 subsection for three or more
It is 1,1.5,2 to determine weight coefficient, so that system of the brightness value of the image at the edge of close second image section 112 in histogram
Shared weight is maximum during meter, make the edge away from the second image section 112 image brightness value histogram system
Shared weight is minimum during meter, and then makes the statistics of the second histogram 122 more accurate.
In step S206, the extreme coordinates of identification region in picture are determined by the first histogram and the second histogram.
The description of step S206 refers to the description of above-mentioned steps S103, and this will not be detailed here.
The present embodiment on the basis of the advantageous effects with above-described embodiment, by make the first image section along
The corresponding first group of weight coefficient of brightness value of first axis successively decreases along first axis, and the second image section is along first axis
The corresponding second group of weight coefficient of brightness value be incremented by along first axis, improve the edge and the second figure of the first image section
Weight as shared by the edge of part, since the part more close to image border is heavier to the angle of inclination for determining identification region
Will, therefore the disclosure is by the corresponding weight of the corresponding brightness value of the pixel for improving image border, so that identification region
The identification of extreme coordinates is more accurate, and then subsequent image identification is made to have more specific aim.
Fig. 3 A are according to the flow chart of the definite method of identification region in the picture shown in an exemplary embodiment two, Fig. 3 B
It is the schematic diagram according to the identification region after the adjustment shown in an exemplary embodiment two；The present embodiment utilizes the embodiment of the present disclosure
The above method of offer, with how by the first histogram and the second histogram determine identification region extreme coordinates and how
It illustrates exemplified by adjustment target area and with reference to Figure 1B to Fig. 1 G, as shown in Figure 3A, includes the following steps：
In step S301, Target Photo is divided into the first image section and the second image section according to first axis.
The description of step S301 refers to the description of above-mentioned steps S101, and this will not be detailed here.
In step s 302, the first image section is determined in the second axial corresponding first histogram and determines the second figure
As part is axial vertical with first axis in the second axial corresponding second histogram, second.
The description of step S302 refers to description or above-mentioned steps S202 the retouching to step S205 of above-mentioned steps S102
It states, herein no longer in detail.
In step S303, determine first edge in the first histogram in second axial the first location of pixels point and the
Second edge in one histogram is in second the second axial location of pixels point.
In step s 304, determine the 3rd edge in the second histogram in the second axial the 3rd location of pixels point and the
The 4th edge in two histograms in the second the 4th axial location of pixels point, the first location of pixels point, the second location of pixels point,
3rd location of pixels point and the 4th location of pixels point form the extreme coordinates of identification region.
In step S303 and step S304, first can be determined by the difference of the adjacent bright angle value of the first histogram
The first edge and second edge of histogram determine the second histogram by the difference of the adjacent bright angle value of the second histogram
3rd edge and the 4th edge and then definite first edge and second edge close to the bottom of the first histogram coordinate points,
So that it is determined that the first location of pixels point and the second location of pixels point, similarly, determine that the 3rd edge and the 4th edge are straight close to second
The coordinate points of the stage of square figure, so that it is determined that the 3rd location of pixels point and the 4th location of pixels point.
In step S305, pass through the first location of pixels point, the second location of pixels point, the 3rd location of pixels point and the 4th picture
Plain location point determines the angle of inclination of identification region.
In one embodiment, the angle of inclination of identification region can be determined by extreme coordinates, as shown in Figure 1 G, if first
131 coordinate points in the target image of location of pixels point be (x1, y1), the second location of pixels 132 seat in the target image of point
Punctuate be (x2, y2), the 3rd 133 coordinate points in the target image of location of pixels point be (x3, y3), the 4th location of pixels point
134 coordinate points in the target image are (x4, y4), you can pass through the first location of pixels point 131 and the 4th location of pixels point 134
The angle of inclination for determining identification region isAlternatively, the second location of pixels point 132 and the 3rd pixel position can be passed through
The angle of inclination for putting a little 133 definite identification regions isAlternatively, it can also pass throughIt determines to know
The angle of inclination in other region.
In step S306, identification region is adjusted to by horizontality from heeling condition according to angle of inclination.
In one embodiment, Principle of Affine Transformation can be based on, according to angle of inclination by identification region from heeling condition tune
Whole is horizontality, and as shown in Figure 3B, after affine transformation, identification region is via skewed for the identification region after adjustment
State is adjusted to horizontality, so as to be identified beneficial to subsequent image.
The present embodiment determines cog region on the basis of the advantageous effects with above-described embodiment, by extreme coordinates
The angle of inclination in domain, and identification region is adjusted to by horizontality from heeling condition according to angle of inclination, so as to identify
The non-standard state (such as the left side of the Target Photo shown in Figure 1B is lower than the right) in region is adjusted to horizontality, so as to true
The rotation angle of identification region is determined to further define on the basis of identification region, so as to be conducive to subsequent image segmentation.
Fig. 4 is according to the block diagram of the determining device of identification region in a kind of picture shown in an exemplary embodiment, such as Fig. 4
Shown, the device for controlling the indicator light being mounted on smart machine includes：
Split module 41, be configured as Target Photo being divided into the first image section and the second image according to first axis
Part；
First determining module 42 is configured to determine that the first image section after the segmentation segmentation of module 41 is axial right second
The second image section after the first histogram answered and definite segmentation module 41 segmentation is in the second axial corresponding second Nogata
Figure, second is axial vertical with first axis；
Second determining module 43 is configured as the first histogram and the second histogram that are determined by the first determining module 42
Determine the extreme coordinates of identification region in picture.
Fig. 5 be according to the block diagram of the determining device of identification region in another picture shown in an exemplary embodiment,
On the basis of above-mentioned embodiment illustrated in fig. 4, as shown in figure 5, in one embodiment, the first determining module 42 may include：
First determination sub-module 421 is configured to determine that the first image section is corresponding along the brightness value of first axis
First group of weight coefficient, first group of weight coefficient successively decrease along first axis；
Second determination sub-module 422 is configured as according to the first image section along the brightness value of first axis and first
Corresponding weight coefficient determines the first subsection corresponding first in first group of definite weight coefficient of determination sub-module 421
Histogram.
In one embodiment, the first determining module 42 may include：
3rd determination sub-module 423 is configured to determine that the second image section is corresponding along the brightness value of first axis
Second group of weight coefficient, second group of weight coefficient are incremented by along first axis；
4th determination sub-module 424 is configured as according to the second image section along the brightness value of first axis and the 3rd
Corresponding weight coefficient determines the second subsection corresponding second in second group of definite weight coefficient of determination sub-module 423
Histogram.
In one embodiment, the second determining module 43 may include：
5th determination sub-module 431, first be configured to determine that in the first definite histogram of the first determining module 42
Second edge of the edge in the second axial the first location of pixels point and the first histogram is in second the second axial pixel position
It puts a little；
6th determination sub-module 432, the 3rd be configured to determine that in the second definite histogram of the first determining module 42
Fourth edge of the edge in the second axial the 3rd location of pixels point and the second histogram is in the second the 4th axial pixel position
It puts a little, the first location of pixels point, the second location of pixels point, the 3rd location of pixels point and the 4th location of pixels point form identification region
Extreme coordinates.
In one embodiment, device may also include：
3rd determining module 44 is configured as determining identification region by the extreme coordinates that the second determining module 43 determines
Angle of inclination；
Module 45 is adjusted, is configured as identification region according to the angle of inclination that the 3rd determining module 44 determines from skewed
State is adjusted to horizontality.
On the device in above-described embodiment, wherein modules perform the concrete mode of operation in related this method
Embodiment in be described in detail, explanation will be not set forth in detail herein.
Fig. 6 is the frame according to a kind of determining device of identification region suitable for picture shown in an exemplary embodiment
Figure.For example, device 600 can be mobile phone, computer, digital broadcast terminal, messaging devices, game console puts down
Board device, Medical Devices, body-building equipment, personal digital assistant etc..
With reference to Fig. 6, device 600 can include following one or more assemblies：Processing component 602, memory 604, power supply
Component 606, multimedia component 608, audio component 610, the interface 612 of input/output (I/O), sensor module 614 and
Communication component 616.
The integrated operation of 602 usual control device 600 of processing component, such as with display, call, data communication, phase
Machine operates and record operates associated operation.Processing element 602 can refer to including one or more processors 620 to perform
Order, to perform all or part of the steps of the methods described above.In addition, processing component 602 can include one or more modules, just
Interaction between processing component 602 and other assemblies.For example, processing component 602 can include multi-media module, it is more to facilitate
Interaction between media component 608 and processing component 602.
Memory 604 is configured as storing various types of data to support the operation in equipment 600.These data are shown
Example is included for the instruction of any application program or method that are operated on device 600, contact data, and telephone book data disappears
Breath, picture, video etc..Memory 604 can be by any kind of volatibility or non-volatile memory device or their group
It closes and realizes, such as static RAM (SRAM), electrically erasable programmable read-only memory (EEPROM) is erasable to compile
Journey read-only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, flash
Device, disk or CD.
Electric power assembly 606 provides electric power for the various assemblies of device 600.Electric power assembly 606 can include power management system
System, one or more power supplys and other generate, manage and distribute electric power associated component with for device 600.
Multimedia component 608 is included in the screen of one output interface of offer between described device 600 and user.One
In a little embodiments, screen can include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, screen
Curtain may be implemented as touch-screen, to receive input signal from the user.Touch panel includes one or more touch sensings
Device is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding action
Border, but also detect duration and pressure associated with the touch or slide operation.In some embodiments, more matchmakers
Body component 608 includes a front camera and/or rear camera.When equipment 600 is in operation mode, such as screening-mode or
During video mode, front camera and/or rear camera can receive external multi-medium data.Each front camera and
Rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 610 is configured as output and/or input audio signal.For example, audio component 610 includes a Mike
Wind (MIC), when device 600 is in operation mode, during such as call model, logging mode and speech recognition mode, microphone by with
It is set to reception external audio signal.The received audio signal can be further stored in memory 604 or via communication set
Part 616 is sent.In some embodiments, audio component 610 further includes a loud speaker, for exports audio signal.
I/O interfaces 612 provide interface between processing component 602 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include but be not limited to：Home button, volume button, start button and lock
Determine button.
Sensor module 614 includes one or more sensors, and the state for providing various aspects for device 600 is commented
Estimate.For example, sensor module 614 can detect opening/closed state of equipment 600, and the relative positioning of component, for example, it is described
Component is the display and keypad of device 600, and sensor module 614 can be with 600 1 components of detection device 600 or device
Position change, the existence or non-existence that user contacts with device 600,600 orientation of device or acceleration/deceleration and device 600
Temperature change.Sensor module 614 can include proximity sensor, be configured to detect without any physical contact
Presence of nearby objects.Sensor module 614 can also include optical sensor, such as CMOS or ccd image sensor, for into
As being used in application.In some embodiments, which can also include acceleration transducer, gyro sensors
Device, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 616 is configured to facilitate the communication of wired or wireless way between device 600 and other equipment.Device
600 can access the wireless network based on communication standard, such as WiFi, 2G or 3G or combination thereof.In an exemplary implementation
In example, communication component 616 receives broadcast singal or broadcast related information from external broadcasting management system via broadcast channel.
In one exemplary embodiment, the communication component 616 further includes near-field communication (NFC) module, to promote short range communication.Example
Such as, NFC module can be based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band (UWB) technology,
Bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, device 600 can be believed by one or more application application-specific integrated circuit (ASIC), number
Number processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array
(FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for performing the above method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instructing, example are additionally provided
Such as include the memory 604 of instruction, above-metioned instruction can be performed to complete the above method by the processor 620 of device 600.For example,
The non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk
With optical data storage devices etc..
Those skilled in the art will readily occur to the disclosure its after considering specification and putting into practice disclosure disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principle of the disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.Description and embodiments are considered only as illustratively, and the true scope and spirit of the disclosure are by following
Claim is pointed out.
It should be appreciated that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by appended claim.
Claims (7)
1. a kind of definite method of identification region in picture, which is characterized in that the described method includes：
Target Photo is divided into the first image section and the second image section according to first axis；
Described first image part is determined in the second axial corresponding first histogram and determines that second image section exists
Described second axial corresponding second histogram, described second is axial vertical with the first axis；
The extreme coordinates of identification region in the picture are determined by first histogram and second histogram；
Wherein, the definite described first image part is in the second axial corresponding first histogram, including：
Determine the corresponding first group of weight coefficient of brightness value of described first image part along the first axis, described first
Group weight coefficient successively decreases along the first axis；
According to described first image part along corresponding in the brightness value and first group of weight coefficient of the first axis
Weight coefficient determines corresponding first histogram of described first image subdivision；
It is described to determine second image section in the described second axial corresponding second histogram, including：
Determine the corresponding second group of weight coefficient of brightness value of the second image section along the first axis, described second
Group weight coefficient is incremented by along the first axis；
According to second image section along corresponding in the brightness value and second group of weight coefficient of the first axis
Weight coefficient determines corresponding second histogram of second subsection.
2. according to the method described in claim 1, it is characterized in that, described pass through first histogram and second Nogata
Figure determines the extreme coordinates of the identification region, including：
Determine the first edge in first histogram in described second the first axial location of pixels point and described first directly
Second edge in square figure is in described second the second axial location of pixels point；
Determine the 3rd edge in second histogram in the described second the 3rd axial location of pixels point and described second directly
The 4th edge in square figure is in the described second the 4th axial location of pixels point, the first location of pixels point, second picture
Plain location point, the 3rd location of pixels point and the 4th location of pixels point form the extreme coordinates of the identification region.
3. according to the method described in claim 1, it is characterized in that, the method further includes：
The angle of inclination of the identification region is determined by the extreme coordinates；
The identification region is adjusted to by horizontality from heeling condition according to the angle of inclination.
4. the determining device of identification region in a kind of picture, which is characterized in that described device includes：
Split module, be configured as Target Photo being divided into the first image section and the second image section according to first axis；
First determining module is configured to determine that the described first image part after the segmentation module segmentation is axial right second
Second image section after the first histogram answered and the definite segmentation module segmentation is axial corresponding described second
The second histogram, described second is axial vertical with the first axis；
Second determining module is configured as first histogram determined by first determining module and described second straight
Side's figure determines the extreme coordinates of identification region in the picture；
Wherein, first determining module includes：
First determination sub-module is configured to determine that described first image part is corresponding along the brightness value of the first axis
First group of weight coefficient, first group of weight coefficient successively decrease along the first axis；
Second determination sub-module is configured as according to described first image part along the brightness value of the first axis and described
Corresponding weight coefficient determines described first image subdivision in first group of weight coefficient that first determination sub-module determines
Corresponding first histogram；
First determining module includes：
3rd determination sub-module is configured to determine that second image section is corresponding along the brightness value of the first axis
Second group of weight coefficient, second group of weight coefficient are incremented by along the first axis；
4th determination sub-module is configured as according to second image section along the brightness value of the first axis and described
Corresponding weight coefficient determines second subsection in second group of weight coefficient that 3rd determination sub-module determines
Corresponding second histogram.
5. device according to claim 4, which is characterized in that second determining module includes：
5th determination sub-module, the first side being configured to determine that in first histogram that first determining module determines
Second edge of the edge in the described second axial the first location of pixels point and first histogram is in the described second axial direction
Second location of pixels point；
6th determination sub-module, the 3rd side being configured to determine that in second histogram that first determining module determines
Fourth edge of the edge in the described second axial the 3rd location of pixels point and second histogram is in the described second axial direction
4th location of pixels point, the first location of pixels point, the second location of pixels point, the 3rd location of pixels point and described
4th location of pixels point forms the extreme coordinates of the identification region.
6. device according to claim 4, which is characterized in that described device further includes：
3rd determining module is configured as determining the cog region by the extreme coordinates that second determining module determines
The angle of inclination in domain；
Module is adjusted, is configured as the identification region according to the angle of inclination that the 3rd determining module determines from inclining
Ramp-like state is adjusted to horizontality.
7. the determining device of identification region in a kind of picture, which is characterized in that described device includes：
Processor；
For storing the memory of processor-executable instruction；
Wherein, the processor is configured as：
Target Photo is divided into the first image section and the second image section according to first axis；
Described first image part is determined in the second axial corresponding first histogram and determines that second image section exists
Described second axial corresponding second histogram, described second is axial vertical with the first axis；
The extreme coordinates of identification region in the picture are determined by first histogram and second histogram；
Wherein, the definite described first image part is in the second axial corresponding first histogram, including：
Determine the corresponding first group of weight coefficient of brightness value of described first image part along the first axis, described first
Group weight coefficient successively decreases along the first axis；
According to described first image part along corresponding in the brightness value and first group of weight coefficient of the first axis
Weight coefficient determines corresponding first histogram of described first image subdivision；
It is described to determine second image section in the described second axial corresponding second histogram, including：
Determine the corresponding second group of weight coefficient of brightness value of the second image section along the first axis, described second
Group weight coefficient is incremented by along the first axis；
According to second image section along corresponding in the brightness value and second group of weight coefficient of the first axis
Weight coefficient determines corresponding second histogram of second subsection.
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| CN108960099B (en) * | 2018-06-22 | 2021-07-06 | 哈尔滨工业大学深圳研究生院 | Method, system, equipment and storage medium for estimating left and right inclination angles of human face |
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| CN102132323A (en) * | 2008-08-26 | 2011-07-20 | 微软公司 | Automatic image straightening |
| CN102509112A (en) * | 2011-11-02 | 2012-06-20 | 珠海逸迩科技有限公司 | Number plate identification method and identification system thereof |
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| US8411970B2 (en) * | 2010-03-16 | 2013-04-02 | Pixia Corp. | Method and system for determining statistical data for image pixels having a higher bit depth per band |
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| CN101137046A (en) * | 2006-08-31 | 2008-03-05 | 索尼株式会社 | Image processing device, method and program |
| CN102132323A (en) * | 2008-08-26 | 2011-07-20 | 微软公司 | Automatic image straightening |
| CN102509112A (en) * | 2011-11-02 | 2012-06-20 | 珠海逸迩科技有限公司 | Number plate identification method and identification system thereof |
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