CN104239873B - Image processing apparatus and processing method - Google Patents
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- CN104239873B CN104239873B CN201410512740.3A CN201410512740A CN104239873B CN 104239873 B CN104239873 B CN 104239873B CN 201410512740 A CN201410512740 A CN 201410512740A CN 104239873 B CN104239873 B CN 104239873B
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- 238000003672 processing method Methods 0.000 title claims abstract description 28
- 238000004458 analytical method Methods 0.000 claims description 45
- 238000010191 image analysis Methods 0.000 claims description 27
- 230000008859 change Effects 0.000 claims description 15
- 230000003458 metachromatic effect Effects 0.000 claims description 13
- 238000010183 spectrum analysis Methods 0.000 claims description 13
- 238000000034 method Methods 0.000 claims description 12
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 6
- 238000005728 strengthening Methods 0.000 claims description 5
- 238000011282 treatment Methods 0.000 claims description 5
- 238000001228 spectrum Methods 0.000 claims description 2
- 238000003703 image analysis method Methods 0.000 claims 9
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- 238000009434 installation Methods 0.000 description 5
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- 238000005516 engineering process Methods 0.000 description 3
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- 238000010168 coupling process Methods 0.000 description 1
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Abstract
The invention discloses an image processing apparatus and a processing method thereof. The image processing method comprises the following steps: providing at least two preset image data types, wherein the at least two preset image data types respectively correspond to at least one image processing program; the image data is acquired through the image extractor, and the corresponding at least one processing program is selected to be executed according to which of the preset image data types the type of the image data is, so that the image data is processed through the corresponding at least one image processing program. The image processing method provided by the invention can save the step and time for searching the image processing program by a user, and greatly improves the convenience of use.
Description
Technical field
The present invention relates to a kind of image processing apparatus and processing method, and more particularly to one kind automatically selects image procossing journey
The image processing apparatus and processing method of sequence.
Background technology
With the progress of electronics technology, people are also increased for the demand of consumption electronic products.And exchanged in information
On the premise of convenience, electronic product now is frequently necessary to the function with powerful image procossing.
The image extractor configured on electronic installation can be used to extract a variety of images.For example, electricity is passed through
Sub-device, user can extract the view data of the general patterns such as personage, landscape, can also be extracted such as by electronic installation
Fingerprint, file or business card etc. have the view data of trickleer identification feature.And these view data of different nature are directed to,
Electronic installation often needs the image processing program that offer differs to carry out follow-up action.And in known technical field,
The selection of this image processing program usually requires to complete by the operation of user, causes using upper not convenient.
The content of the invention
The embodiment of the present invention provides a kind of image processing apparatus and its image processing method, is chosen according to the species of image
Image processing program.
The image processing method of the embodiment of the present invention includes：At least two pre-set image data class, and at least two are provided
Pre-set image data class corresponds respectively to an at least image processing program；View data is obtained by image extractor, also,
It is which of pre-set image data class according to the species of view data, to select an at least processing routine corresponding to execution,
To handle view data by a corresponding at least image processing program.
The image processing apparatus of the embodiment of the present invention includes image extractor and controller.Image extractor is used for obtaining
View data, controller coupling image extractor, to provide at least two pre-set image data class, at least two pre-set image numbers
An at least image processing program is corresponded respectively to according to species, and being pre-set image data kind according to the species of view data
Class which, come select perform corresponding to an at least image processing program, to handle view data.
Based on above-mentioned, the present invention can be directed to the action that extracted view data is judged, and according to being judged
The species of view data, to correspond to the image processing program for selecting one or more, and one or more images by selecting
Processing routine to carry out the view data that extraction obtains the action of image procossing.Consequently, it is possible to electronic installation can be automatic
Correct image processing program is selected to perform the follow-up image procossing action of view data, the person of eliminating the need for is found at image
The step of managing program and time, the convenience used is substantially improved.
For features described above of the invention and advantage can be become apparent, special embodiment below, and coordinate institute's accompanying drawings
It is described in detail below.
Brief description of the drawings
Fig. 1 shows the flow chart of the image processing method of one embodiment of the invention.
Fig. 2 shows the flow chart of the image procossing mode of another embodiment of the present invention.
Fig. 3~Fig. 7 shows the schematic diagram of a variety of different graphical analysis modes respectively.
Fig. 8 shows the schematic diagram of the image processing apparatus of one embodiment of the invention.
Wherein, description of reference numerals is as follows：
S110~S130, S210~S240：The step of image processing method
311st, 411,511,611,711~713：Fingerprint image
321st, 421,521,621,721~723：Landscape image
312、322：Bar chart
412：Binaryzation fingerprint image
413、423：Image
422：Binaryzation landscape image
512：Fingerprint image after conversion
522：Landscape image after conversion
513：Spectrum analysis fingerprint image
523：Spectrum analysis landscape image
621、622：Edge strengthening image
613、623：Image after processing
800：Image processing apparatus
810：Image extractor
820：Controller
831：Feature identification program
832：Graphic joining program
Embodiment
Fig. 1 is refer to, Fig. 1 shows the flow chart of the image processing method of one embodiment of the invention.Wherein, image processing method
The step of method, includes：In step s 110, view data is obtained by image extractor；Also, in the step s 120, according to
The species of acquired view data in step s 110, come it is (automatic) selection execution multiple images processing routine at least its
One of, also, extracted view data is handled by selected at least one image processing program performed.
In the present embodiment, the view data that image extractor may be extracted has multiple species.Also, various species
View data can correspond to one or more image processing program.Image processing program is corresponding with the species of view data
Relation can be set in advance in image processing apparatus, at one or more images corresponding to the view data of various species
Reason program applies to handle the image processing program of the view data corresponding to it.
Above-mentioned image processing program interior in advance can be built in image processing apparatus, certainly, above-mentioned image processing program
One or more of, networking cause can also be passed through by the electronic installation residing for image processing apparatus or image processing apparatus
Outside is downloaded.
Further illustrate, the image received in the embodiment of the present invention can include multiple species.Image kind therein
Class includes the image with identification feature, such as fingerprint shadow sample, document image, Three-Dimensional Bar Code image and business card image etc., or
Such as the general pattern such as landscape, personage.In an embodiment of the present invention, extract image by image extractor and obtain image
Data, and the differentiation of image species is carried out for view data.That is, the image processing method of the embodiment of the present invention
Method can handle two kinds or two kinds default view data species, and pre-set image data class corresponds respectively at least one
Processing routine.Default view data species for example fingerprint shadow sample species, document image species, Three-Dimensional Bar Code image species and/
Or business card image species etc..
For example, when the species of image is the first species image of such as fingerprint image, image processing apparatus can be selected one
It is individual or it is multiple performed applied to the feature identification program of identification of fingerprint, to carry out identification of fingerprint.Relative, when the species of image
During to be, for example, the second species image of landscape image, image processing apparatus (automatic) can be applied to pattern from one or more
The image processing program of splicing performs.In addition, when the species of image is such as Three-Dimensional Bar Code image, can automatically turn on
Bar code image interpretation program, the automatic information (being, for example, character element code or network address) parsed described in Three-Dimensional Bar Code image.When
The species of image is such as business card image, can automatically turn on card information storage program, parses automatically and stores this name
The contact information of piece.In brief, it is which of default multiple images data class according to the species of view data, comes from
Dynamic selection performs one or more processing routine corresponding to the view data species, to pass through the routine processes of selection
View data.
Fig. 2 is refer to below, and Fig. 2 shows the flow chart of the image procossing mode of another embodiment of the present invention.In fig. 2,
Step S210 carries out the extraction action of image, and obtains view data, also, extracted picture number is directed in step S220
According to come utilize multiple images analysis mode come at least one carry out graphical analysis, and use the one or more figures of acquisition
As the result of analysis.Wherein, image analysis result can be used to indicate that extracted image belongs in multiple pre-set image species
Which image species.
Hold it is above-mentioned, wherein, if selected graphical analysis mode is two or more, the pin in step S230
Above-mentioned multiple images analysis result is judged, and by judging whether image analysis result is consistent to determine graphical analysis
As a result no is correct.It is specifically bright, if the image that multiple images analysis result all indicates to extract is identical type image,
Image analysis result be to be correct, it is opposite, if multiple images analysis result not all indicates that the image of extraction is mutually of the same race
During class image, image analysis result is to be wrong.
If image analysis result is correct, step S240 is carried out with image corresponding to being selected according to image analysis result
Processing routine carries out the action of image procossing to image.Relative, if image analysis result is not correct, return to step
S210, and the view data of picture frame is extracted, and the action of the view data progress graphical analysis for next picture frame (frame).
Fig. 3~Fig. 7 is refer on above-mentioned graphical analysis mode, Fig. 3~Fig. 7 shows a variety of different images point respectively
The schematic diagram of analysis mode.It please join reference picture 3, graphical analysis mode in figure 3 is Statistics Method.Wherein, Statistics Method
It is to obtain image analysis result by calculating the change metachromatic state between the grey decision-making of more several pixels of the view data.To adhere to separately
The fingerprint image 311 and landscape image 321 of variety classes image are example, and fingerprint image 311 and landscape image 321 are divided
Its grey decision-making bar chart 312 and 322 corresponding with pixel is not corresponded to.By bar chart 312 and 322 it is known that fingerprint image 311
Pixel grey decision-making between the change metachromatic state pixel that is greater than landscape image 321 grey decision-making between change metachromatic state.Also because
This, can be by setting a default variation value, and when above-mentioned change metachromatic state is more than default variation value, corresponding graphical analysis
As a result it is the first species image that fingerprint image 311, which can be represented, relative, when above-mentioned change metachromatic state is not more than default variation value,
Corresponding image analysis result can represent that landscape image 321 is second species image.
Above-mentioned change metachromatic state can obtain standard deviation and/or average value to obtain by calculating the grey decision-making of pixel.
Default variation value is a value set in advance, and designer can be according to the distribution of the change metachromatic state of variety classes image
State sets default variation value, and using Fig. 3 embodiment as example, such as fingerprint image 311 is calculated by standard deviation
Change metachromatic state into 97, and the change metachromatic state that such as landscape image 321 is calculated by standard deviation is 64, and presetting variation value can
The numerical value being set as between 97 and 64.
Then Fig. 4 is refer to, graphical analysis mode in Fig. 4 is signature analysis.Wherein, signature analysis are used for dividing
Whether analysis image is circular or ellipse.Exemplified by carrying out signature analysis for fingerprint image 411, first for fingerprint image
411 progress binary conversion treatments simultaneously obtain the binary image data of binaryzation fingerprint image 412, then by binaryzation fingerprint image
As 412 actions for carrying out shape analysis, the external form that can learn image 413 is ellipse.That is, pass through signature analysis
Graphical analysis mode, it can be determined that it is the first species image to go out fingerprint image 411.
In addition, exemplified by carrying out signature analysis for landscape image 421, first binaryzation is carried out for landscape image 421
Handle and obtain the binary image data of binaryzation landscape image 422, then by carrying out shape to binaryzation landscape image 422
The action of analysis, can learn the external form of image 423 it is non-be it is circular also non-be ellipse.That is, pass through signature analysis
Graphical analysis mode, it can be determined that it is second species image to go out landscape image 421.
Subsidiary one carries, and above-mentioned binary conversion treatment and the mode of shape analysis be that image processing field has usual knowledge
Technology known to person, related details is pardoned herein seldom to be repeated.
Fig. 5 is refer to below, and graphical analysis mode in Figure 5 is Spectral Analysis Method.Below to be directed to fingerprint image respectively
As 511 and landscape image 521 carry out analysis and are illustrated for example.Wherein, first for fingerprint image 511 and landscape figure
The conversion of landscape image 522 after carrying out digital Fourier transforms as 521 with fingerprint image 512 after change respectively and change
View data afterwards.Binary conversion treatment is carried out for above-mentioned converted images data to obtain spectrum analysis fingerprint image respectively again
513 and the spectrum analysis view data of spectrum analysis landscape image 523.View data is analyzed by analysis spectrum, to judge
Picture element density in one regional extent of spectrum analysis fingerprint image 513 and spectrum analysis landscape image 523, can learn finger
Print image 511 and landscape image 521 are the first species image or second species image respectively.Wherein, can be understood by Fig. 5
See, the pixel of spectrum analysis fingerprint image 513 has zonal, and the pixel of spectrum analysis fingerprint image 523 is then to spread
In whole image region, thus, it is possible to judge that fingerprint image 511 and landscape image 521 are the first familygram respectively
Picture and second species image.
Fig. 6 is refer to below, and graphical analysis mode in figure 6 is vector analysis.With for fingerprint image 611 and
It is example that landscape image 612, which carries out vector analysis, first, rim detection is carried out for fingerprint image 611 and landscape image 612
And edge strengthening image 621 and 622 is obtained, then carry out for edge strengthening image 612 and 622 filling out hole (fill hole)
Or grid (grid) processing is with image 613 and 623 after handle respectively, finally respectively for image 613 after handling and
623 carry out vector detection, to use image analysis result corresponding to acquisition.Wherein, after for the processing of corresponding fingerprint image 611
Image 613 carries out vector detection it can be found that the pixel distribution after processing in image 613 is that tool is directive (around fingerprint
Center), and the pixel distribution after the processing of corresponding landscape image 621 in image 623 be it is in disorder without directionality, therefore,
By vector detection results can specifically learn fingerprint image 611 and landscape image 612 be respectively the first species image and
Second species image.
Fig. 7 is refer to below, and graphical analysis mode in the figure 7 is context analyzer method.Wherein, context analyzer method is carried out
When, it can receive and keep in the fingerprint image 711~713 of different picture frames (such as continuous picture frame) with the more several pending images of acquisition
Data, and the difference for calculating two pending view data of adjacent picture frame in these pending view data is divided to obtain image
Result is analysed, the characteristic being widely varied, two pending view data of above-mentioned adjacent picture frame will not be produced based on fingerprint image
Difference can be a very little numerical value, thereby, it can be determined that it is the first species image to go out fingerprint image 711~713.Relatively
, when receive and keep in for landscape image 721~723 when, the difference meeting of two pending view data of adjacent picture frame
It is a relatively large numerical value, also therefore may determine that landscape image 721~723 is second species image.
Fig. 8 is refer to below, and Fig. 8 shows the schematic diagram of the image processing apparatus of one embodiment of the invention.Image procossing fills
Putting 800 includes image extractor 810 and controller 820.Image extractor 810 is, for example, CMOS OPTICAL SENSORSs, CCD light sensings
To extract image to obtain view data, controller 820 couples image extractor 810, control for device or thin film phototransistor
Device 820 selects to perform at least one in multiple images processing routine according to the species of view data, and passes through at least one
The image processing program processing view data of execution.In more detail, controller 820 couples the image extractor 810.Controller
820 to provide at least two pre-set image data class, and at least two pre-set image data class correspond respectively to an at least image
Processing routine, and to according to the species of the view data be pre-set image data class which, come select perform should
A corresponding at least image processing program, to handle the view data.
Controller 820 can be, for example, microprocessor collocation software or firmware program, or be portable electronic devices
Processing unit.Wherein, image processing program includes feature identification program 831 and graphic joining program 832, and controller 820 can
Species selection according to view data performs feature identification program 831 or graphic joining program 832 is come to the institute of image extractor 810
The image of extraction carries out the action of image procossing.Image processing program can also include more different programs, to correspond to not
Congener image, such as information of the Three-Dimensional Bar Code decoding program described in interpretation Three-Dimensional Bar Code image.Card information is deposited
Program is stored up to recognize the image of business card species, and stores the contact information of business card.Image processing program can be stored in figure
As processing unit storage media in.
Implementation detail on image processing apparatus 800 has specifically in above-mentioned multiple embodiments and embodiment
It is bright, seldom repeated with following.
In summary, the present invention is by analyzing the species of image, and automatically according to the species of image come corresponding to selecting one
Individual or multiple images processing routine, suitable image procossing action is carried out to image.Consequently, it is possible to the processing action of image can
With the completion of automation, improve and use upper convenience.
Claims (15)
1. a kind of image processing method, including：
There is provided at least two pre-set image data class, and this at least two pre-set image data class correspond respectively to an at least figure
As processing routine；
One view data is obtained by an image extractor；
It is which of pre-set image data class according to the species of the view data, to select to perform a corresponding at least figure
As processing routine, to handle the view data；
The image processing method also includes：Entered using at least one in multiple images analysis method for the view data
Row is analyzed to obtain the species of the view data；
It is more using this wherein to carry out analysis for the view data using at least one in multiple images analysis method
At least two image analysis method is analyzed the view data and produces corresponding divide in individual image analysis method
Result is analysed, the image processing method also includes：
According to whether those image analysis results are consistent to judge whether those image analysis results are correct；
When those image analysis results are correct, select to perform in those image processing programs according to the image analysis result
At least one；And
When those image analysis results are not correct, analyzed for the image of next picture frame.
2. image processing method as claimed in claim 1, wherein those image analysis methods include a Statistics Method, the number
Manage the change metachromatic state between the grey decision-making of more several pixels of the statistic law including calculating the view data.
It is corresponding to be somebody's turn to do 3. image processing method as claimed in claim 2, wherein the change metachromatic state are more than a default variation value
Image analysis result represents that the image is one first species image, corresponding when the change metachromatic state is no more than the default variation value
The image analysis result represents that the view data is a second species image.
4. image processing method as claimed in claim 2, wherein the change metachromatic state are according to the grey decision-making for calculating those pixels
Average value and/or standard deviation obtain.
5. image processing method as claimed in claim 1, wherein those image analysis methods include a signature analysis, the figure
Conformal analysis method is judging whether the shape of the image in the image is circular or ellipse.
6. image processing method as claimed in claim 5, wherein being shaped as circular or ellipse when the image in the image
When, the corresponding image analysis result represents that the view data is one first species image, when the shape of the image in the image
It is non-for it is circular or oval when, the corresponding image analysis result represents that the view data is a second species image.
7. image processing method as claimed in claim 6, the wherein signature analysis include：
Binary conversion treatment is carried out for the view data, and uses and obtains a binary image data；And
The corresponding image analysis result is produced according to the binary image data.
8. image processing method as claimed in claim 1, wherein those image analysis methods include a Spectral Analysis Method, the frequency
Spectrum analytic approach includes：
A digital Fourier transform is carried out for the view data to obtain a converted images data；And
Binary conversion treatment is carried out for the converted images data to obtain a spectrum analysis view data；And
The picture element density in the regional extent in the spectrum analysis view data is judged to obtain the corresponding graphical analysis knot
Fruit.
9. image processing method as claimed in claim 1, wherein those image analysis methods include a vector analysis, this to
Amount analytic approach includes：
Rim detection is carried out for the image and obtains an edge strengthening image；
Carry out filling out hole or grid processing for the edge strengthening image to obtain image after a processing；And
Vector detection is carried out for image after the processing, and uses the image analysis result corresponding to acquisition.
, should 10. image processing method as claimed in claim 1, wherein those image analysis methods include a context analyzer method
Context analyzer method includes：
Receive and keep in the images of more several continuous picture frames to obtain more several pending view data；
More several differences of two pending view data of adjacent picture frame in those pending view data are calculated respectively；And
The image analysis result corresponding to being obtained according to those differences.
11. image processing method as claimed in claim 1, wherein this at least two pre-set image data class include fingerprint image
Wantonly two species of species, document image species, Three-Dimensional Bar Code image species and business card image species wherein at least.
12. image processing method as claimed in claim 11, wherein processing routine corresponding to the fingerprint image species are characterized
Processing routine corresponding to identification program, this document image species is graphic joining program, corresponding to the Three-Dimensional Bar Code image species
Processing routine be bar code image interpretation program and the business card image species corresponding to processing routine be card information storage program.
13. a kind of image processing apparatus, including：
One image extractor, to obtain a view data；
One controller, the image extractor is coupled, to provide at least two pre-set image data class, at least two pre-set images
Data class corresponds respectively to an at least image processing program, and being pre-set image number according to the species of the view data
According to species which, to select to perform a corresponding at least image processing program, to handle the view data；
Wherein the controller also to using at least one in multiple images analysis method for the view data carry out
Analyze to obtain the species of the view data；And
Wherein the controller also to using at least one in multiple images analysis method for the view data carry out
Analyze to be analyzed simultaneously the view data using at least two image analysis method in the plurality of image analysis method
And analysis result corresponding to producing, the controller were also included according to two whether being consistent at least within those image analysis results
To judge whether those image analysis results are correct, when those image analysis results are correct, the controller is according to the image
Analysis result selection performs at least one in those image processing programs, when those image analysis results are not correct
When, the controller is analyzed for the image of next picture frame.
14. image processing apparatus as claimed in claim 13, wherein this at least two pre-set image data class include fingerprint image
As species, document image species, wantonly two species of Three-Dimensional Bar Code image species and business card image species wherein at least.
15. image processing apparatus as claimed in claim 14, wherein processing routine corresponding to the fingerprint image species are characterized
Processing routine corresponding to identification program, this document image species is graphic joining program, corresponding to the Three-Dimensional Bar Code image species
Processing routine be bar code image interpretation program and the business card image species corresponding to processing routine be card information storage program.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW103114831A TWI525555B (en) | 2014-04-24 | 2014-04-24 | Image processing apparatus and processing method thereof |
| TW103114831 | 2014-04-24 |
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| CN104239873B true CN104239873B (en) | 2018-01-19 |
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Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105389541B (en) * | 2015-10-19 | 2018-05-01 | 广东欧珀移动通信有限公司 | The recognition methods of fingerprint image and device |
| CN105653152A (en) * | 2015-12-23 | 2016-06-08 | 北京金山安全软件有限公司 | Picture processing method and device and electronic equipment |
| CN105718839B (en) * | 2016-01-27 | 2018-01-30 | 苏州佳世达电通有限公司 | Bar code decoding method and bar code decoding device |
| US10192097B2 (en) | 2016-04-20 | 2019-01-29 | Novatek Microelectronics Corp. | Finger print detection apparatus and detection method thereof |
| CN107786867A (en) * | 2016-08-26 | 2018-03-09 | 原相科技股份有限公司 | Image identification method and system based on deep learning architecture |
| US10726573B2 (en) | 2016-08-26 | 2020-07-28 | Pixart Imaging Inc. | Object detection method and system based on machine learning |
| TWI620167B (en) * | 2017-07-18 | 2018-04-01 | 友達光電股份有限公司 | Display device and driving method thereof |
| CN109063547B (en) * | 2018-06-13 | 2021-10-08 | 中山大学中山眼科中心 | Cell type identification method based on deep learning |
| TWI722297B (en) * | 2018-06-28 | 2021-03-21 | 國立高雄科技大學 | Internal edge detection system and method thereof for processing medical images |
| TWI828397B (en) * | 2021-11-18 | 2024-01-01 | 東陽實業廠股份有限公司 | Intelligent transparent shading system |
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| CN102034083A (en) * | 2009-09-25 | 2011-04-27 | 神基科技股份有限公司 | Method for identifying bar code |
| CN102298533A (en) * | 2011-09-20 | 2011-12-28 | 宇龙计算机通信科技(深圳)有限公司 | Method for activating application program and terminal equipment |
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| US20080317346A1 (en) * | 2007-06-21 | 2008-12-25 | Microsoft Corporation | Character and Object Recognition with a Mobile Photographic Device |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102034083A (en) * | 2009-09-25 | 2011-04-27 | 神基科技股份有限公司 | Method for identifying bar code |
| CN102298533A (en) * | 2011-09-20 | 2011-12-28 | 宇龙计算机通信科技(深圳)有限公司 | Method for activating application program and terminal equipment |
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| TWI525555B (en) | 2016-03-11 |
| CN104239873A (en) | 2014-12-24 |
| TW201541364A (en) | 2015-11-01 |
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