CN106344073A - saliva image identification method for predicting female ovulation period - Google Patents
saliva image identification method for predicting female ovulation period Download PDFInfo
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- 210000003296 saliva Anatomy 0.000 title claims abstract description 88
- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000016087 ovulation Effects 0.000 title claims description 44
- 230000000624 ovulatory effect Effects 0.000 claims abstract description 21
- 238000005457 optimization Methods 0.000 claims description 12
- 238000003909 pattern recognition Methods 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 238000003066 decision tree Methods 0.000 claims description 8
- 238000005065 mining Methods 0.000 claims description 8
- 238000003708 edge detection Methods 0.000 claims description 7
- 241001494479 Pecora Species 0.000 claims description 5
- 230000009466 transformation Effects 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 3
- 230000035558 fertility Effects 0.000 abstract description 4
- 238000001514 detection method Methods 0.000 description 8
- 238000004458 analytical method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000036760 body temperature Effects 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000002175 menstrual effect Effects 0.000 description 1
- 230000027758 ovulation cycle Effects 0.000 description 1
- 210000002700 urine Anatomy 0.000 description 1
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Abstract
The invention discloses a saliva image identification method for predicting the ovulatory period of a woman, which comprises an image obtaining step, an image optimizing step, an image binarization step and a pattern identification step, and can be used for simply, quickly, safely and accurately and automatically detecting and analyzing the saliva image of the woman and automatically judging whether the woman is in one of a non-ovulatory period, a possible ovulatory period and an ovulatory period according to the saliva image, thereby helping a user to predict the ovulatory period and further obtain the control right of independent fertility or birth control.
Description
Technical field
The present invention is relevant with a kind of saliva image recognition method, particularly relates to a kind of saliva image recognition method for forecasting ovulatory period of woman.
Background technology
Generally speaking, the menstrual cycle of women is about 27 to 30, wherein, menstrual phase lasts about 3 to 7, and the onset of ovulation then lasts about greatly 6, therefore in order to the detection of ovulation phase is to obtain fertility or birth control control, it is in the streets to develop basal body temperature method, vaginal secretionies analysis and several detection modes such as urine detection, and in numerous detection modes, saliva is detected as a newer technology, its crystalline pattern mainly by the saliva that sees drying, to distinguish the ovulation state of saliva owner, pointed out according to existing research data, this crystalline pattern can be distinguished into point-like, half fern shape and full fern shape, and correspond to the non-onset of ovulation of women respectively, the possible onset of ovulation and the onset of ovulation.
But existing saliva detection mode, mostly it is that saliva is coated microscope slide, observed by microscope again and identified, not only operate inconvenience, and its identification success rate depends on distinguishing the experience of the knowledgeable, it is therefore to have dealer to develop United States Patent (USP) such as to disclose us20080255472 patent, it discloses regular acquisition one saliva image, and carry out image binary conversion treatment, this saliva video conversion is become a binaryzation image, then analyze the black picture element density of this binaryzation image, and record and be depicted as a Statistics of Density curve chart, whereby, make saliva owner can pass through this Statistics of Density curve chart, understand the ovulation state of oneself.
But above-mentioned patent adopts the mode defining pixel gray level value filtering the noises such as the noise in image, easily there is the situation of erroneous judgement, lead to identification success rate not good, and saliva owner is only capable of observing understanding ovulation state by this Statistics of Density curve chart afterwards, and cannot immediately learn ovulation state at that time.
Content of the invention
In order to solve above-mentioned technical problem, the present invention provides a kind of saliva image recognition method for forecasting ovulatory period of woman, it is available for the saliva image of simple, quick, safety and automatic detection analysis women exactly, and the ovulation state by this saliva image this women of automatic decision.
For reaching above-mentioned purpose, saliva image recognition method for forecasting ovulatory period of woman provided by the present invention, include the following step: an acquirement image step, obtain one using an image capture unit shooting and saliva image is dried, and process through image gray scaleization, this is dried saliva video conversion and becomes a GTG saliva image；And one optimization image step, remove the noise of this GTG saliva image using wave filter, and strengthen the image detail of this GTG saliva image；And an image binarization step, set a threshold values, and the grey decision-making of each pixel of this GTG saliva image and this threshold values are compared, if the grey decision-making of this pixel is less than or equal to this threshold values, then defining this pixel is black pixel, if and the grey decision-making of this pixel is higher than this threshold values, defining this pixel is white pixel, obtains a binaryzation image whereby；Also have a Pattern recognition step, this binaryzation image analyzed by a decision mechanism, and automatically judge this binaryzation image as image non-onset of ovulation, may the onset of ovulation image and the image onset of ovulation one of them.
Preferably, wherein, this decision mechanism adopts the white pixel density analyzing this binaryzation image being judged.
Preferably, wherein, set one first threshold value and one second threshold value, when this white pixel density is less than this first threshold value, then judge this binaryzation image as image non-onset of ovulation, and work as this white pixel density between this first threshold value and this second threshold value, then judge this binaryzation image as may the onset of ovulation image, and this white pixel density is higher than this second threshold value, then judge this binaryzation image as the image onset of ovulation.
Preferably, wherein, this decision mechanism is judged by the way of Date Mining.
Preferably, wherein, Date Mining is carried out using decision tree classification.
Preferably, wherein, in the saliva image by tool sheep toothed pattern, extract six line segment features such as total segment, long line segment, short-term section, the percentage ratio of parallel segment, the percentage ratio of long line segment and parallel segment to set up a decision tree.
Preferably, wherein, between this acquirement image step and this optimization image step, further include an image Cut out step, this GTG saliva image is carried out with locking and the cutting of particular block, so as to reducing the data quantity of this GTG saliva image.
Preferably, wherein, between this optimization image step and this image binarization step, further include an edge detection step, edge detection process is carried out to this GTG saliva image, indicate the obvious pixel of GTG value changes in image to search.
Preferably, wherein, between this image binarization step and this Pattern recognition step, further include an image graph thinning step, the white pixel of this binaryzation image is simplified to the graph thinning image that width is 1 pixel, and between this image graph thinning step and this Pattern recognition step, further includes a feature extraction step, this graph thinning image execution Hough transformation is processed, to capture the edge feature included in image.
Preferably, wherein, in this optimization image step, the noises such as the speckle noise of this GTG saliva image are removed using a median filter, and a height increases wave filter to suppress low frequency information, strengthen the edge feature of this GTG saliva image whereby, make image detail sharpened.
Saliva image recognition method for forecasting ovulatory period of woman provided by the present invention, by this acquirement image step, this optimization image step, this image binarization step and this Pattern recognition step, can simply, the saliva image of quick, safety and automatic detection analysis women exactly, and by this saliva this women of image automatic decision be in the non-onset of ovulation, may the onset of ovulation and the onset of ovulation one of them, whereby, must help the user predicting ovulation phase, and then obtain the control of autonomous fertility or birth control.
Brief description
Fig. 1 is the schematic flow sheet of first preferred embodiment of the present invention.
Fig. 2 is the schematic flow sheet of second preferred embodiment of the present invention.
Fig. 3 is the schematic flow sheet of the 3rd preferred embodiment of the present invention.
Fig. 4 is the schematic flow sheet of the 4th preferred embodiment of the present invention.
Specific embodiment
The invention will be further described with specific embodiment below in conjunction with the accompanying drawings, so that those skilled in the art can be better understood from the present invention and can be practiced, but illustrated embodiment is not as a limitation of the invention.
Refer to shown in Fig. 1, be the schematic flow sheet of first preferred embodiment of the present invention, its exposure has a kind of saliva image recognition method for forecasting ovulatory period of woman, this saliva image recognition method includes the following step:
One acquirement image step, obtains one using an image capture unit shooting and saliva image is dried, and process through image gray scaleization, this is dried saliva video conversion and becomes a GTG saliva image.
One optimization image step, is removed the noise of this GTG saliva image, and strengthens the image detail of this GTG saliva image using wave filter.
One image binarization step, set a threshold values, and the grey decision-making of each pixel of this GTG saliva image and this threshold values are compared, if the grey decision-making of this pixel is less than or equal to this threshold values, then defining this pixel is black pixel, if and the grey decision-making of this pixel is higher than this threshold values, defining this pixel is white pixel, obtains a binaryzation image whereby.
One Pattern recognition step, analyzes this binaryzation image by a decision mechanism, and automatically judge this binaryzation image as image non-onset of ovulation, may the onset of ovulation image and the image onset of ovulation one of them.
Please continue to refer to shown in Fig. 1, the saliva image recognition method of the present invention mainly uses matlab software to be carried out, its steps flow chart is as follows, need to be obtained this using this image capture unit shooting first by person and saliva image is dried, wherein, this image capture unit can be general mobile phone, it is easy to user whereby to be shot whenever and wherever possible, or the instrumentation developed for this saliva filming image, thereby ensure that the correctness of image capture, here is not intended to limit the mode that user obtains this and saliva image is dried.
Image gray scaleization is utilized to process afterwards, this is dried saliva video conversion and becomes this GTG saliva image, and the noise of this GTG saliva image is removed using wave filter, and strengthen the image detail of this GTG saliva image, in the present embodiment, it is to remove the noises such as the speckle noise of this GTG saliva image using a median filter, further low frequency information is suppressed using a high wave filter that increases, strengthen the edge feature of this GTG saliva image whereby, make image detail sharpened.
Then again binary conversion treatment is carried out to this GTG saliva image, its processing mode is to be compared the grey decision-making of each pixel of this GTG saliva image and this threshold values, if the grey decision-making of this pixel is less than or equal to this threshold values, then define this pixel be black pixel, and if the grey decision-making of this pixel be higher than this threshold values, define this pixel be white pixel, obtain this binaryzation image whereby, wherein, this threshold values by user self-defining, or can be automatically selected with noise according to the edge message in image.
Finally again this binaryzation image is analyzed by this decision mechanism，And automatically judge this binaryzation image as image non-onset of ovulation、Possible onset of ovulation image and the image onset of ovulation one of them，In the present embodiment，This decision mechanism is the quantity using this white pixel，Can get over characteristic that is notable and increasing with the sheep toothed pattern of saliva image，Adopt by the number of white pixels in image divided by black pixel and white pixel quantity summation，To calculate the white pixel density of this binaryzation image，Then this white pixel density is compared with one first threshold value set in advance and one second threshold value，If this white pixel density is less than this first threshold value，Then judge this binaryzation image as image non-onset of ovulation，And if this white pixel density is between this first threshold value and this second threshold value，Then judge this binaryzation image as the possibility image onset of ovulation，And if this white pixel density is higher than this second threshold value，Then judge this binaryzation image as the image onset of ovulation，Wherein，This first threshold value and this second threshold value can be different and change according to the body constitution of user，Therefore this first threshold value and this second threshold value can be by user self-definings，Or the ovulation state of follow-up analysis user for a period of time after，Automatically define according to acquired statistical data.
Whereby, make the saliva image recognition method of the present invention, can simply, the saliva image of quick, safety and automatic detection analysis women exactly, and by this saliva this women of image automatic decision be in the non-onset of ovulation, may the onset of ovulation and the onset of ovulation one of them, and the user predicting ovulation phase can be helped, and then obtain the control of autonomous fertility or birth control.
Please refer to again shown in Fig. 2 simultaneously, it is the schematic flow sheet of second preferred embodiment of the present invention, this saliva image recognition method is with aforementioned first preferred embodiment difference, between this optimization image step and this image binarization step, further include an edge detection step, edge detection process is carried out to this GTG saliva image, indicate the obvious pixel of GTG value changes in image first to search, so that when subsequently carrying out this image binarization step, make the edge feature of this binaryzation image more clean and obvious, and accuracy during Pattern recognition can be lifted, wherein, this edge detection processes and can adopt sobel, canny, the one of which computing mode such as prewitt is carried out, in the present embodiment, using sobel computing mode.
Please refer to again shown in Fig. 3 simultaneously, it is the schematic flow sheet of the 3rd preferred embodiment of the present invention, this saliva image recognition method is with aforementioned second preferred embodiment difference, between this acquirement image step and this optimization image step, further include an image Cut out step, this GTG saliva image is carried out with locking and the cutting of particular block, so as to reducing the data quantity of this GTG saliva image, to lift the speed of overall image computing, and reach the effect reducing False Rate.
Please refer to again shown in Fig. 4 simultaneously，It is the schematic flow sheet of the 4th preferred embodiment of the present invention，This saliva image recognition method is with aforementioned 3rd preferred embodiment difference，Between this image binarization step and this Pattern recognition step，Further include an image graph thinning step，The white pixel of this binaryzation image is simplified to the graph thinning image that width is 1 pixel，And between this image graph thinning step and this Pattern recognition step，Further include a feature extraction step，This graph thinning image execution Hough transformation is processed，To capture the edge feature included in image，This decision mechanism is then adopted the mode of Date Mining and is judged simultaneously，Wherein，The mode of Date Mining can adopt bayesian classification、Class neural network is classified、The one way in which such as decision tree classification are carried out，In the present embodiment，Date Mining is carried out using decision tree classification，Its specific embodiment is exemplified below described in section.
Because sheep toothed pattern is mainly constituted with a plurality of short-term section by staggered or parallel a plurality of long line segment, therefore can be first by the saliva image having sheep toothed pattern, extract six line segment features, i.e. total segment, long line segment, short-term section, parallel segment, the percentage ratio of long line segment and the percentage ratio of parallel segment, and above-mentioned line segment feature is created as a decision tree using the j48 classification of weka software, as long as so by the above-mentioned node comparing this decision tree through the edge feature that Hough transformation captures, the line segment feature of this graph thinning image can be gone out by Fast Identification, and it is judged as image non-onset of ovulation further, possible onset of ovulation image and the image onset of ovulation one of which, whereby, identification success rate can be improved by the mode of Date Mining further.
Embodiment described above is only the preferred embodiment lifted for absolutely proving the present invention, protection scope of the present invention not limited to this.Equivalent substitute or conversion that those skilled in the art are made on the basis of the present invention, all within protection scope of the present invention.Protection scope of the present invention is defined by claims.
Claims (10)
1. a kind of saliva image recognition method for forecasting ovulatory period of woman is it is characterised in that include the following step:
One acquirement image step, obtains one using an image capture unit shooting and saliva image is dried, and process through image gray scaleization, this is dried saliva video conversion and becomes a GTG saliva image；
One optimization image step, is removed the noise of this GTG saliva image, and strengthens the image detail of this GTG saliva image using wave filter；
One image binarization step, set a threshold values, and the grey decision-making of each pixel of this GTG saliva image and this threshold values are compared, if the grey decision-making of this pixel is less than or equal to this threshold values, then defining this pixel is black pixel, if and the grey decision-making of this pixel is higher than this threshold values, defining this pixel is white pixel, obtains a binaryzation image whereby；
One Pattern recognition step, analyzes this binaryzation image by a decision mechanism, and automatically judge this binaryzation image as image non-onset of ovulation, may the onset of ovulation image and the image onset of ovulation one of them.
2. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 1 it is characterised in that this decision mechanism is to be judged using the white pixel density analyzing this binaryzation image.
3. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 2, it is characterized in that, set one first threshold value and one second threshold value, when this white pixel density is less than this first threshold value, then judge this binaryzation image as image non-onset of ovulation, and work as this white pixel density between this first threshold value and this second threshold value, then judge this binaryzation image as the possibility image onset of ovulation, and this white pixel density is higher than this second threshold value, then judge this binaryzation image as the image onset of ovulation.
4. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 1 it is characterised in that this decision mechanism is judged by the way of Date Mining.
5. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 4 it is characterised in that Date Mining is carried out using decision tree classification.
6. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 5, it is characterized in that, in saliva image by tool sheep toothed pattern, extract six line segment features such as total segment, long line segment, short-term section, the percentage ratio of parallel segment, the percentage ratio of long line segment and parallel segment to set up a decision tree.
7. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 1, it is characterized in that, between this acquirement image step and this optimization image step, further include an image Cut out step, this GTG saliva image is carried out with locking and the cutting of particular block, so as to reducing the data quantity of this GTG saliva image.
8. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 1, it is characterized in that, between this optimization image step and this image binarization step, further include an edge detection step, edge detection process is carried out to this GTG saliva image, indicates the obvious pixel of GTG value changes in image to search.
9. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 4, it is characterized in that, between this image binarization step and this Pattern recognition step, further include an image graph thinning step, the white pixel of this binaryzation image is simplified to the graph thinning image that width is 1 pixel, and between this image graph thinning step and this Pattern recognition step, further include a feature extraction step, this graph thinning image execution Hough transformation is processed, to capture the edge feature included in image.
10. according to the saliva image recognition method for forecasting ovulatory period of woman described in claim 1, it is characterized in that, remove the noises such as the speckle noise of this GTG saliva image in this optimization image step using a median filter, and one high increase wave filter to suppress low frequency information, strengthen the edge feature of this GTG saliva image whereby, make image detail sharpened.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW104122967 | 2015-07-15 | ||
| TW104122967A TWI569766B (en) | 2015-07-15 | 2015-07-15 | A method for predicting saliva image recognition in female ovulation |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI676456B (en) * | 2018-08-02 | 2019-11-11 | 林渝宸 | An image recognition method for ovulation detection |
| CN112305208A (en) * | 2020-10-22 | 2021-02-02 | 言谱物(杭州)智能科技有限责任公司 | Female physiological cycle detection device and system |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI701640B (en) * | 2019-04-26 | 2020-08-11 | 林渝宸 | Ovulation prediction method based on saliva crystallization |
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2015
- 2015-07-15 TW TW104122967A patent/TWI569766B/en not_active IP Right Cessation
- 2015-08-05 CN CN201510473229.1A patent/CN106344073A/en active Pending
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI676456B (en) * | 2018-08-02 | 2019-11-11 | 林渝宸 | An image recognition method for ovulation detection |
| CN112305208A (en) * | 2020-10-22 | 2021-02-02 | 言谱物(杭州)智能科技有限责任公司 | Female physiological cycle detection device and system |
Also Published As
| Publication number | Publication date |
|---|---|
| TWI569766B (en) | 2017-02-11 |
| TW201701837A (en) | 2017-01-16 |
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