CN101966083A - Abnormal skin area calculation system and calculation method thereof - Google Patents
Abnormal skin area calculation system and calculation method thereof Download PDFInfo
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Abstract
The invention discloses an abnormal skin area calculation system and a calculation method thereof. The database stores at least one abnormal skin analysis data in advance, and the skin analysis module analyzes by using the abnormal skin analysis data and marks an abnormal skin area graph included in the skin image. The numerical operation module calculates the pixel area of the abnormal skin area graph, and then calculates the actual area of the abnormal skin area corresponding to the human skin according to an area correction parameter. The area correction parameter is pre-stored in the database, or generated by the numerical operation module according to a correction object graph included in the skin image and calculating the conversion relation between the reference length unit and the pixel distance unit.
Description
Technical field
The present invention system is about a kind of unusual skin analysis system and method thereof, particularly about a kind of unusual part of analyzing skin and calculate the unusual skin area computing system and the method thereof of its corresponding surface product value.
Background technology
In the prior art, existing skin doctor is judged sufferer, and to suffer from unusual skin disorder (thick as burn, scald, speckle, cutin skin, white macula, pore ... Deng) time, the normal skin medical skill of using is for utilizing the unusual skin of low-energy laser irradiation, during generally because of the low-energy laser irradiation human body skin, can't damage health, so have higher safety, belong to relatively mild therapeutic modality.
Yet skin doctor carries out medical treatment when valuation, and collecting of expense is that reputation, sensation, range estimation area size according to the doctor comes patient is charged.The standard of valuation is by doctor individual decision fully, and a comparatively objective charging way is not arranged.And the areal extent of unusual skin that both sides estimate also has the difference on numerical value and the sense organ, makes doctor and sufferer cause more easily on charging system that both sides are cognitive to be misread, and then produces unnecessary medical tangle.
So how unusual skin range computation device system is provided comparatively accurately, the problem that should ponder over for manufacturer.
Summary of the invention
It is a kind of in order to calculate the computing system and the computational methods of actual unusual skin distributed areas area that the problem system that desire of the present invention solves provides.
For solving the said system problem, the present invention system provides a kind of unusual skin area computing system, and it comprises a taking module, a data base, a skin analysis module and a numerical operation module.At least one unusual skin analysis data of the pre-storage of data base, taking module is used to take a human body skin and produces a skin image.The skin analysis module utilizes above-mentioned unusual skin analysis data that the skin image is performed an analysis, and obtains the skin image and comprises unusual skin area figure.The numerical operation module then is used to calculate the elemental area of unusual skin area figure, utilizes an area correction parameter to calculate the real area of the pairing human body skin of unusual skin area figure.
Unusual skin area computing system provided by the present invention, skin analysis module system utilizes the switch technology of rgb color image and HSV color image, the saturation of cooperation adjustment HSV and lightness adjustment technology are used and are obtained unusual skin area figure to adjust the skin image.
Unusual skin area computing system provided by the present invention, skin analysis module system utilizes the combinations of one formation at least such as figure gray scale technique, binaryzation technology, boundary extraction rule and rim detection rule, uses and obtains unusual skin area figure.
Unusual skin area computing system of the present invention, its correction thing that more disposes a known yardstick produce the skin image with correction thing figure when taking module is taken in the coverage of taking module.The numerical operation module is then resolved and is proofreaied and correct yardstick that the thing figure presents to obtain a reference length unit, calculates the area correction parameter of reference length unit and pixel distance unit by this.
Unusual skin area computing system of the present invention, its area correction parameter comprises the distance of taking module and human body skin, and the calibration shift parameter of corresponding pixel distance unit and actual range unit.
For solving the said method problem, the present invention system provides a kind of unusual skin area computational methods, and it comprises: utilize a taking module to take a human body skin to produce a skin image; Go out the skin image by a skin analysis module analysis and comprise unusual skin area figure; Calculate the elemental area of unusual skin area figure by a numerical operation module; And utilize an area correction parameter to calculate the real area of unusual skin area figure corresponding to human body skin by the numerical operation module.
Unusual skin area computational methods of the present invention, skin analysis module system utilizes rgb color video conversion technology or HSV color image switch technology to adjust the skin image, uses and obtains unusual skin area figure.
Unusual skin area computational methods of the present invention, skin analysis module system utilizes the combinations of one formation at least such as figure gray scale technique, binaryzation technology, boundary extraction rule and rim detection rule, uses and obtains unusual skin area figure.
Unusual skin area computational methods of the present invention, its correction thing that more disposes a known yardstick produce the skin image with correction thing figure when taking module is taken in the coverage of taking module.The yardstick that numerical operation module parses correction thing figure presents calculates the area correction parameter of reference length unit and pixel distance unit by this to obtain a reference length unit.
Unusual skin area computing system of the present invention, its area correction parameter comprises the distance of taking module and human body skin, and the calibration shift parameter of the pixel distance unit of correspondence and actual range unit.
Characteristics of the present invention are to be system provided by the invention and method thereof system in order to calculate unusual comparatively accurately skin distribution area, so provide doctor and sufferer both sides one more reliably, more not disputed objective value.The doctor can also can promote the mutual trust degree between doctor and the sufferer according to these type of data to set up or to provide rational expenses standard to give sufferer, is of value to the enhancement doctor and cures the efficient of unusual skin.Moreover system and method provided by the invention more can write down each the skin medical treatment area and the skin of sufferer and cure area, to provide the doctor as the comparable data of curing sufferer one by one in conjunction with existing medical resume technology.
Description of drawings
Fig. 1 is the unusual skin area computing system of a present invention embodiment system block diagrams;
Fig. 2 A is the unusual skin area computational methods of a present invention embodiment schematic flow sheet;
Fig. 2 B is the thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S120;
Fig. 2 C is the thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S123;
Fig. 2 D is another thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S120;
Fig. 2 E is the thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S1203;
Fig. 2 F is another thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S1203;
Fig. 3 A is an one of embodiment of the invention skin image example;
Fig. 3 B is the unusual skin area figure of embodiment of the invention corresponding diagram 3A;
Fig. 3 C is another example of embodiment of the invention skin image;
Fig. 3 D is the unusual skin area figure of embodiment of the invention corresponding diagram 3C;
Fig. 4 A is that embodiment of the invention GTG figure changes sketch map;
Fig. 4 B is an embodiment of the invention image capture sketch map;
Fig. 5 A and Fig. 5 B are that the embodiment of the invention is chosen grey-tone image threshold values sketch map;
Fig. 5 C is that the binaryzation image of the embodiment of the invention forms and unusual skin area graphic sketch map; And
Fig. 6 is an example of embodiment of the invention skin image and unusual skin area figure bonded area correction parameter sketch map thereof.
The primary clustering symbol description
10 taking modules, 20 servo host
21 skin analysis modules, 22 numerical operation modules
23 data bases, 24 data input modules
25 display modules, 30 unusual skin analysis data
31 colour model translation data, 32 image gray scale analytical data
40 areas are proofreaied and correct data 51 skin images
52 color image, 53 unusual skin area figures
54 grey-tone images, 55 binaryzation images
The specific embodiment
Below in conjunction with accompanying drawing, preferred embodiment of the present invention is described in detail as follows:
At first please refer to the system block diagrams of Fig. 1 for the unusual skin area computing system of the present invention embodiment.The unusual skin area computing system of present embodiment comprises a taking module 10, a data base 23, skin analysis module 21 and a numerical operation module 22.The native system suitable configuration also is applicable to the example that a taking module 10 and a servo host 20 link in an example with electronic equipment of shooting ability.Present embodiment system adopts taking module 10 and the example that servo host 20 links, and below describes:
Taking module 10 is used for taking towards a human body skin, to produce the skin image 51 of corresponding human body skin.Taking module 10 is camera, digital camera or camera head with types such as handheld device of shooting ability, and handheld device comprises mobile phone or personal digital assistant.
Embodiment of the invention skin image one example that please illustrate with reference to Fig. 3 A simultaneously, the unusual skin area figure that Fig. 3 B illustrates embodiment of the invention corresponding diagram 3A, another example of skin image and Fig. 3 D that Fig. 3 C illustrates the embodiment of the invention illustrate the unusual skin area figure of embodiment of the invention corresponding diagram 3C.
Skin analysis module 21 can obtain the skin image 51 that taking module 10 is taken, and utilizes above-mentioned unusual skin analysis data 30 to analyze the unusual skin area figure 53 that skin image 51 comprises.22 elemental areas that calculate unusual skin area figure 53 of numerical operation module, and by the area correction parameter to calculate the real area of unusual skin area figure 53 corresponding to human body skin.
Wherein, unusual skin analysis data 30 comprise more than one colour model translation data 31, and it comprises rgb color model conversion data and HSV colour model translation data.
In this explanation, present embodiment indication rgb color model is the additive mixture color model of developing in theory at three primary colors for describing modal narration method in the chromatology, wherein comprised red (R, Red), green (G, Green) and blue (B, Blue) three kinds of primary colors.The interval of every kind of color all is from 0～255, will obtain (256) to these three value combinations
3Plant color.This rgb color model can represent that zero is that (0,0,0) represents black with a three-dimensional cube, and coordinate vertices (255,255,255) is represented white; Three summits on the coordinate axes are represented R, G, three primary colors of B respectively, and the complementary color of three kinds of primary colours is then represented on remaining three summit respectively, and they are mixed by adjacent two summit additive colors on the same plane respectively.
In this explanation, the HSV color system is three base attributes according to chromatology: tone (H, Hue), saturation (S, Saturation) and lightness (V Value) comes a kind of method of standard color.Tone H is the base attribute of color, and by deciding around the anglec of rotation of V axle (lightness axis), its span is from 0 ° to 360 °.Begin by counterclockwise calculating from redness, redness is 0 °, and green is 120 °, and blueness is 240 °.
Skin analysis module 21 can be resolved color image 52, finds out the distributed areas and the scope of unusual skin, and it is made to indicate the aforesaid unusual skin area figure 53 of formation.Yet the maneuver of resolving has two kinds at least, one: with unusual skin characteristic data and it is after finishing the colour model conversion process, the color data that presents on the color image 52 is stored in data base 23, or be contained in the unusual skin analysis data 30, take for skin analysis module 21, to form the skin analysis work pattern of the unusual skin of automatic analysis.Another: provide a data input module 24 and to be electrically coupled to skin analysis module 21, it is used for importing one and chooses order to click color image 52 more than one pixels, looking this type of pixel is object pixel, to indicate with color pixel with object pixel, form the skin analysis work pattern of manually choosing unusual skin.
Please consult Fig. 4 A and Fig. 4 B simultaneously, Fig. 4 A illustrates embodiment of the invention GTG figure and changes sketch map, and Fig. 4 B illustrates embodiment of the invention image capture sketch map.Please cooperate simultaneously with reference to Fig. 3 A to Fig. 3 D and be beneficial to understand.In the present embodiment, unusual skin analysis data 30 also can be an image gray scale analytical data 32, its recording image GTG and the flow process control instruction of analyzing unusual skin area image.According to image gray scale analytical data 32, skin analysis module 21 be with skin image 51 after being converted to a color image 52, again color image 52 is converted to a grey-tone image 54, resolves and indicate the unusual skin area figure 53 of above-mentioned grey-tone image 54 again according to an image division method.
The image partitioning scheme has several work patterns:
One, as Fig. 4 A and Fig. 4 B, user utilizes data input module 24 inputs one to choose order earlier, and this chooses order comprises that user is chosen from grey-tone image 54 image capturing range.Skin analysis module 21 is chosen order obtain one or more abnormal pixel sample value from grey-tone image according to above-mentioned, chooses for user, or selects one abnormal pixel sample value voluntarily by skin analysis module 21.Then, skin analysis module 21 is utilized selected abnormal pixel sample value, finds out a plurality of abnormal pixels that meet the abnormal pixel sample value from grey-tone image 54, and to its above-mentioned unusual skin area figure 53 of formation of marking.
Please be simultaneously with reference to Fig. 5 A to Fig. 5 C, Fig. 5 A and Fig. 5 B illustrate the threshold values sketch map that the embodiment of the invention is chosen grey-tone image, and the binaryzation image that Fig. 5 C illustrates the embodiment of the invention forms and unusual skin area graphic sketch map.
Its two, user utilizes data input module 24 input one to choose order earlier, this chooses order comprises that user is chosen from grey-tone image 54 image capturing range (the red frame position that Fig. 5 A and Fig. 5 B illustrate).Skin analysis module 21 calculates a GTG threshold values of corresponding grey-tone image 54 earlier.This GTG threshold values can be the average GTG value of grey-tone image 54 each pixel, or further calculate (as 90%, 80%, 70% of average GTG value according to the percentage ratio of average GTG value ... also or claim to reduce by 10%, 20%, 30% ... Deng the GTG value, similar numerical value like this, form or rule etc. are all suitable).Also or, according to being selected in the pixel coverage, take out a threshold values voluntarily by skin analysis module 21.As Fig. 5 A and Fig. 5 B, two pixel coverages that user is selected, 21 of skin analysis modules do not calculate 29 and 105 two GTG values, and the above-mentioned GTG value of foundation is extrapolated a threshold values, as 105x1.1=115,5, or to utilize data input module 25 direct specified threshold by user be 110 ... isotype, but do not exceed with above-mentioned pattern.Below with threshold values 110 as an illustration.
Skin analysis module 21 is to be benchmark with threshold values 110, grey-tone image 54 is made binaryzation to form binaryzation image 55, therefrom choose a plurality of abnormal pixels again and (be black person as color, or color is white person, both select one), indicate the position of abnormal pixel at last, to produce above-mentioned unusual skin area figure 53.Yet skin analysis module 21 also can use rim detection rule or boundary extraction rule to obtain above-mentioned unusual skin area figure 53.What is more, skin analysis module 21 is to utilize in grey-tone image 54 technology, binaryzation technology, boundary extraction rule and the rim detection rule at least its two, cooperatively interacts and produces above-mentioned unusual skin area figure 53.
Aforesaid area correction parameter also has plural number and plants different generation and modus operandi, the one person, the area correction parameter comprises the conversion parameter of the distance of taking module 10 and the skin of human body and corresponding pixel distance unit thereof and actual range unit, and the area correction parameter is stored among the data base 23 in advance.
Please illustrate the example of embodiment of the invention skin image 51 and unusual skin area figure 53 bonded area correction parameter sketch maps thereof simultaneously with reference to Fig. 6.For example, when the distance of taking module 10 and human body skin was 50 centimeters, pixel distance unit was 10 units with the conversion parameter of actual range unit: 1 centimeter; Routine again, when the distance of taking module 10 and human body skin was 40 centimeters, pixel distance unit was 20 units with the conversion parameter of actual range unit: 1 centimeter; Routine again, when the distance of taking module 10 and human body skin was 60 centimeters, pixel distance unit was 5 units with the conversion parameter of actual range unit: 1 centimeter ... suchlike data pattern, but not as limit, the related data kenel also is suitable for.
The distance of taking module 10 and human body skin can be obtained by dual mode, one self has the distance sensing unit of sensing to the human body distance for taking module 10, one for being utilized data input module 24 these distance values of input by user, take the area correction parameter of corresponding this distance values for numerical operation module 22.
Another kind of area correction parameter operational mode is that user provides one to proofread and correct thing, and it is disposed in the coverage of taking module 10.The skin image 51 of taking module 10 captured generations promptly comprises the corresponding correction thing figure of proofreading and correct thing.Numerical operation module 22 is to resolve to proofread and correct the thing figure, parses the reference length unit that it presents, and union goes out the transformational relation of reference length unit and pixel distance unit, it is recorded as above-mentioned area correction parameter.Wherein, proofreading and correct thing is a known yardstick object, as the flat board of gage, label or known area unit.Right in dull and stereotyped edge driving fit and the identical polygon of shape mutually, as parallelogram, regular hexagon, triangle.
No matter be which kind of area correction parameter produces and function mode, all be applicable to the operation that numerical operation module 22 is calculated actual unusual skin distribution area.
Secondly, system comprises a display module 25, and it connects skin analysis module 21 and numerical operation module 22, in order to present the processing process and the result of each skin image 51.What is more, display module 25 also presents the input interface of data input module 24, is convenient to import relevant parameter and carries out correlation function for user.
Please consult Fig. 2 A in regular turn and illustrate the unusual skin area computational methods of the present invention embodiment schematic flow sheet, Fig. 2 B illustrates the thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S120, Fig. 2 C illustrates the thin portion of the unusual skin area computational methods of the present invention embodiment step S123 schematic flow sheet, Fig. 2 D illustrates another thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S120, Fig. 2 E illustrates the unusual skin area computational methods of the present invention embodiment step S1203 thin portion schematic flow sheet and Fig. 2 F illustrates another thin portion schematic flow sheet of the unusual skin area computational methods of the present invention embodiment step S1203.Please consulting Fig. 1 simultaneously is beneficial to understand.This unusual skin area computational methods flow process is as follows:
Utilize a taking module 10 to take a human body skin and produce a skin image 51 (step S110).As described above, taking module 10 is camera, digital camera or camera head with types such as handheld device of shooting ability, and it is in order to take towards a human body skin, to produce the skin image 51 of corresponding human body skin.
Comprise unusual skin area figure 53 (step S120) by a skin analysis module 21 analyzing skin images 51.Data base 23 stores at least one unusual skin analysis data 30, and the unusual skin characteristic of its indication comprises burn, scald, speckle, cutin skin, white macula ... etc. type.Skin analysis module 21 can obtain the skin image 51 that taking module 10 is taken, and utilizes above-mentioned unusual skin analysis data 30 to analyze the unusual skin area figure 53 that skin image 51 comprises.
Wherein unusual skin analysis data 30 comprise more than one colour model translation data 31, an image gray scale analytical data 32 or comprise above-mentioned two kinds of data simultaneously.Rgb color model conversion data that colour model translation data 31 comprises and HSV colour model translation data.
When unusual skin analysis data 30 adopted colour model translation data 31 kenels, (step S120) comprised following thin portion flow process:
As Fig. 2 B, skin analysis module 21 utilizes color model conversion data that skin image 51 is converted to a color image 52 (step S121) earlier, and adjusts the model numerical value (step S122) of color image 52.Skin analysis module 22 one of can be utilized in the above-mentioned colour model translation data 31 person, and skin image 51 is converted to the color image 52 of corresponding rgb color model or HSB colour model, the similar image that is illustrated as Fig. 3 B or Fig. 3 D.
Skin analysis module 21 can be adjusted the model numerical value in the color image 52, to reduce the influence to follow-up image analysing computer.As: color image 52 specifications are the HSV colour model, and skin analysis module 21 is promptly adjusted lightness, saturation and the tone of color image 52, make color image 52 present different colors in response to the different skin color and luster.And for example: skin analysis module 21 is in response in the skin image 51, the color of the corresponding different systems of the representative meaning of each pixel, the skin video conversion is become only to present above-mentioned standard color, simplify the complexity of image, highlight the color image 52 of the skin scope of different symptoms simultaneously.
From the color image 52 of adjusted model numerical value, resolve and indicate unusual skin area figure 53 (step S123).As Fig. 3 A to Fig. 3 D, skin analysis module 21 can be resolved color image 52, with distributed areas and the scope of finding out unusual skin, and to the aforesaid unusual skin area figure 53 of its work sign formation.
Yet the maneuver of resolving has two kinds at least, one: with unusual skin characteristic data and it is after finishing the colour model conversion process, the color data that presents on color image 52 is stored in data base 23, or be contained in the unusual skin analysis data 30, take for skin analysis module 21, to form the skin analysis work pattern of the unusual skin of automatic analysis.Another: as Fig. 2 C, a data input module 24 is provided and is electrically coupled to skin analysis module 21, it chooses order (step S1231) in order to import one, to click more than one pixel in the color image 52.Obtain at least one abnormal pixel sample value (step S1232) according to choosing order from color image 52 by skin analysis module 21, and find out a plurality of abnormal pixels that meet at least one abnormal pixel sample value from color image 52, be unusual skin area figure (step S1233) to indicate these abnormal pixels.
From above-mentioned steps, learn, it is object pixel that skin analysis module 21 can be looked each pixel that meets the abnormal pixel sample value, to make sign and form above-mentioned unusual skin area figure with color pixel with object pixel, to reach the skin analysis work pattern of manually choosing unusual skin.
When unusual skin analysis data 30 adopted image gray scale analytical data 32 kenels, (step S120) comprised following thin portion flow process:
As Fig. 2 D, skin analysis module 21 is converted to a color image 52 (step S1201) according to above-mentioned colour model translation data 31 with skin image 51 earlier.Simplify the complexity that follow-up image calculates by this.
Skin analysis module 21 is according to image gray scale analytical data 32 color image 52 to be converted to a grey-tone image 54 (step S1202).As described above, unusual skin analysis data 30 also can be an image gray scale analytical data 32, and its recording image GTG and the flow process control instruction of analyzing unusual skin area image are taken for skin analysis module 21.Yet skin analysis module 21 also can use image gray scale analytical data 32 that skin image 51 directly is converted to grey-tone image, but does not exceed with above-mentioned two kinds of image gray scale operations, and other similar image gray scale pattern also is suitable for.
Skin analysis module 21 utilizes an image division method to resolve and indicate the unusual skin area figure 53 (step S1203) of grey-tone image 54.This step applies maneuver two, is described as follows:
One as Fig. 2 E, please cooperates simultaneously and consults Fig. 4 A and Fig. 4 B, chooses order to obtain at least one abnormal pixel sample value (step S12031) from grey-tone image according to one.As described above, user utilizes data input module 24 inputs one to choose order earlier, and this chooses order comprises that user is chosen from grey-tone image 54 image capturing range.Skin analysis module 21 is chosen order obtaining one or more abnormal pixel sample value from grey-tone image according to above-mentioned, selecting one abnormal pixel sample value voluntarily, or is chosen by user and therefrom to select one.
Skin analysis module 21 is found out from grey-tone image and is met a plurality of abnormal pixels of abnormal pixel sample value, is unusual skin area figure to indicate these abnormal pixels.(step S12032).
Its two, as Fig. 2 F, please cooperate simultaneously and consult Fig. 5 A to Fig. 5 C, choose order and obtain an abnormal pixel sample value (step S12033) according to one from grey-tone image.User utilizes data input module 24 inputs one to choose order earlier, and this chooses order comprises that user is chosen from grey-tone image 54 image capturing range (the red frame position that Fig. 5 A and Fig. 5 B illustrate).Skin analysis module 21 can calculate the one or more GTG value of corresponding grey-tone image 54 according in the selected image capturing range, therefrom takes out a threshold values voluntarily.Or skin analysis module 21 calculates the average GTG value of each pixel of grey-tone image 54 earlier, with it as the GTG threshold values.Also or, person further, percentage ratio according to average GTG value calculates that above-mentioned GTG threshold values is (as 90%, 80%, 70% of average GTG value ..., also or claim to reduce by 10%, 20%, 30% ... Deng the GTG value, similar numerical value like this, form or rule etc. are all suitable).
The abnormal pixel sample value is the threshold values of binaryzation, and the conversion grey-tone image is a binaryzation image (step S12034).As Fig. 5 A and Fig. 5 B, two pixel coverages that user is selected, skin analysis module 21 calculates 29 and 105 two GTG values respectively, and the above-mentioned GTG value of foundation is extrapolated a threshold values, as 105x1.1=115,5, or to utilize data input module 25 direct specified threshold by user be 110 ... isotype, but do not exceed with above-mentioned pattern.Below with threshold values 110 as an illustration.
Utilize Boolean calculation from the binaryzation image, to select unusual skin area figure (step S12035).As Fig. 5 C, skin analysis module 21 is to be benchmark with threshold values 110, grey-tone image 54 is made binaryzation to form binaryzation image 55, therefrom choose a plurality of abnormal pixels again and (be black person as color, or color is white person, both select one), by Boolean calculation binaryzation image 55 is made area distribution again and calculate to indicate the position of abnormal pixel, to produce above-mentioned unusual skin area figure 53.Yet skin analysis module 21 also can use rim detection rule or boundary extraction rule to obtain above-mentioned unusual skin area figure 53.What is more, skin analysis module 21 be utilize grey-tone image 54 technology, binaryzation technology, boundary extraction rule and rim detection rule at least its two, produce above-mentioned unusual skin area figure 53 to cooperatively interact.
Calculate the elemental area (step S130) of unusual skin area figure 53 by a numerical operation module 22.Numerical operation module 22 meeting elder generations are by the computing formula of associated straight lines, curve shape, to calculate the elemental area that unusual skin area figure 53 occupies in the picture scope.
Yet above-mentioned skin analysis module 21 is analyzed in the operation of unusual skin area figure 53, also be applicable to and import rim detection rule, boundary extraction rule or aforementioned two kinds of rules to obtain comparatively accurate unusual skin area figure 53, but not as limit, the relational graph analytical technology also is suitable for.
Utilize an area correction parameter to calculate the real area (step S140) of unusual skin area figure 53 by numerical operation module 22 corresponding to human body skin.Illustrate as Fig. 6, the area correction parameter comprises the conversion parameter of the distance of taking module 10 and human body skin and corresponding pixel distance unit thereof and actual range unit.For example: when the distance of taking module 10 and human body skin was 50 centimeters, pixel distance unit was 10 units with the conversion parameter of actual range unit: 1 centimeter; Routine again, when the distance of taking module 10 and human body skin was 40 centimeters, pixel distance unit was 20 units with the conversion parameter of actual range unit: 1 centimeter; Routine again, when the distance of taking module 10 and human body skin was 60 centimeters, pixel distance unit was 5 units with the conversion parameter of actual range unit: 1 centimeter ... suchlike data pattern, but not as limit, the related data kenel also is suitable for.
The distance of taking module 10 and human body skin can be obtained by dual mode, one self has the distance sensing unit of sensing to the human body distance for taking module 10, one for being utilized data input module 24 these distance values of input by user, take the area correction parameter of corresponding this distance values for numerical operation module 22.
Another kind of area correction parameter operational mode is that user provides one to proofread and correct thing, and it is disposed in the coverage of taking module 10.The skin image 51 of taking module 10 captured generations promptly comprises the corresponding correction thing figure of proofreading and correct thing.Numerical operation module 22 is to resolve to proofread and correct the thing figure, parses the reference length unit that it presents, and union goes out the transformational relation of reference length unit and pixel distance unit, it is recorded as above-mentioned area correction parameter.Wherein, proofreading and correct thing is a known yardstick object, as the flat board of gage, label or known area unit.Right in dull and stereotyped edge driving fit and the identical polygon of shape mutually, as parallelogram, regular hexagon, triangle.
No matter be which kind of area correction parameter produces and function mode, all be applicable to the operation that numerical operation module 22 is calculated actual unusual skin distribution area.In addition, the unusual skin area total graphic area that numerical operation module 22 is more calculated in order to the plural number that adds up, and calculate the actual distribution area of unusual skin according to above-mentioned area correction data, with the statistics one or many skin course of treatment gross area, provide user and sufferer one reliable basis.
In sum, only notebook invention is not to be used for limiting patent working scope of the present invention for presenting the embodiment or the embodiment of the technological means that adopted of dealing with problems.Be that patent claim context all and of the present invention conforms to, or change and modification, be all claim of the present invention and contain according to the equalization that claim of the present invention is done.
Claims (15)
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| CN 201010142033 CN101966083B (en) | 2010-04-08 | 2010-04-08 | Abnormal skin area calculation system and its calculation method |
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| CN104042189A (en) * | 2014-05-30 | 2014-09-17 | 中国人民解放军第三军医大学野战外科研究所 | Firearm injury devitalized tissue detection instrument |
| CN104161522A (en) * | 2014-08-12 | 2014-11-26 | 北京工业大学 | Auxiliary distance-measuring device of wound area measurement system |
| CN105125169A (en) * | 2014-05-30 | 2015-12-09 | 中国人民解放军第三军医大学野战外科研究所 | Lung blast injury detecting instrument and method for detecting lung blast injury image |
| CN106846395A (en) * | 2016-12-31 | 2017-06-13 | 中国农业科学院农业环境与可持续发展研究所 | Targeted graphical area computation method and system in photo |
| CN107049263A (en) * | 2017-06-14 | 2017-08-18 | 武汉理工大学 | Leucoderma condition-inference and cosmetic effect evaluating method and system based on image procossing |
| CN107773234A (en) * | 2017-10-10 | 2018-03-09 | 首都医科大学附属北京朝阳医院 | Image processing method and device |
| WO2019035768A1 (en) * | 2017-08-17 | 2019-02-21 | Iko Pte. Ltd. | Systems and methods for analyzing cutaneous conditions |
| CN109389610A (en) * | 2018-11-21 | 2019-02-26 | 上海衡道医学病理诊断中心有限公司 | A kind of skin lesion area computation method based on artificial intelligence identification |
| CN109480847A (en) * | 2018-10-31 | 2019-03-19 | 中国人民解放军陆军军医大学第附属医院 | A kind of disease damage area measuring device |
| CN109758122A (en) * | 2019-03-04 | 2019-05-17 | 上海长海医院 | A dermoscopy-based burn wound detection and recording system |
| TWI687686B (en) * | 2018-02-21 | 2020-03-11 | 魔力歐生技有限公司 | Method, apparatus and system for examining biological epidermis |
| CN114271796A (en) * | 2022-01-25 | 2022-04-05 | 泰安市康宇医疗器械有限公司 | Method and device for measuring human body components by using body state density method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105125169A (en) * | 2014-05-30 | 2015-12-09 | 中国人民解放军第三军医大学野战外科研究所 | Lung blast injury detecting instrument and method for detecting lung blast injury image |
| CN104042189B (en) * | 2014-05-30 | 2016-09-07 | 中国人民解放军第三军医大学野战外科研究所 | Firearm injury devitalized tissue detector |
| CN104042189A (en) * | 2014-05-30 | 2014-09-17 | 中国人民解放军第三军医大学野战外科研究所 | Firearm injury devitalized tissue detection instrument |
| CN104161522A (en) * | 2014-08-12 | 2014-11-26 | 北京工业大学 | Auxiliary distance-measuring device of wound area measurement system |
| CN106846395B (en) * | 2016-12-31 | 2019-12-27 | 中国农业科学院农业环境与可持续发展研究所 | Method and system for calculating area of target graph in photo |
| CN106846395A (en) * | 2016-12-31 | 2017-06-13 | 中国农业科学院农业环境与可持续发展研究所 | Targeted graphical area computation method and system in photo |
| CN107049263A (en) * | 2017-06-14 | 2017-08-18 | 武汉理工大学 | Leucoderma condition-inference and cosmetic effect evaluating method and system based on image procossing |
| WO2019035768A1 (en) * | 2017-08-17 | 2019-02-21 | Iko Pte. Ltd. | Systems and methods for analyzing cutaneous conditions |
| US11504055B2 (en) | 2017-08-17 | 2022-11-22 | Iko Pte. Ltd. | Systems and methods for analyzing cutaneous conditions |
| CN107773234A (en) * | 2017-10-10 | 2018-03-09 | 首都医科大学附属北京朝阳医院 | Image processing method and device |
| TWI687686B (en) * | 2018-02-21 | 2020-03-11 | 魔力歐生技有限公司 | Method, apparatus and system for examining biological epidermis |
| CN109480847A (en) * | 2018-10-31 | 2019-03-19 | 中国人民解放军陆军军医大学第附属医院 | A kind of disease damage area measuring device |
| CN109480847B (en) * | 2018-10-31 | 2021-09-14 | 中国人民解放军陆军军医大学第一附属医院 | Lesion area measuring device |
| CN109389610A (en) * | 2018-11-21 | 2019-02-26 | 上海衡道医学病理诊断中心有限公司 | A kind of skin lesion area computation method based on artificial intelligence identification |
| CN109758122A (en) * | 2019-03-04 | 2019-05-17 | 上海长海医院 | A dermoscopy-based burn wound detection and recording system |
| CN109758122B (en) * | 2019-03-04 | 2021-10-01 | 上海长海医院 | A dermoscopy-based burn wound detection and recording system |
| CN114271796A (en) * | 2022-01-25 | 2022-04-05 | 泰安市康宇医疗器械有限公司 | Method and device for measuring human body components by using body state density method |
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