CN111046700A - Method for analyzing fingerprint and palm print information by cloud - Google Patents
Method for analyzing fingerprint and palm print information by cloud Download PDFInfo
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- CN111046700A CN111046700A CN201811191607.7A CN201811191607A CN111046700A CN 111046700 A CN111046700 A CN 111046700A CN 201811191607 A CN201811191607 A CN 201811191607A CN 111046700 A CN111046700 A CN 111046700A
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
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- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
The invention discloses a method for analyzing fingerprint and palm print information by a cloud, which comprises the following steps: step S1: the cloud server receives the fingerprint and palm print information uploaded by the acquisition equipment and judges whether the fingerprint and palm print information is complete or not, if so, the next step is carried out; if not, returning an acquisition signal to inform the acquisition equipment to supplement and upload fingerprint and palm print information; step S2: performing fingerprint interpretation processing, fingerprint classification processing and palm print interpretation processing on the fingerprint and palm print information, and outputting identification result data; step S3: and generating a corresponding analysis result report according to the identification result data and different report versions. The invention can accurately carry out medical preliminary auxiliary detection and multivariate intelligent evaluation, is applied to auxiliary diagnosis of medical institutions on the spot, has high accuracy of analysis results, has practical scientific basis, medical clinical and published paper examples, greatly improves the satisfaction degree of users and has good user experience effect.
Description
Technical Field
The invention relates to the technical field of dermatoglyph analysis, in particular to a method for analyzing fingerprint and palm print information by a cloud.
Background
Many diseases, such as autism, cannot be correctly known until now, have various explanation mechanisms, but all of them are described later, and cannot achieve the effect of prevention, so that it is very important for infants to know whether to take care of the golden period, and to discover and treat in early period. Most of children are caused by physiological factors because of abnormal behaviors caused by psychological and social factors before the age of three, and at the moment, the children are in the stage of infants and cannot clearly explain the root of special conditions through behavior observation. The physiological factors are solved, so that derived psychological and social problems are solved, the most important of the physiological factors belongs to the integration of congenital brain sensation and screening of brain structures of various regions, and whether the brain condition of children can be detected early to help parents to engage in proper sensory stimulation is important for future development. As for lack of attention and excessive movement, the most headache of parents and teachers in education at present can be caused, and according to researches, the excessive movement can be divided into excellent excessive movement, somatosensory excessive movement and excessive movement with improper nerve connection, and how to separate various symptoms relates to whether the children with different symptoms can be correctly treated and treated, and the probability that the children with the somatosensory type are mistakenly judged to be excessive movement is reduced. The medical genetic dermatoglyph analysis has the characteristics of convenience, simplicity, rapidness and science, and is practically feasible when being used for medical primary auxiliary detection or multivariate intelligent evaluation. However, the existing dermatoglyph analysis method lacks clinical accumulation and research and development experience, cannot accurately perform medical preliminary auxiliary detection and multivariate intelligent evaluation, has large analysis result error, cannot improve the satisfaction degree of users, and has poor user experience effect, so that the analysis technology obtained through long-term brain-dermatoglyph research and a large number of clinical examinations is urgently needed.
Disclosure of Invention
Aiming at the defects in the prior art, the technical problem to be solved by the invention is to provide a method for analyzing fingerprint and palm print information by a cloud, and solve the problems that in the prior art, medical preliminary auxiliary detection and multivariate intelligent evaluation cannot be accurately performed, the error of an analysis result is large, the satisfaction degree of a user cannot be improved, and the user experience effect is poor, the medical preliminary auxiliary detection and multivariate intelligent evaluation can be accurately performed, the method is applied to auxiliary diagnosis of medical institutions on the spot, the accuracy of the analysis result is high, the user experience effect is good, and the method has the real scientific basis, medical clinical and published paper examples.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a method for analyzing fingerprint and palm print information by a cloud comprises the following steps:
step S1: the cloud server receives the fingerprint and palm print information uploaded by the acquisition equipment and judges whether the fingerprint and palm print information is complete or not, if so, the next step is carried out; if not, returning an acquisition signal to inform the acquisition equipment to supplement and upload fingerprint and palm print information;
step S2: performing fingerprint interpretation processing, fingerprint classification processing and palm print interpretation processing on the fingerprint and palm print information, and outputting identification result data;
step S3: and generating a corresponding analysis result report according to the identification result data and different report versions.
Preferably, the fingerprint and palm print information includes fingerprint image information, palm print image information and foot print image information.
Preferably, the fingerprint interpretation processing includes determining a true ridge and a false ridge, and the fingerprint interpretation processing includes determining the true ridge or the false ridge based on an entire width of the ridge in the fingerprint and palm information.
Preferably, the fingerprint interpretation process further includes: identifying a loop, wherein the loop is a line segment presented by ridges, the line segment is a complete smooth curve, and if the top end of the loop has additional lines which are adhered by the ridges in different directions and destroy the smooth state, the loop is not identified; identifying a model area, wherein the model area is an area with continuous repeated trends of ridges in the finger and palm print information; identifying the outer envelope: the outer envelope is a first loop ridge line which encloses the model area; determining a divergence line and a triangular point, wherein the divergence line is a virtual line segment at which two outer envelope lines tend to be parallel and are perpendicular to the two outer envelope lines, and the triangular point is a ridge line intersection point or a midpoint of the divergence line which is positioned between the outer envelope lines and the model area and passes through the divergence line; identifying a core point, the core point being a top of a center ridge line within a most core loop, or a core shoulder point distal from the triangle point; and calculating the number of ridges intersected with a straight line connecting the core point to the triangular point, wherein the intersected ridges are complete loops, and if the intersected ridges are single points or the loops of the intersected ridges are incomplete, the intersected ridges are not listed for identification.
Preferably, the fingerprint classification processing includes classifying the fingerprint image information in the finger and palm print information into eleven categories, which include positive skip information, reverse skip information, simple arc information, tent arc information, loop bucket information, spiral bucket information, capsule bucket information, broken double bucket information, peacock eye information, and deformed print information.
Preferably, the palm print interpretation process includes: determining A, B, C, D, T points and ATD angles of the palm print image information, wherein the ATD angles comprise angles of connecting lines of A, T, D three points on the palm print image information; identifying a ridge flow direction area in the palm print image information; identifying an interphalangeal loop of the palmprint image information in the palmprint information, wherein the interphalangeal loop comprises a humorous ring, a serious ring, a noble ring and a courage ring; identifying a music ring and a hypothenar circuit of a thenar circuit in the palmprint image information; and identifying the palm center shape, the number of the transverse wrinkles of the left little finger and the number of the transverse wrinkles of the right little finger in the palm print image information.
Preferably, in step S2, the method further includes a step of performing a footprint interpretation process on the fingerprint and palm print information, wherein the footprint interpretation process includes a step of dividing the fingerprint image information in the fingerprint and palm print information into ball information, calf-side loop information, inter-toe information, and underfoot loop information.
The method for analyzing the fingerprint and palm print information by the cloud end receives the fingerprint and palm print information uploaded by the acquisition equipment through the cloud end server and judges whether the fingerprint and palm print information is complete or not, so that fingerprint interpretation processing, fingerprint classification processing, palm print interpretation processing and foot print interpretation processing are carried out on the fingerprint and palm print information, identification result data are output, corresponding analysis result reports are generated by the identification result data according to different report versions, primary medical auxiliary detection and multivariate intelligent evaluation can be accurately carried out from brain science, the accuracy and the professional degree of analysis results are high, the satisfaction degree of a user is greatly improved, and the user experience effect and the follow-up feedback are good.
Drawings
FIG. 1 is a flowchart illustrating a method for cloud analysis of fingerprint and palm print information according to the present invention;
FIG. 2 is a schematic diagram of a fingerprint interpretation processing component in the fingerprint and palm print information according to the present invention;
FIG. 3 is a diagram of image information of eleven types of fingerprints in the fingerprint and palm print information of the present invention;
FIG. 4 is a schematic diagram of a palm print interpretation processing component in the finger and palm print information according to the present invention;
FIG. 5(1) is a schematic diagram illustrating a spiral fingerprint bucket and an inner broken double bucket winding in the fingerprint and palm print information according to the present invention;
FIG. 5(2) is a schematic diagram of the spiral-shaped loop and the inner broken loop of the fingerprint in the fingerprint and palm print information of the present invention
FIG. 6 is a schematic diagram of a bidirectional inward-surrounding double-bucket fingerprint information according to the present invention;
FIG. 7 is a schematic diagram of the same-direction winding inner breaking double buckets in the fingerprint and palm print information according to the present invention;
FIG. 8 is a diagram illustrating C degradation in fingerprint and palm print information according to the present invention;
FIG. 9 is a schematic diagram of a palm print C without (C is not visible) in the finger-palm print information according to the present invention;
FIG. 10 is a diagram illustrating the degeneration of palm print D in the finger and palm print information according to the present invention;
FIG. 11 is a schematic diagram of a palm print D (not visible) in the finger-palm print information according to the present invention;
FIG. 12(1) is a schematic diagram of a vibration ring Lr of a palm print in the finger/palm print information according to the present invention;
FIG. 12(2) is a schematic diagram of a palm print intuitive connection point T in the finger print information according to the present invention;
FIG. 13 is a schematic view of a spherical foot print inclined-away dustpan and a half-bucket in the fingerprint and palm print information of the present invention;
FIG. 14 is a schematic diagram of a plantar fibular side loop of the fingerprint and palmprint information according to the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, in the flowchart of the method for analyzing fingerprint and palm print information by the cloud of the present invention, the method for analyzing fingerprint and palm print information by the cloud includes the following steps: step S1: the cloud server receives the fingerprint and palm print information uploaded by the acquisition equipment and judges whether the fingerprint and palm print information is complete or not, if so, the next step is carried out; if not, returning an acquisition signal to inform the acquisition equipment to supplement the uploaded fingerprint and palm print information; step S2: carrying out fingerprint interpretation processing, fingerprint classification processing and palm print interpretation processing on the finger and palm print information, and outputting identification result data; step S3: and generating corresponding analysis result reports according to different report versions by using the identification result data. It can be understood that for the information collector under the age of 6, the collecting device collects the foot print item newly.
Specifically, in this step S2, several innovative techniques are involved:
1. as shown in FIG. 3, the distinction between the ring bucket information and the spiral bucket information is that the ring bucket is surrounded by three close circles of approximately regular circular patterns from the core point, and each circle is basically independent to form a ring; the spiral hopper is characterized in that the core point is started to directly form a vortex-shaped tightly wound circle with three circles which are basically and tightly connected into a ridge line.
2. The way of counting the number of turns of the spiral hopper is shown in FIG. 5(1), and one half of a turn is regarded as one turn starting from the core point and is established above the triangle point, and the concept of three turns is established similarly; if the ridge line does not go back up under the triangle point as shown in fig. 5(2), the circle is considered to be false.
3. As shown in fig. 3, when the annular aspect ratio of the annular bucket information or the spiral bucket information is greater than or equal to 2: 1; or when the ring shape deviates from the perfect circle and presents a horizontal flattening state when compared with the bucket shape information lines of other fingers, the ring shape deviates from the perfect circle and is identified as the capsule bucket information when the ring shape is obviously different from the roundness information of other fingers.
4. The lines are identified as inner broken double bucket information under two conditions:
firstly, the identification is that the two-way winding internal-breaking double bucket is wound in a bidirectional and alternate way, namely, two strands of spiral bucket information loops are wound in a bidirectional and alternate way, as shown in fig. 6, and the following conditions are met: when the number of the ridges intersected by the connecting line between the core point and the triangular point is less than 15, two loops need to be formed by encircling one circle; when the number of the ridges intersected by the connecting line between the core point and the triangular point is more than or equal to 15, the two loops need to be formed by two circles.
Secondly, the identification is to break the double buckets inwards around the same direction. As shown in fig. 7, when the two-strand spiral bucket information loops are wound alternately in the forward and reverse directions, the most core loop with the upward opening is identified as a reverse loop, and thus the loop is damaged, and the grain cannot find the reverse loop, the two forward loops are abutted, and all conditions of one of the two-strand spiral bucket information loops which are wound inwards to break the two buckets are converted into two forward loops suitable for the two abutted cores.
5. The difference between the internal broken double-bucket information and the double-bucket information is as follows: under the condition of the same-direction winding or the two-direction winding, when the number of the ridges intersected by the connecting line between the core point and the triangular point is less than 15, any one of the two loops cannot satisfy the condition of forming a circle, and the loop is identified as a double bucket; when the number of the ridges intersected by the connecting line between the core point and the triangular point is more than or equal to 15, any one of the two loops cannot satisfy the condition of surrounding two circles and forming the loop, and the loop is identified as a double bucket.
6. The above rules 4 and 5 have a special case, when identifying the left and right thumb line information, the following conditions are satisfied: (1) the total number of the ten fingers is less than 150; (2) the middle finger, ring finger and little finger of the left hand and the right hand are all positive skip grain information; (3) the number of pieces of information on the thumbs is not less than 15. When the number of the ridges intersected by the connecting line between the core point and the triangular point is more than or equal to 15, the judgment standard of the inner broken double-bucket and the double-bucket is changed into that one of two loops surrounds two circles and the other loop surrounds one circle, so that the inner broken double-bucket can be identified.
7. The difference between peacock eye information and twin-bucket information: the peacock eye information interpretation condition is that the model area is the bucket-shaped grain information (ring-shaped bucket information, spiral bucket information, bag-shaped bucket information or inner broken double bucket information), and the straight line connecting line of the left triangular point and the right triangular point is not tangent or intersected with the model area, and generally, the relative positions of the triangular points on the two sides have obvious height difference. When the grain core region cannot satisfy the information of the fighting grain, especially the condition of defining the broken double-bucket and the double-bucket occurs, even if the straight line connecting lines of the two triangular points are not tangent or intersected, the information of the double-bucket is identified.
8. As shown in fig. 8, there are two identification modules for C degradation in the palm print: firstly, a clear loop is arranged at the periphery of the point C, and the point C is independently wrapped left and right; secondly, the ridge lines connected with the points C form a loop towards one side, the points C are independently wrapped on the left and right of the whole periphery of the clear loop, and the number of the other ridge lines in the ridge line loop connected with the points C is four, including four.
9. As shown in fig. 9, C is not present in the palm print (C is not visible) and is formed at the point C where the three sides do not converge and are parallel, and a clear loop appears at the periphery.
10. As shown in fig. 10, there are two identification modules for D degradation in the palm print: firstly, a clear loop is arranged at the periphery of the point D to independently wrap the point D left and right; secondly, the ridge lines connected with the points D form a loop towards one side, the clear loop is arranged on the periphery of the whole body, the points D are independently wrapped on the left and the right of the loop, and the number of the other ridge lines in the ridge line loop connected with the points D is four, including four.
11. As shown in fig. 11, D-none (D-out) in the palm print is D-point formed where the D-point region has no three-edge convergence parallel, and a clear loop appears at the periphery.
12. An interphalangeal loop humorous ring between a point C and a point D in a palm print is generally presented as a single repeated loop, and is identified as a double humorous ring when two independent and disjoint repeated loops appear; when the shape of the repeated loop approaches a square, a square humorous ring is recognized.
13. In the palm, when the number of ridges where the humorous ring is located has no loop but the intersection of the connecting lines between the points C and D is extremely low (within 20), the humorous ring analysis part is identified as a low-number CD.
14. As shown in fig. 4, if loop information appears in the hypothenar in the palm print, the direction of the opening toward the ulnar part of the palm is generally "Lu", and the direction of the opening toward the pars flexibilis is generally "Lr", and no other distinction is made. The analysis method takes the point T as a newly added analysis condition and has the following five conclusions: (1) when the loop appears above the T point and the opening faces the palm flexing part, the loop is identified as an intuitive loop; (2) when the loop appears below the point T and the opening faces the palm flexing part, the loop is identified as a vibration ring Lr; (3) referring to FIG. 12(1), when the loop wraps the T point and connects to the dorsal line of the hypothenar, it is identified as the vibration ring Lr; (4) as shown in FIG. 12(2), when the lowest ridge line of the loop is connected to the ridge line connecting the point T toward the hypothenar direction, it is identified as the intuitive loop connecting the point T; (5) when the opening of the loop faces the palm ruler part, no matter the position of the T point, the vibration ring Lu is identified.
15. As shown in fig. 13, a half bucket and a far skip are newly added to the ball part of the footprint, wherein the half bucket is an extension of a circular arc loop which is generally presented but the other half of the circular arc loop is cut off and is in a half circular arc shape; the inclined long dustpan has an inclined profile which forms an angle of 45 degrees or more with the vertical line segment compared with the long dustpan with the opening facing the vertical direction.
16. As shown in fig. 14, the general fibula in the foot print only refers to the upper circular fibula loop, and the analysis method divides the line between the bottom of the metatarsal bone of the big toe and the bottom of the metatarsal bone of the small toe into an upper segment and a middle segment, and analyzes the circular fibula loop and the tent circular fibula loop at the middle end.
17. Six newly-increased research parts in the palm print, six research parts include: (1) whether the point A exists or not (whether the point A exists or not, and whether the point A is identified as a deformed hand stop analysis process) and whether the point B exists or not (whether the point B exists or not, and whether the point B is identified as a deformed hand stop analysis process); (2) the number of ridges intersected by the connection lines between the points AB and BC; (3) c point morphology (C present, C absent, C degenerated) and D point morphology (D present, D absent, D degenerated); (4) double humorous rings, humorous ring degeneration, low-number CD, square humorous ring in the interphalangeal circuit; (5) the vibration rings (Lu, Lr) in the hypothenar circuit are distinguished; (6) the intuitive loop connects points T. Specifically, the fingerprint and palm print information comprises fingerprint image information, palm print image information and foot print image information; the fingerprint interpretation processing comprises judging a true ridge and a false ridge, and the fingerprint interpretation processing comprises judging the true ridge or the false ridge according to the whole width of the ridge in the fingerprint and palm print information; the fingerprint interpretation process further includes: identifying a loop, wherein the loop is a complete and smooth curve represented by the ridge, and if the ridge in different directions is adhered at the top end of the loop, the additional line with broken smooth state is not regarded as the loop; identifying a model area, wherein the model area is an area with continuous repeated trend of ridges in the fingerprint and palm print information; identifying the outer envelope: the outer envelope line is a first loop ridge line which encloses the model area, is not necessarily a continuous line segment, but is necessarily a smooth curve without sharp turning; determining a divergence line and triangular points, wherein the divergence line is a virtual line segment which is perpendicular to the outer envelope line at the position where the two outer envelope lines tend to be parallel, the triangular points are ridge line intersection points or midpoint of the divergence line which are positioned between the outer envelope line and the model area and pass through the divergence line, and if a plurality of points meet the condition of the triangular points, selecting one point which is closest to the perpendicular distance of the following core points as the triangular points; identifying a core point that is either the top of a center ridge line within the most core loop (typically the inner ridge line is odd) or a shoulder point that is far from the triangle point but close to the core point (typically the inner ridge line is even); and calculating the number of ridges intersected with a straight line connecting the core point to the triangular point, wherein the intersected ridges need to be complete loops, and if the intersected ridges are single points or the loops are incomplete, the ridges are not listed in identification.
As shown in fig. 3, the fingerprint classification process includes dividing the fingerprint image information in the finger and palm print information into positive skip information, reverse skip information, simple arc information, tent arc information, loop bucket information, spiral bucket information, capsule bucket information, broken-inside double bucket information, peacock eye information, and deformed print information;
as shown in fig. 4, the palm print interpretation process includes: identifying one of palm print image information, A, B, C, D and a point T in the finger and palm print information, and judging the palm print image information as (1) whether the point A exists (the point A exists and the point A does not exist, and the point A does not exist and is identified as a deformed hand stop analysis process), whether the point B exists (the point B exists and the point B does not exist, and the point B does not exist and is identified as a deformed hand stop analysis process), and whether the point T exists (the point T exists and the point T does not exist) according to the following sequence; (2) determining an ATD angle, wherein the ATD angle comprises an angle of a connecting line of three points A, T, D on the left palm print image information and the right palm print image information, and the angle is 0 if the D point or the T point does not exist; (3) the number of ridges intersected by the connection lines between the points AB and BC; (4) a point A ridge flow direction region (A1-A5) and a point B ridge flow direction region (B1, B2); (5) c point morphology (C present, C absent, C degenerated) and D point morphology (D present, D absent, D degenerated); secondly, an interphalangeal loop, which comprises a humorous ring (with, double humorous ring, humorous ring degeneration, low-number CD, square humorous ring), a serious ring (with, serious ring degeneration), a noble ring and a courage ring; thirdly, the music ring (bucket pattern, skip pattern, fading pattern) of the thenar circuit; fourthly, a hypothenar loop which comprises a vibration ring (Lu and Lr), an intuitive ring connecting T point, a bucket line and a double bucket line; fifthly, palm shape, which comprises normal palm wrinkles, a through hand, a transitional connection type through hand, a transitional fusion type through hand and a Sydney type through hand; sixthly, the number of the cross folds of the little fingers of the left and right hands.
In step S2, the method further includes performing a footprint interpretation process on the fingerprint and palm print information, where the footprint interpretation process includes dividing the footprint image information in the fingerprint and palm print information into ball information (fibular arc information, shin tent arc information (axial arc information), far skip information, oblique far skip information, shin skip information, fibular skip information, skip print information, half skip information, and double skip information); underbody information Rubinstein type); fibular side loop information (upper, middle skip lines, middle tent arch lines); inter-toe information (2-3Ld loop, 2-3Lp loop, 3-4Lp loop, 4-5Ld loop, 4-5Lp loop); a underfoot circuit.
Specifically, in the actual work process, establish communication connection with this collection equipment and high in the clouds server, this collection equipment includes fingerprint collection scanner and CPU treater, and this fingerprint collection scanner passes through the power cord and establishes communication connection with this CPU treater. Ten fingers in fingerprint collection need to be collected, and each finger needs to collect three important information (a complete model area, a core point and a triangle point); the collection sequence is that the left thumb is firstly started, the left index finger, the middle finger, the ring finger and the little finger are connected, and then the right thumb, the index finger, the middle finger, the ring finger and the little finger are changed; firstly, lightly placing and pressing the finger on the photosensitive area of the fingerprint acquisition scanner and lightly rolling to scan the image, displaying the image on a computer by virtue of acquisition software, finding the image which meets the requirement of S1 and pressing down to store and store the acquired data. It can be understood that before the CPU processor stores the collected fingerprint information, it is necessary to examine the integrity of the fingerprint information collection in the image file, i.e. to ensure that all information on the palm is complete and clear, including the central finger abdomen, which requires "the core point and the model area are clear"; the middle part deviates to the left and requires that a model area appears slightly and a triangular point at the left end is clear (if the triangular point at the left end does not exist, the image deviates to the model area again); the middle part is deviated to the right, and the model area appears slightly and the triangle point at the right end is clear (if the triangle point at the left end is not available, the image is deviated to the model area again). It can be understood that the final identification result is transmitted back to the corresponding report output center, and the cloud big data report is generated according to the selected report version.
Specifically, in step S1, the determining whether the finger/palm print information is complete includes analyzing whether the data of each finger, palm and foot can be classified and quantified by the dermatoglyph, including whether the three images of each finger can be identified and analyzed, whether the palm information is complete and clear, the result has uniqueness, the possibility of no overlap in calculation and analysis is present, and if one piece of information is not qualified, the process is regarded as invalid information, and the information is returned to notify the collecting device to supplement and collect corresponding information. And then the cloud server analyzes and identifies the received personal information after the received personal information is qualified, namely fingerprint interpretation, palm print interpretation, foot print interpretation and the like.
As will be appreciated, the fingerprint interpretation includes true ridge to false ridge differentiation and fingerprint classification, false ridges are not counted; the fingerprint classification comprises dividing the fingerprint into ten types, wherein each type has corresponding and exclusive judgment standards, and specifically comprises a positive skip, a reverse skip, a simple arc, a tent arc, a ring-shaped bucket, a spiral bucket, a bag-shaped bucket, an internal broken double bucket, a peacock eye and a deformed line. The positive skip grain is provided with a backward curved line and a triangular point, and the flow direction of the positive skip grain faces to the direction of the little finger; the reverse skip grain is provided with a backward curved line and a triangular point, and the flow direction of the reverse skip grain faces the direction of the thumb; therefore, the results obtained by the left hand and the right hand of the above two patterns are opposite; the simple arc is composed of a plurality of approximately parallel arcs, the radian at the center is gentle and generally exceeds 90 degrees; the tent arc is composed of a plurality of approximately parallel arc lines, but the center of the tent arc is generally provided with a ridge line protrusion, and the radian of the center of the tent arc is generally less than 90 degrees; at least 3 locking loops at the center of the annular hopper are in a tightly growing state; the center of the spiral hopper is connected with at least 3 circles of loops (in a vortex type) in a tightly growing state; the bag-type bucket takes a ring-shaped bucket as a reference standard, and is classified as the item when the length-width ratio of the bag-type bucket meets or exceeds 2: 1; the loops at the center of the inner broken double bucket are S-shaped, the outer parts of the inner broken double bucket are wound by two-way or homodromous loops in a crossed way, and the detailed standards are in the innovative technologies 4, 5 and 6; the double-bucket veins are reversely combined by two skip veins, and the detailed standard is in the innovative technologies 4, 5 and 6; the peacock eye model area needs to have the characteristics of a bucket-shaped grain (a ring-shaped bucket, a spiral bucket, a bag-shaped bucket and an internal broken double bucket), and the connecting line between two triangular points can not contact the ridge line of the model area; the deformed lines are formed by combining two or more lines, or when the lines generate more than two triangular points. The fingerprint interpretation step comprises the following steps: finding out a model area, an outer envelope line, a divergence line and triangular points; the counting method is the number of ridges intersected with a straight line connecting the core point to the triangular point.
Specifically, the determination of the envelope includes: the outer covering line is not necessarily a continuous line, the outer covering line may be short, the outer covering line may not be a turn, the outer covering line should cover all of the three-corner points as much as possible, and a non-parallel line may not be selected as the outer covering line. The triangle point judgment comprises the following steps: the triangular point is positioned at the middle point of the divergent line; when there are several triangle points, selecting the points close to the core point; the ridge line containing the triangular point is inside the divergent line and mainly near the line end; the ridge line containing the triangular point is outside the divergent line and is mainly close to the core point; if the ridge line is exactly located in the straight line direction facing the core point, the point where the straight line ridge line stops is taken as a triangular point. The core point determination includes: shoulder points in the most core loop away from the triangle points; only a single ridge line is in the core loop, and the top end of the ridge line is taken as a core point; odd ridges are based on the top of the median ridge in the core loop; the top of the ridge line with the median far away from the triangular point in the core loop is used as a core point; if the top of the core loop is long with an additional wire (or sarcoma), the loop is damaged and not considered in the loop; the two loops crossing into a core loop, the core point being determined by whether the crossing point is located on the shoulder line of the two loops; if the intersection is above or below the shoulder line, the intersection is determined according to the rule of four ridge lines. The counting mode comprises the following steps: drawing a virtual straight line from a core point to a triangular point, counting ridge lines (no matter one point or line) crossed with the virtual straight line, but not counting the core point and the triangular point; if the core loop is connected with other ridge lines, whether the loop periphery is counted or not is judged according to the following graph; if no other ridge line exists between the core loop and the triangle point, it should be noted whether the triangle point is located above the core loop, if true, the loop is not counted.
Specifically, the skip grain constituting basic elements include: a complete back curve; a triangular point is arranged; the number of loops (if the back curve does not cross the virtual straight line between the triangle point and the core point, it will not be considered as having a complete back curve) can be counted. The tent arc forming basic elements comprise: the ridges have an angle of 90 DEG or less at the center where one or more ridges project, and the lines of the projections have an angle of 45 DEG or more from the horizontal, and often the end of many ridges. The special feature of the pattern like a skip pattern but having at most two skip patterns is possible, and the special feature of three skip patterns is impossible. The peacock eyes constitute basic elements and comprise: two triangular points; at least one ridge constitutes or faces a complete circle (spiral bucket, ring bucket, or other form of circle); the virtual straight line between two triangle points can not contact or pass through the ridge in the small edge model area; if there is no complete circle, the barrier line can be also listed, but the barrier line must be perpendicular to the inner flow line (the virtual straight line between the triangle point and the core point). The double-bucket-pattern forming basic elements comprise: two triangular points; has two separate skip-grain patterns, and each skip-grain has a separate and independent shoulder line. The double-bucket line has two separate skip lines, two clear and independent shoulders and two triangular points.
As can be appreciated, the palm print interpretation includes: humorous ring, serious ring, noble ring, courage ring, music ring, vibration ring, intuition ring; a, B, C, D, T points are contained on the palm, each point has different meanings, the ATD angle is the angle of a connecting line of A, T, D points, and the size of the ATD angle is related to the response speed of sensory functions to external information; points A and B: the point A is positioned at the Y-shaped intersection below the index finger; the point B is positioned at the intersection of the Y-shaped points below the middle finger; the two connecting lines are a-b, the number of the intersecting ridges in the connecting lines is the numerical value of a-b, and the data is only related to the medical analysis plate; and C, point: the degradation of the C point and the invisibility of the C point are related to the driving force, the reaction speed and the impatience degree; the connecting line between the points B and C is B-C, the number of the intersecting ridge lines in the connecting line is the numerical value of B-C, and the data is only related to the medical analysis plate; and D, point: d point degeneration and D point disappearance, and vision intensity and functional disorder are related; passing through: the coherent hand is related to the internal dynamic energy value and is subdivided into five types according to different line shapes, namely normal palm wrinkles, transition connection type coherent hand, transition fusion type coherent hand, Sydney type coherent hand and the like.
The technical scheme includes that the field of footprint interpretation relates to brainstem, footprint information is related to a medical analysis plate, screening is mainly performed on children aged 0-6, screening can be performed according to requirements at any age, special textures of a ball part (a region below the thumb), an inter-toe loop and a fibular loop can be recorded in an identification analysis system of a non-medical analysis plate to serve as primary brain health screening, and all identification analysis contents related to the footprint have multiple meanings and have a lot of genetic information in the medical analysis plate.
The cloud server receives the fingerprint and palm print information uploaded by the acquisition equipment and judges whether the fingerprint and palm print information is complete or not, so that fingerprint interpretation processing, fingerprint classification processing, palm print interpretation processing and foot print interpretation processing are performed on the fingerprint and palm print information, identification result data are output, corresponding analysis result reports are generated according to different report versions by the identification result data, primary medical auxiliary detection and multiple intelligent evaluation can be accurately performed from brain science, the accuracy of an analysis result is high, the satisfaction degree of a user is greatly improved, the user experience effect is good, the fault difference is presented with the prior art, the prior art is still continuously researched and developed, the research on brain functions is refined, and a higher-quality analysis technology is upgraded.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, and the scope of protection is still within the scope of the invention.
Claims (7)
1. A method for analyzing fingerprint and palm print information by a cloud is characterized by comprising the following steps: the method comprises the following steps:
step S1: the cloud server receives the fingerprint and palm print information uploaded by the acquisition equipment and judges whether the fingerprint and palm print information is complete or not, if so, the next step is carried out; if not, returning an acquisition signal to inform the acquisition equipment to supplement and upload fingerprint and palm print information;
step S2: performing fingerprint interpretation processing, fingerprint classification processing and palm print interpretation processing on the fingerprint and palm print information, and outputting identification result data;
step S3: and generating a corresponding analysis result report according to the identification result data and different report versions.
2. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: the fingerprint and palm print information comprises fingerprint image information, palm print image information and foot print image information.
3. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: the fingerprint interpretation processing includes determining a true ridge and a false ridge, and the fingerprint interpretation processing includes determining the true ridge or the false ridge according to an overall width of the ridge in the fingerprint and palm print information.
4. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: the fingerprint interpretation process further includes: identifying a loop, wherein the loop is a line segment presented by ridges, the line segment is a complete smooth curve, and if the top end of the loop has additional lines which are adhered by the ridges in different directions and destroy the smooth state, the loop is not identified; identifying a model area, wherein the model area is an area with continuous repeated trends of ridges in the finger and palm print information; identifying the outer envelope: the outer envelope is a first loop ridge line which encloses the model area; determining a divergence line and a triangular point, wherein the divergence line is a virtual line segment at which two outer envelope lines tend to be parallel and are perpendicular to the two outer envelope lines, and the triangular point is a ridge line intersection point or a midpoint of the divergence line which is positioned between the outer envelope lines and the model area and passes through the divergence line; identifying a core point, the core point being a top of a center ridge line within a most core loop, or a core shoulder point distal from the triangle point; and calculating the number of ridges intersected with a straight line connecting the core point to the triangular point, wherein the intersected ridges are complete loops, and if the intersected ridges are single points or the loops of the intersected ridges are incomplete, the intersected ridges are not listed for identification.
5. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: the fingerprint classification processing comprises dividing fingerprint image information in the finger and palm print information into eleven categories, wherein the eleven categories comprise positive skip information, reverse skip information, simple arc information, tent arc information, annular skip information, spiral skip information, capsule skip information, inner broken double skip information, peacock eye information and deformed skip information.
6. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: the palm print interpretation processing includes: determining A, B, C, D, T points and ATD angles of the palm print image information, wherein the ATD angles comprise angles of connecting lines of A, T, D three points on the palm print image information; identifying a ridge flow direction area in the palm print image information; identifying an interphalangeal loop of the palmprint image information in the palmprint information, wherein the interphalangeal loop comprises a humorous ring, a serious ring, a noble ring and a courage ring; identifying a music ring and a hypothenar circuit of a thenar circuit in the palmprint image information; and identifying the palm center shape, the number of the transverse wrinkles of the left little finger and the number of the transverse wrinkles of the right little finger in the palm print image information.
7. The method for analyzing fingerprint and palm print information at cloud end of claim 1, wherein: in step S2, the method further includes a step of performing a footprint interpretation process on the fingerprint and palm print information, where the footprint interpretation process includes dividing the fingerprint image information in the fingerprint and palm print information into ball information, calf-side loop information, inter-toe information, and a foot lower loop.
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| CN112568683A (en) * | 2020-12-28 | 2021-03-30 | 中科彭州智慧产业创新中心有限公司 | Foot pad for bathroom, health evaluation system and health evaluation method |
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