WO2017031969A1 - 指纹验证方法、指纹验证装置和终端 - Google Patents
指纹验证方法、指纹验证装置和终端 Download PDFInfo
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- WO2017031969A1 WO2017031969A1 PCT/CN2016/074898 CN2016074898W WO2017031969A1 WO 2017031969 A1 WO2017031969 A1 WO 2017031969A1 CN 2016074898 W CN2016074898 W CN 2016074898W WO 2017031969 A1 WO2017031969 A1 WO 2017031969A1
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- fingerprint
- fingerprint information
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- thumb
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- 238000012795 verification Methods 0.000 title claims abstract description 104
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000004364 calculation method Methods 0.000 claims abstract description 11
- 210000003813 thumb Anatomy 0.000 claims description 226
- 210000003811 finger Anatomy 0.000 claims description 96
- 230000006870 function Effects 0.000 claims description 12
- 230000007547 defect Effects 0.000 abstract description 9
- 238000005516 engineering process Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 6
- 238000012850 discrimination method Methods 0.000 description 5
- 230000015572 biosynthetic process Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000003786 synthesis reaction Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 1
- 210000004247 hand Anatomy 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000001308 synthesis method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- 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
- G06V40/1365—Matching; Classification
Definitions
- the present invention relates to the field of terminal technologies, and in particular, to a fingerprint verification method, a fingerprint verification device, and a terminal.
- the current fingerprint identification scheme first collects one or more single fingerprints of the user, and then compares one or more single fingerprints with a preset one or a pair of preset single fingerprints, and determines whether the user is based on the comparison result. For legitimate users.
- this fingerprint identification scheme requires a small number of fingerprints to be collected, and the discriminating method is single, and when there are stains, perspirations, or hand-skinning on the hands of legitimate users, misidentification may occur.
- a new technical solution is needed, which can improve the fingerprint verification function to collect a small number of fingerprints, a single discriminating method, and a defect that is easy to be misidentified, and improve the security of fingerprint verification.
- the invention is based on the above problems, and proposes a new technical solution, which can improve the fingerprint collection function to collect a small number of fingerprints, a single discriminating method and a defect that is easy to be misidentified, and improve the security of fingerprint verification.
- an aspect of the present invention provides a fingerprint verification method for a terminal, including: receiving at least two pieces of fingerprint information; determining each of the at least two pieces of fingerprint information and preset fingerprint information. a similarity degree; calculating a fingerprint superimposed comprehensive value of the at least two fingerprint information according to a similarity between the preset weight of each fingerprint information and the preset fingerprint information and a predetermined fingerprint superposition algorithm formula; determining the fingerprint superposition Whether the integrated value reaches the preset comprehensive value; according to the judgment result, it is determined whether or not the fingerprint is verified.
- the existing fingerprint verification function has the defects of small number of fingerprints collected, single discrimination method and easy misidentification, and the security of fingerprint verification is improved by increasing the number of fingerprints, and the comprehensive value of similarity is used. Judging whether the verification is passed or not, it can also avoid the unrecognizable situation caused by objective reasons such as finger stains, and more adapt to the actual needs of the user, thereby improving the user experience.
- determining the similarity between each of the at least two fingerprint information and the preset fingerprint information specifically: determining any one of the at least two fingerprint information a similarity between the information and each of the plurality of preset fingerprint information; and a finger type of the preset fingerprint information having the highest similarity as a finger of the any fingerprint information Types of.
- the similarity between each fingerprint information and each preset fingerprint information can be obtained, so that the highest similarity can be selected therein, and any fingerprint can be determined.
- the type of finger for the message For example, when any fingerprint information has the highest similarity with the preset thumb fingerprint information, any fingerprint information may be determined as the thumb type fingerprint information.
- the thumb fingerprint can be determined according to the highest similarity of each fingerprint information. Whether the number of information is one or two, it is convenient to further select a corresponding predetermined fingerprint superposition algorithm formula according to the number of thumb fingerprint information.
- the method further includes: determining, according to the finger type corresponding to each fingerprint information, the number of fingerprint information of the finger type as a thumb type; and in a plurality of predetermined fingerprint superposition algorithm formulas The predetermined fingerprint overlay algorithm formula corresponding to the number is selected.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the corresponding preset comprehensive value is higher and easier to identify.
- the corresponding formula of the predetermined fingerprint superposition algorithm is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the fingerprint information of the thumb type
- N is the number of the at least two pieces of fingerprint information
- q 1 , q 2 , ..., q N-1 are respectively the highest similarities of the other fingerprint information.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the corresponding formula of the predetermined fingerprint superposition algorithm is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the fingerprint information of the second thumb type
- N is the number of the at least two pieces of fingerprint information
- N ⁇ 2, q 1 , q 2 , ..., q N-2 are respectively the highest similarities of the other fingerprint information.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different. Wherein, when the number of thumb fingerprint information is two, the corresponding preset comprehensive value is higher and easier to identify.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the method further comprises: setting an average weight of the thumb type of the thumb information according to the received setting command The preset integrated value, wherein the average weight of the thumb type fingerprint information is a predetermined value, and the average weight of the other fingerprint information is:
- s q is the average weight of the other fingerprint information
- s is the average weight of the thumb type fingerprint information
- N is the number of the at least two fingerprint information
- n is the thumb type fingerprint information quantity.
- the preset weight of the thumb type fingerprint information may be preset to a fixed value, and the preset weights of other fingerprint information need to be performed according to the total number of fingerprint information and the number of thumb type fingerprint information. Calculation.
- the preset weight of the thumb type fingerprint information may be set to 1/2, so that when the number of thumb type fingerprint information is 1, the average weight of the other fingerprint information is:
- the thumb type when the number of fingerprint information of the thumb type is 2, the thumb type can be set.
- the preset weight of the fingerprint information is 1/4, so that the average weight of other fingerprint information is:
- the weight of the fingerprint information and the preset comprehensive value can be set according to the actual situation, so as to control the difficulty of the fingerprint verification and adapt to the actual needs of the user.
- Another aspect of the present invention also provides a fingerprint verification apparatus for a terminal, comprising: a receiving unit, receiving at least two pieces of fingerprint information; and a similarity determining unit determining each of the at least two pieces of fingerprint information Calculating a similarity with the preset fingerprint information; calculating a fingerprint of the at least two fingerprint information according to a similarity between the preset weight of each fingerprint information and the preset fingerprint information and a predetermined fingerprint superposition algorithm formula Superimposing the comprehensive value; the verification unit determines whether the integrated value of the fingerprint overlay reaches a preset comprehensive value, so as to determine whether to pass the fingerprint verification according to the judgment result.
- the fingerprint information of at least two fingers is collected, and the similarity between each fingerprint information and the predetermined fingerprint information is determined, thereby determining the finger type of each fingerprint information according to the similarity, thereby determining the similarity and
- the preset weight of each fingerprint information is substituted into a predetermined fingerprint superposition algorithm formula for calculation, and the fingerprint superimposed comprehensive value of the fingerprint verification can be obtained. Further, the fingerprint superimposed comprehensive value can be compared with the preset comprehensive value, and the fingerprint superposition is performed. When the integrated value is greater than or equal to the preset comprehensive value, it indicates that the fingerprint similarity meets the requirements, and then the fingerprint verification is allowed. Otherwise, the fingerprint verification is prohibited.
- the existing fingerprint verification function has the defects of small number of fingerprints collected, single discrimination method and easy misidentification, and the security of fingerprint verification is improved by increasing the number of fingerprints, and the comprehensive value of similarity is used. Judging whether the verification is passed or not, it can also avoid the unrecognizable situation caused by objective reasons such as finger stains, and more adapt to the actual needs of the user, thereby improving the user experience.
- the similarity determining unit is specifically configured to: determine any one of the at least two pieces of fingerprint information and each of the plurality of preset fingerprint information The similarity of the fingerprint information, and determining the finger type of the preset fingerprint information having the highest similarity as the finger type of the any fingerprint information.
- the similarity between each fingerprint information and each preset fingerprint information can be obtained, so that the highest similarity can be selected therein, and Determine the finger type of any fingerprint information. For example, when any fingerprint information has the highest similarity with the preset thumb fingerprint information, any fingerprint information may be determined as the thumb type fingerprint information.
- the thumb fingerprint can be determined according to the highest similarity of each fingerprint information. Whether the number of information is one or two, it is convenient to further select a corresponding predetermined fingerprint superposition algorithm formula according to the number of thumb fingerprint information.
- the method further includes: a thumb number determining unit, after determining the finger type of the preset fingerprint information having the highest similarity as the finger type corresponding to the any fingerprint information, Before calculating the fingerprint superimposed integrated value of the at least two fingerprint information, determining, according to the finger type corresponding to each fingerprint information, the number of fingerprint information of the finger type being a thumb type; a formula selection unit, The predetermined fingerprint superposition algorithm formula corresponding to the quantity is selected among a plurality of predetermined fingerprint superposition algorithm formulas.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the corresponding preset comprehensive value is higher and easier to identify.
- the corresponding formula of the predetermined fingerprint superposition algorithm is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the fingerprint information of the thumb type
- N is the number of the at least two pieces of fingerprint information
- q 1 , q 2 , ..., q N-1 are respectively the highest similarities of the other fingerprint information.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the corresponding formula of the predetermined fingerprint superposition algorithm is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the fingerprint information of the second thumb type
- N is the number of the at least two pieces of fingerprint information
- N ⁇ 2, q 1 , q 2 , ..., q N-2 are respectively the highest similarities of the other fingerprint information.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different. Wherein, when the number of thumb fingerprint information is two, the corresponding preset comprehensive value is higher and easier to identify.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the setting unit further includes: setting the fingerprint information of the thumb type according to the received setting command before calculating the fingerprint superimposed integrated value of the at least two pieces of fingerprint information
- the average weight and the preset integrated value wherein the average weight of the thumb type fingerprint information is a predetermined value, and the average weight of the other fingerprint information is:
- s q is the average weight of the other fingerprint information
- s is the average weight of the thumb type fingerprint information
- N is the number of the at least two fingerprint information
- n is the thumb type fingerprint information quantity.
- the preset weight of the thumb type fingerprint information may be preset to a fixed value, and the preset weights of other fingerprint information need to be performed according to the total number of fingerprint information and the number of thumb type fingerprint information. Calculation.
- the preset weight of the thumb type fingerprint information may be set to 1/2, so that when the number of thumb type fingerprint information is 1, the average weight of the other fingerprint information is:
- the preset weight of the thumb type fingerprint information may be set to 1/4, so that the average weight of other fingerprint information is:
- the weight of the fingerprint information and the preset comprehensive value can be set according to the actual situation, so as to control the difficulty of the fingerprint verification and adapt to the actual needs of the user.
- a further aspect of the present invention provides a terminal having a fingerprint verification function, the terminal comprising a processor and a memory, wherein the memory stores a set of program codes, and the processor is configured to call the memory to store Program code for doing the following:
- the processor determines a similarity between each of the at least two fingerprint information and the preset fingerprint information, where the specific operation is:
- the finger type of the preset fingerprint information having the highest similarity is determined as the finger type of the any fingerprint information.
- the predetermined fingerprint superposition algorithm formula corresponding to the quantity is selected among a plurality of predetermined fingerprint superposition algorithm formulas.
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the fingerprint information of the thumb type
- N is the number of the at least two pieces of fingerprint information
- q 1 , q 2 , ..., q N-1 are respectively the highest similarities of the other fingerprint information.
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the fingerprint information of the second thumb type
- N is the number of the at least two pieces of fingerprint information
- N ⁇ 2, q 1 , q 2 , ..., q N-2 are respectively the highest similarities of the other fingerprint information.
- the processor calculates the at least two fingerprint information in the Before the fingerprint overlays the integrated value, it also executes:
- an average weight of the thumb type information and the preset integrated value wherein an average weight of the thumb type fingerprint information is a predetermined value, and the other fingerprint information
- the average weight is:
- the existing fingerprint verification function has the defects of small number of fingerprints collected, single discrimination method and easy misidentification, and the security of fingerprint verification is improved by increasing the number of fingerprints, and the similarity is adopted.
- the comprehensive value is used to judge whether the verification is passed, and the unrecognizable situation caused by objective causes such as finger stains can be avoided, and the user's actual needs are further adapted to improve the user experience.
- FIG. 1 shows a flow chart of a fingerprint verification method in accordance with one embodiment of the present invention
- FIG. 2 shows a block diagram of a fingerprint verification device in accordance with one embodiment of the present invention
- FIG. 3 shows a block diagram of a terminal in accordance with an embodiment of the present invention
- FIG. 4 shows a block diagram of another alternative in accordance with an embodiment of the present invention.
- FIG. 1 shows a flow chart of a fingerprint verification method in accordance with one embodiment of the present invention.
- a fingerprint verification method is used for a terminal, including:
- Step 102 Receive at least two fingerprint information.
- Step 104 Determine a similarity between each of the at least two pieces of fingerprint information and the preset fingerprint information.
- Step 106 Calculate a fingerprint superimposed integrated value of at least two fingerprint information according to a similarity between the preset weight of each fingerprint information and the preset fingerprint information and a predetermined fingerprint superposition algorithm formula.
- Step 108 Determine whether the integrated value of the fingerprint overlay reaches a preset comprehensive value.
- Step 110 Determine, according to the judgment result, whether to pass the fingerprint verification.
- the fingerprint information of at least two fingers is collected, and the similarity between each fingerprint information and the predetermined fingerprint information is determined, thereby determining the finger type of each fingerprint information according to the similarity, thereby determining the similarity and
- the preset weight of each fingerprint information is substituted into a predetermined fingerprint superposition algorithm formula for calculation, and the fingerprint superimposed comprehensive value of the fingerprint verification can be obtained. Further, the fingerprint superimposed comprehensive value can be compared with the preset comprehensive value, and the fingerprint superposition is performed. When the integrated value is greater than or equal to the preset comprehensive value, it indicates that the fingerprint similarity meets the requirements, and then the fingerprint verification is allowed. Otherwise, the fingerprint verification is prohibited.
- the existing fingerprint verification function has the defects of small number of fingerprints collected, single discrimination method and easy misidentification, and the security of fingerprint verification is improved by increasing the number of fingerprints, and the comprehensive value of similarity is used. Judging whether the verification is passed or not, it can also avoid the unrecognizable situation caused by objective reasons such as finger stains, and more adapt to the actual needs of the user, thereby improving the user experience.
- the step 104 includes: determining a similarity between any one of the at least two pieces of fingerprint information and each of the plurality of preset fingerprint information; and having the highest similarity
- the finger type of the preset fingerprint information is determined as the finger type of any fingerprint information.
- the similarity between each fingerprint information and each preset fingerprint information can be obtained, so that the highest similarity can be selected therein, and any fingerprint can be determined.
- the type of finger for the message For example, when any fingerprint information has the highest similarity with the preset thumb fingerprint information, any fingerprint information may be determined as the thumb type fingerprint information.
- the thumb fingerprint can be determined according to the highest similarity of each fingerprint information. Whether the number of information is one or two, it is convenient to further select a corresponding predetermined fingerprint superposition algorithm formula according to the number of thumb fingerprint information.
- the method further includes And determining, according to the finger type corresponding to each fingerprint information, the number of fingerprint information whose finger type is a thumb type; and selecting a predetermined fingerprint superposition algorithm formula corresponding to the quantity in the plurality of predetermined fingerprint superposition algorithm formulas.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the corresponding preset comprehensive value is higher and easier to identify.
- the corresponding predetermined fingerprint superposition algorithm formula is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the thumb type fingerprint information
- N is the number of at least two fingerprint information
- N ⁇ 2 q 1 , q 2 , ..., q N-1 is the highest similarity of other fingerprint information.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the corresponding predetermined fingerprint superposition algorithm formula is:
- A is a fingerprint superimposed comprehensive value of at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is an average of other fingerprint information other than the thumb type fingerprint information in at least two fingerprint information.
- Weight p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the highest similarity of the fingerprint information of the second thumb type
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different. Wherein, when the number of thumb fingerprint information is two, the corresponding preset comprehensive value is higher and easier to identify.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the method further includes: setting, according to the received setting command, an average weight of the thumb type information and the preset integrated value, wherein the thumb The average weight of the fingerprint information of the type is a predetermined value, and the average weight of the other fingerprint information is:
- s q is the average weight of the other fingerprint information
- s is the average weight of the thumb type fingerprint information
- N is the number of the at least two fingerprint information
- n is the thumb type fingerprint information quantity.
- the preset weight of the thumb type fingerprint information may be preset to a fixed value, and the preset weights of other fingerprint information need to be performed according to the total number of fingerprint information and the number of thumb type fingerprint information. Calculation.
- the preset weight of the fingerprint information of the thumb type can be set to 1/2, so that when the number of fingerprint information of the thumb type is 1,
- the average weight of other fingerprint information is:
- the preset weight of the thumb type fingerprint information may be set to 1/4, so that the average weight of other fingerprint information is:
- the weight of the fingerprint information and the preset comprehensive value can be set according to the actual situation, so as to control the difficulty of the fingerprint verification and adapt to the actual needs of the user.
- FIG. 2 shows a block diagram of a fingerprint verification device in accordance with one embodiment of the present invention.
- the fingerprint verification apparatus 200 is used for a terminal, comprising: a receiving unit 202, which receives at least two pieces of fingerprint information; and a similarity determining unit 204 that determines at least two pieces of fingerprint information.
- the verification unit 208 determines whether the integrated value of the fingerprint overlay reaches a preset comprehensive value, so as to determine whether to pass the fingerprint verification according to the judgment result.
- the fingerprint information of at least two fingers is collected, and the similarity between each fingerprint information and the predetermined fingerprint information is determined, thereby determining the finger type of each fingerprint information according to the similarity, thereby determining the similarity and
- the preset weight of each fingerprint information is substituted into a predetermined fingerprint superposition algorithm formula for calculation, and the fingerprint superimposed comprehensive value of the fingerprint verification can be obtained. Further, the fingerprint superimposed comprehensive value can be compared with the preset comprehensive value, and the fingerprint superposition is performed. When the integrated value is greater than or equal to the preset comprehensive value, it indicates that the fingerprint similarity meets the requirements, and then the fingerprint verification is allowed. Otherwise, the fingerprint verification is prohibited.
- the existing fingerprint verification function has the defects of small number of fingerprints collected, single discrimination method and easy misidentification, and the security of fingerprint verification is improved by increasing the number of fingerprints, and the comprehensive value of similarity is used. Judging whether the verification is passed or not, it can also avoid the unrecognizable situation caused by objective reasons such as finger stains, and more adapt to the actual needs of the user, thereby improving the user experience.
- the similarity determining unit 204 is specifically configured to: determine to Determining the similarity between any one of the two fingerprint information and each of the plurality of preset fingerprint information, and determining the finger type of the preset fingerprint information having the highest similarity as any fingerprint information Finger type.
- the similarity between each fingerprint information and each preset fingerprint information can be obtained, so that the highest similarity can be selected therein, and any fingerprint can be determined.
- the type of finger for the message For example, when any fingerprint information has the highest similarity with the preset thumb fingerprint information, any fingerprint information may be determined as the thumb type fingerprint information.
- the thumb fingerprint can be determined according to the highest similarity of each fingerprint information. Whether the number of information is one or two, it is convenient to further select a corresponding predetermined fingerprint superposition algorithm formula according to the number of thumb fingerprint information.
- the thumb number determining unit 210 calculates at least two fingerprints after determining the finger type of the preset fingerprint information having the highest similarity as the finger type corresponding to any fingerprint information. Before the fingerprint of the information is superimposed on the integrated value, the number of the finger type is determined as the thumb type according to the finger type corresponding to each fingerprint information; the formula selecting unit 212 selects the number corresponding to the plurality of predetermined fingerprint overlay algorithm formulas. Predetermine the fingerprint overlay algorithm formula.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the corresponding preset comprehensive value is higher and easier to identify.
- the corresponding predetermined fingerprint superposition algorithm formula is:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the thumb type fingerprint information
- N is the number of at least two fingerprint information
- N ⁇ 2 q 1 , q 2 , ..., q N-1 is the highest similarity of other fingerprint information.
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the corresponding predetermined fingerprint superposition algorithm formula is:
- A is a fingerprint superimposed comprehensive value of at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is an average of other fingerprint information other than the thumb type fingerprint information in at least two fingerprint information.
- Weight p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the highest similarity of the fingerprint information of the second thumb type
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- N is the number of at least two pieces of fingerprint information
- the fingerprint information of the thumb is different from other fingers, and once similar, the similarity value is high, and the similarity can reach 80%, so the fingerprint weight assigned to the thumb is higher, the thumb fingerprint
- the number of information is different, and the corresponding predetermined fingerprint overlay algorithm formula and preset integrated value are also different. Wherein, when the number of thumb fingerprint information is two, the corresponding preset comprehensive value is higher and easier to identify.
- the similarity value of the fingerprint recognition technology can range from 70% to 80%.
- the preset integrated value can be defined as 75%, that is, the fingerprint superimposed integrated value of the newly acquired fingerprint is greater than or equal to 75%, and the fingerprint verification can be successfully passed. Otherwise, fingerprint verification is prohibited.
- the setting unit 214 is configured to set an average weight of the thumb type information according to the received setting command before calculating the fingerprint superimposed integrated value of the at least two pieces of fingerprint information.
- the preset integrated value wherein the average weight of the thumb type fingerprint information is a predetermined value, and the average weight of the other fingerprint information is:
- s q is the average weight of the other fingerprint information
- s is the average weight of the thumb type fingerprint information
- N is the number of the at least two fingerprint information
- n is the thumb type fingerprint information quantity.
- the preset weight of the thumb type fingerprint information may be preset to a fixed value, and the preset weights of other fingerprint information need to be performed according to the total number of fingerprint information and the number of thumb type fingerprint information. Calculation.
- the preset weight of the thumb type fingerprint information may be set to 1/2, so that when the number of thumb type fingerprint information is 1, the average weight of the other fingerprint information is:
- the preset weight of the thumb type fingerprint information may be set to 1/4, so that the average weight of other fingerprint information is:
- the weight of the fingerprint information and the preset comprehensive value can be set according to the actual situation, so as to control the difficulty of the fingerprint verification and adapt to the actual needs of the user.
- FIG. 3 shows a block diagram of a terminal in accordance with an embodiment of the present invention.
- the terminal 300 As shown in FIG. 3, the terminal 300 according to an embodiment of the present invention has a fingerprint verification function including the fingerprint verification apparatus 200 shown in FIG. 2. Therefore, the terminal 300 has the same technology as the fingerprint verification apparatus shown in FIG. The effect will not be described here.
- Fingerprint refers to the uneven lines on the front surface of the human finger end.
- the lines are regularly arranged to form different patterns.
- the starting point, end point, joint point and bifurcation point of the line are called fingerprints.
- the feature points of the detail are verified by comparing the feature points of the fingerprint.
- the fingerprint verification method of the embodiment is based on the single fingerprint identification. In the fingerprint identification process, the fingerprint verification method of the embodiment may be directly invoked, or the fingerprint verification method of the embodiment may be invoked when the single fingerprint unlocking fails. This improves the accuracy of fingerprint recognition.
- the specific steps are as follows:
- a legitimate user can use a fingerprint method to collect fingerprint images of N fingers (including at least one thumb) through a fingerprint collection device, and store the fingerprint information of the legitimate user in the fingerprint database.
- the number of fingerprints can be appropriately reduced. For example, 3 to 5 fingerprint information can be reduced.
- the fingerprint weight value assigned to the thumb is often higher. high. For example, you can assign weight values as follows:
- the weight of the thumb is set to 1/2, and the average weight of the other fingers is:
- the criterion for judging the similarity of two fingerprints can be determined.
- the value is defined as 75%
- the multi-fingerprint superimposed comprehensive value A in the legal fingerprint database is also 75%. That is, if the multi-fingerprint superimposed integrated value of the fingerprint is greater than or equal to 75%, the unlocking succeeds, otherwise the unlocking fails, and the fingerprint is regarded as an invalid fingerprint.
- the standard value for judging the similarity of the two fingerprints can be defined as a value other than 75%.
- the preset weight of the thumb type fingerprint information can be set to 1/2, then
- N is the total number of fingerprint information, N ⁇ 2, A 1 is at least two superimposed integrated fingerprint fingerprint information value, p is the highest similarity type fingerprint information thumb, said thumb for the second type
- the highest similarity of the fingerprint information is q 1 , q 2 , ..., q N-2 are the highest similarities of other fingerprint information, respectively.
- the preset weight of the fingerprint information of each thumb type can be set to 1/4, then
- N is the number of at least two pieces of fingerprint information, N ⁇ 2, A 2 is a fingerprint superimposed comprehensive value of at least two fingerprint information, p 1 is the highest similarity of the fingerprint information of the first thumb type, and p 2 is The highest similarity of the fingerprint information of the second thumb type is q 1 , q 2 , ..., q N-2 are the highest similarities of other fingerprint information, respectively.
- the multi-fingerprint superposition synthesis algorithm in two cases is separately stored in the memory A 1 and the memory A 2 for later post calling. At this point, the initial entry step has been completed.
- the user When the user uses the fingerprint to unlock, the user first inputs the fingerprint into the fingerprint recognizer, and the fingerprint recognizer can first perform one-to-many comparison matching by using the single fingerprint identification method. If the single fingerprint identification passes, the user directly unlocks; if the single fingerprint recognition fails, then The above multi-fingerprint overlay synthesis method is called to unlock.
- FIG. 4 shows a block diagram of a terminal in accordance with an embodiment of the present invention.
- a terminal 4 according to an embodiment of the present invention has a fingerprint verification function, including: at least one processor 41, such as a CPU, at least one communication bus 42 and a memory 43; and a communication bus 42 for implementing these components
- the connection communication the memory 43 may be a high speed RAM memory or a non-volatile memory such as at least one disk memory.
- a set of program codes is stored in the memory 43, and the processor 41 is configured to call the program code stored in the memory 43 for performing the following operations:
- the processor 41 determines the similarity between each of the at least two pieces of fingerprint information and the preset fingerprint information, and the specific operations are:
- the finger type of the preset fingerprint information having the highest similarity is determined as the finger type of the any fingerprint information.
- the processor 41 calculates the at least two fingerprints after determining the finger type of the preset fingerprint information having the highest similarity as the finger type corresponding to the any fingerprint information. Before the fingerprint of the information is superimposed on the integrated value, it is also executed:
- the predetermined fingerprint superposition algorithm formula corresponding to the quantity is selected among a plurality of predetermined fingerprint superposition algorithm formulas.
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p is the highest similarity of the fingerprint information of the thumb type
- N is the number of the at least two pieces of fingerprint information
- q 1 , q 2 , ..., q N-1 are respectively the highest similarities of the other fingerprint information.
- the predetermined fingerprint overlay algorithm formula should be:
- A is the fingerprint superimposed integrated value of the at least two fingerprint information
- s is an average weight of the thumb type fingerprint information
- s q is the thumb type in the at least two fingerprint information
- p 1 is the highest similarity of the fingerprint information of the first thumb type
- p 2 is the fingerprint information of the second thumb type
- N is the number of the at least two pieces of fingerprint information
- N ⁇ 2, q 1 , q 2 , ..., q N-2 are respectively the highest similarities of the other fingerprint information.
- the processor 41 further performs: before calculating the fingerprint superimposed integrated value of the at least two pieces of fingerprint information:
- an average weight of the thumb type information and the preset integrated value wherein an average weight of the thumb type fingerprint information is a predetermined value, and the other fingerprint information
- the average weight is:
- the technical solution of the present invention improves the defects of the existing fingerprint verification function for collecting a small number of fingerprints, a single discriminating method, and prone to misidentification, increasing the number of fingerprints and improving the fingerprint.
- the security of the verification according to the comprehensive value of the similarity to judge whether the verification is passed, can also avoid the unrecognizable situation caused by objective reasons such as finger stains, and more adapt to the actual needs of users.
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Abstract
本发明提出了一种指纹验证方法、一种指纹验证装置和一种终端，其中，指纹验证方法包括：接收至少两个指纹信息；确定至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；根据每个指纹信息的预设权重与预设指纹信息的相似度和预定指纹叠加算法公式，计算至少两个指纹信息的指纹叠加综合数值；判断指纹叠加综合数值是否达到预设综合数值；根据判断结果，确定是否通过指纹验证。通过该技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，增加指纹数量提升了指纹验证的安全性，再根据相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求。
Description
本申请要求于2015年8月25日提交中国专利局，申请号为201510528783.5、发明名称为“指纹验证方法、指纹验证装置和终端”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本发明涉及终端技术领域，具体而言，涉及一种指纹验证方法、一种指纹验证装置和一种终端。
目前的指纹识别方案是先采集用户的一个或者多个单指纹，然后再将一个或者多个单指纹与预设的一个或对个预设单指纹进行对比，并根据比对结果判断该用户是否为合法用户。
但是，这种指纹识别方案需要采集的指纹数量少，判别方法单一，并且当合法用户的手上有污渍、汗渍，或者手蜕皮时，就会导致误识别的现象出现。
因此，需要一种新的技术方案，能够改善指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，提升指纹验证的安全性。
发明内容
本发明正是基于上述问题，提出了一种新的技术方案，能够改善指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，提升指纹验证的安全性。
有鉴于此，本发明的一个方面提出了一种指纹验证方法，用于终端，包括：接收至少两个指纹信息；确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；判断所述指纹叠加综合数值是否达到预设综合数值；根据判断结果，确定是否通过指纹验证。
在该技术方案中，通过采集至少两个手指的指纹信息，并确定每个指
纹信息与预定指纹信息的相似度，从而根据相似度确定每个指纹信息的手指类型，从而将确定的相似度和每个指纹信息的预设权重代入预定指纹叠加算法公式进行计算，即可获取本次指纹验证的指纹叠加综合数值，进一步地，可以将指纹叠加综合数值与预设综合数值进行比较，当指纹叠加综合数值大于或等于预设综合数值时，说明指纹相似度符合要求，才允许通过指纹验证，否则，禁止通过指纹验证。通过该技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，通过增加指纹数量提升了指纹验证的安全性，并且，通过相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求，提升了用户体验。
在上述技术方案中，优选地，所述确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度，具体包括：确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度；以及将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
在该技术方案中，将任一指纹信息与多个预设指纹信息进行比较，可得出其与每个预设指纹信息的相似度，从而可在其中选择最高相似度，并确定任一指纹信息的手指类型。比如，当任一指纹信息与预设的大拇指指纹信息相似度最高时，可以将该任一指纹信息确定为大拇指类型的指纹信息。另外，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，因此，还可以根据各指纹信息的最高相似度确定其中的大拇指指纹信息的数量为一个还是两个，便于进一步根据大拇指指纹信息的数量选择对应的预定指纹叠加算法公式。
在上述技术方案中，优选地，在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还包括：根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；以及在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同，其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。
在上述技术方案中，优选地，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为所述其他指纹信息的所述最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，当所述大拇指类型的指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述
大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为所述其他指纹信息的所述最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还包括：根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为： 
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。
在该技术方案中，大拇指类型的指纹信息的预设权重可以预先设置为固定的数值，而其他指纹信息的预设权重则需要根据指纹信息的总数量及大拇指类型的指纹信息的数量进行计算。比如，可以设置大拇指类型的指纹信息的预设权重为1/2，这样，当大拇指类型的指纹信息的数量为1时，其他指纹信息的平均权重为：
再比如，当大拇指类型的指纹信息的数量为2时，可以设置大拇指类
型的指纹信息的预设权重为1/4，这样，其他指纹信息的平均权重为：
通过该技术方案，可以根据实际情况设置指纹信息的权重及预设综合数值，以便控制指纹验证的难度，适应用户的实际需求。
本发明的另一方面还提出了一种指纹验证装置，用于终端，包括：接收单元，接收至少两个指纹信息；相似度确定单元，确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；计算单元，根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；验证单元，判断所述指纹叠加综合数值是否达到预设综合数值，以供根据判断结果，确定是否通过指纹验证。
在该技术方案中，通过采集至少两个手指的指纹信息，并确定每个指纹信息与预定指纹信息的相似度，从而根据相似度确定每个指纹信息的手指类型，从而将确定的相似度和每个指纹信息的预设权重代入预定指纹叠加算法公式进行计算，即可获取本次指纹验证的指纹叠加综合数值，进一步地，可以将指纹叠加综合数值与预设综合数值进行比较，当指纹叠加综合数值大于或等于预设综合数值时，说明指纹相似度符合要求，才允许通过指纹验证，否则，禁止通过指纹验证。通过该技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，通过增加指纹数量提升了指纹验证的安全性，并且，通过相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求，提升了用户体验。
在上述技术方案中，优选地，所述相似度确定单元具体用于：确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度，并将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
在该技术方案中，将任一指纹信息与多个预设指纹信息进行比较，可得出其与每个预设指纹信息的相似度，从而可在其中选择最高相似度，并
确定任一指纹信息的手指类型。比如，当任一指纹信息与预设的大拇指指纹信息相似度最高时，可以将该任一指纹信息确定为大拇指类型的指纹信息。另外，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，因此，还可以根据各指纹信息的最高相似度确定其中的大拇指指纹信息的数量为一个还是两个，便于进一步根据大拇指指纹信息的数量选择对应的预定指纹叠加算法公式。
在上述技术方案中，优选地，还包括：大拇指数量确定单元，在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，所述计算所述至少两个指纹信息的指纹叠加综合数值之前，根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；公式选择单元，在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同，其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。
在上述技术方案中，优选地，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为所述其他指纹信息的所述最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指
纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，当所述大拇指类型的指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为所述其他指纹信息的所述最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，还包括：设置单元，在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为： 
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。
在该技术方案中，大拇指类型的指纹信息的预设权重可以预先设置为固定的数值，而其他指纹信息的预设权重则需要根据指纹信息的总数量及大拇指类型的指纹信息的数量进行计算。比如，可以设置大拇指类型的指纹信息的预设权重为1/2，这样，当大拇指类型的指纹信息的数量为1时，其他指纹信息的平均权重为：
再比如，当大拇指类型的指纹信息的数量为2时，可以设置大拇指类型的指纹信息的预设权重为1/4，这样，其他指纹信息的平均权重为：
通过该技术方案，可以根据实际情况设置指纹信息的权重及预设综合数值，以便控制指纹验证的难度，适应用户的实际需求。
本发明的再一方面提出了一种终端，具有指纹验证功能，所述终端包括处理器和存储器，其中，所述存储器中存储一组程序代码，且所述处理器用于调用所述存储器中存储的程序代码，用于执行以下操作：
接收至少两个指纹信息；
确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；
根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；
判断所述指纹叠加综合数值是否达到预设综合数值；
根据判断结果，确定是否通过指纹验证。
在上述技术方案中，所述处理器确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度，具体操作为：
确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度；以及
将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
在上述技术方案中，所述处理器在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，计算所述至少两个指纹信息的指纹叠加综合数值之前，还执行：
根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；以及
在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
在上述技术方案中，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为所述其他指纹信息的所述最高相似度。
在上述技术方案中，当所述大拇指类型的指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为所述其他指纹信息的所述最高相似度。
在上述技术方案中，所述处理器在所述计算所述至少两个指纹信息的
指纹叠加综合数值之前，还执行：
根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
通过本发明的上述技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，通过增加指纹数量提升了指纹验证的安全性，并且，通过相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求，提升了用户体验。
图1示出了根据本发明的一个实施例的指纹验证方法的流程图；
图2示出了根据本发明的一个实施例的指纹验证装置的框图；
图3示出了根据本发明的实施例的一种终端的框图；
图4示出了根据本发明的实施例的另一种的框图。
为了能够更清楚地理解本发明的上述目的、特征和优点，下面结合附图和具体实施方式对本发明进行进一步的详细描述。需要说明的是，在不冲突的情况下，本申请的实施例及实施例中的特征可以相互组合。
在下面的描述中阐述了很多具体细节以便于充分理解本发明，但是，本发明还可以采用其他不同于在此描述的其他方式来实施，因此，本发明的保护范围并不受下面公开的具体实施例的限制。
图1示出了根据本发明的一个实施例的指纹验证方法的流程图。
如图1所示，根据本发明的一个实施例的指纹验证方法，用于终端，包括：
步骤102，接收至少两个指纹信息。
步骤104，确定至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度。
步骤106，根据每个指纹信息的预设权重与预设指纹信息的相似度和预定指纹叠加算法公式，计算至少两个指纹信息的指纹叠加综合数值。
步骤108，判断指纹叠加综合数值是否达到预设综合数值。
步骤110，根据判断结果，确定是否通过指纹验证。
在该技术方案中，通过采集至少两个手指的指纹信息，并确定每个指纹信息与预定指纹信息的相似度，从而根据相似度确定每个指纹信息的手指类型，从而将确定的相似度和每个指纹信息的预设权重代入预定指纹叠加算法公式进行计算，即可获取本次指纹验证的指纹叠加综合数值，进一步地，可以将指纹叠加综合数值与预设综合数值进行比较，当指纹叠加综合数值大于或等于预设综合数值时，说明指纹相似度符合要求，才允许通过指纹验证，否则，禁止通过指纹验证。通过该技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，通过增加指纹数量提升了指纹验证的安全性，并且，通过相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求，提升了用户体验。
在上述技术方案中，优选地，步骤104具体包括：确定至少两个指纹信息中的任一指纹信息与多个预设指纹信息中的每个预设指纹信息的相似度；以及将具有最高相似度的预设指纹信息的手指类型确定为任一指纹信息的手指类型。
在该技术方案中，将任一指纹信息与多个预设指纹信息进行比较，可得出其与每个预设指纹信息的相似度，从而可在其中选择最高相似度，并确定任一指纹信息的手指类型。比如，当任一指纹信息与预设的大拇指指纹信息相似度最高时，可以将该任一指纹信息确定为大拇指类型的指纹信息。另外，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，因此，还可以根据各指纹信息的最高相似度确定其中的大拇指指纹信息的数量为一个还是两个，便于进一步根据大拇指指纹信息的数量选择对应的预定指纹叠加算法公式。
在上述技术方案中，优选地，在将具有最高相似度的预设指纹信息的手指类型确定为任一指纹信息对应的手指类型之后，计算至少两个指纹信息的指纹叠加综合数值之前，还包括：根据每个指纹信息对应的手指类型，确定手指类型为大拇指类型的指纹信息的数量；以及在多个预定指纹叠加算法公式中选择与数量对应的预定指纹叠加算法公式。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同，其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。
在上述技术方案中，优选地，当大拇指类型的指纹信息的数量为1时，对应的预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为大拇指类型的指纹信息的最高相似度，N为至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为其他指纹信息的最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，当大拇指类型的指纹信息的数量为2时，对应的预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为至少两个指纹信息的指纹叠加综合数值，s为大拇指类型的指纹信息的平均权重，sq为至少两个指纹信息中的大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个大拇指类型的指纹信息的最高相似度，p2为第二个大拇指类型的指纹信息的最高相似度，N为至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为其他指纹信息的最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，在步骤106之前，还包括：根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。
在该技术方案中，大拇指类型的指纹信息的预设权重可以预先设置为固定的数值，而其他指纹信息的预设权重则需要根据指纹信息的总数量及大拇指类型的指纹信息的数量进行计算。比如，可以设置大拇指类型的指纹信息的预设权重为1/2，这样，当大拇指类型的指纹信息的数量为1时，
其他指纹信息的平均权重为：
再比如，当大拇指类型的指纹信息的数量为2时，可以设置大拇指类型的指纹信息的预设权重为1/4，这样，其他指纹信息的平均权重为：
通过该技术方案，可以根据实际情况设置指纹信息的权重及预设综合数值，以便控制指纹验证的难度，适应用户的实际需求。
图2示出了根据本发明的一个实施例的指纹验证装置的框图。
如图2所示，根据本发明的一个实施例的指纹验证装置200，用于终端，包括：接收单元202，接收至少两个指纹信息；相似度确定单元204，确定至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；计算单元206，根据每个指纹信息的预设权重与预设指纹信息的相似度和预定指纹叠加算法公式，计算至少两个指纹信息的指纹叠加综合数值；验证单元208，判断指纹叠加综合数值是否达到预设综合数值，以供根据判断结果，确定是否通过指纹验证。
在该技术方案中，通过采集至少两个手指的指纹信息，并确定每个指纹信息与预定指纹信息的相似度，从而根据相似度确定每个指纹信息的手指类型，从而将确定的相似度和每个指纹信息的预设权重代入预定指纹叠加算法公式进行计算，即可获取本次指纹验证的指纹叠加综合数值，进一步地，可以将指纹叠加综合数值与预设综合数值进行比较，当指纹叠加综合数值大于或等于预设综合数值时，说明指纹相似度符合要求，才允许通过指纹验证，否则，禁止通过指纹验证。通过该技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，通过增加指纹数量提升了指纹验证的安全性，并且，通过相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求，提升了用户体验。
在上述技术方案中，优选地，相似度确定单元204具体用于：确定至
少两个指纹信息中的任一指纹信息与多个预设指纹信息中的每个预设指纹信息的相似度，并将具有最高相似度的预设指纹信息的手指类型确定为任一指纹信息的手指类型。
在该技术方案中，将任一指纹信息与多个预设指纹信息进行比较，可得出其与每个预设指纹信息的相似度，从而可在其中选择最高相似度，并确定任一指纹信息的手指类型。比如，当任一指纹信息与预设的大拇指指纹信息相似度最高时，可以将该任一指纹信息确定为大拇指类型的指纹信息。另外，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，因此，还可以根据各指纹信息的最高相似度确定其中的大拇指指纹信息的数量为一个还是两个，便于进一步根据大拇指指纹信息的数量选择对应的预定指纹叠加算法公式。
在上述技术方案中，优选地，还包括：大拇指数量确定单元210，在将具有最高相似度的预设指纹信息的手指类型确定为任一指纹信息对应的手指类型之后，计算至少两个指纹信息的指纹叠加综合数值之前，根据每个指纹信息对应的手指类型，确定手指类型为大拇指类型的指纹信息的数量；公式选择单元212，在多个预定指纹叠加算法公式中选择与数量对应的预定指纹叠加算法公式。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同，其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。
在上述技术方案中，优选地，当大拇指类型的指纹信息的数量为1时，对应的预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述
大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为大拇指类型的指纹信息的最高相似度，N为至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为其他指纹信息的最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，当大拇指类型的指纹信息的数量为2时，对应的预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为至少两个指纹信息的指纹叠加综合数值，s为大拇指类型的指纹信息的平均权重，sq为至少两个指纹信息中的大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个大拇指类型的指纹信息的最高相似度，p2为第二个大拇指类型的指纹信息的最高相似度，N为至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为其他指纹信息的最高相似度。
在该技术方案中，由于大拇指的指纹信息与其他手指的差异大，而且一旦相似，其相似度数值高，相似度可以达到80％，故给大拇指分配的指纹权重较高，大拇指指纹信息的数量不同，对应的预定指纹叠加算法公式及预设综合数值也不同。其中，大拇指指纹信息的数量为两个时，对应的预设综合数值更高，更易识别。指纹识别技术可达的相似度数值范围为：70％至80％，比如，可以定义预设综合数值为75％，即新采集指纹的指纹叠加综合数值大于或等于75％便可成功通过指纹验证，否则禁止通过指纹验证。
在上述技术方案中，优选地，还包括：设置单元214，在计算至少两个指纹信息的指纹叠加综合数值之前，根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为： 
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。
在该技术方案中，大拇指类型的指纹信息的预设权重可以预先设置为固定的数值，而其他指纹信息的预设权重则需要根据指纹信息的总数量及大拇指类型的指纹信息的数量进行计算。比如，可以设置大拇指类型的指纹信息的预设权重为1/2，这样，当大拇指类型的指纹信息的数量为1时，其他指纹信息的平均权重为：
再比如，当大拇指类型的指纹信息的数量为2时，可以设置大拇指类型的指纹信息的预设权重为1/4，这样，其他指纹信息的平均权重为：
通过该技术方案，可以根据实际情况设置指纹信息的权重及预设综合数值，以便控制指纹验证的难度，适应用户的实际需求。
图3示出了根据本发明的实施例的终端的框图。
如图3所示，根据本发明的实施例的终端300，具有指纹验证功能，包括图2示出的指纹验证装置200，因此，该终端300具有与图2示出的指纹验证装置相同的技术效果，在此不再赘述。
下面结合具体实施例描述本发明的指纹验证方法：
指纹是指人的手指末端正面皮肤上凸凹不平的纹线，该纹线有规律的排列形成不同的纹型，该纹线的起点、终点、结合点和分叉点，称为指纹
的细节特征点，通过比较指纹的细节特征点来进行指纹验证。而本实施例的指纹验证方法正是基于单指纹识别的，在指纹识别过程中，可以直接调用本实施例的指纹验证方法，也可以在单指纹解锁失败时调用本实施例的指纹验证方法，这样就提高了指纹识别的准确性，具体操作步骤如下：
一、采集合法用户的指纹信息。
合法用户可使用按压式的方法通过指纹采集仪采集N个手指(至少包含一个大拇指)的指纹图像，并将合法用户的这些指纹信息存储到指纹数据库。其中，由于指纹数据库的空间有限，可以适当的减少指纹的采集数量，比如，可以减少到3至5个指纹信息。
二、制定每个指纹信息的权重值和规则。
由于大拇指的指纹信息与其他手指的指纹信息差异大，而且大拇指的指纹信息一旦相似，其相似度较高可以达到80％，因此，为了便于识别，给大拇指分配的指纹权重值往往较高。比如，可以将权重值分配如下：
1、当采集的合法用户指纹中只有1个大拇指指纹时，设置大拇指的权重为1/2，则其他手指的平均权重为：
2、当采集的合法用户指纹中含有2个大拇指指纹时，设置每个大拇指的权重为1/4，则其他手指的平均权重为：
理论上，当两个指纹的相似度达到100％，才将其判定为同一指纹，但由于技术有限，只能无限逼近理论数值，本实施例中，可以将判断两个指纹的相似度的标准数值定义为75％，则合法指纹数据库中多指纹叠加综合数值A也是75％。即采集指纹的多指纹叠加综合数值大于等于75％便可解锁成功，否则解锁失败，将该指纹视为无效指纹。当然，可以将判断两个指纹的相似度的标准数值定义为75％以外的其他值。
三、制定指纹综合算法并存储。
将采集的指纹信息在一对多的基础上进行匹配，获取新采集的每个指
纹与合法用户的指纹信息数据库中所有指纹逐一对比获取相似度中最高的相似数值，则多个手指的指纹叠加综合算法如下：
1、当采集的合法用户指纹中只有1个大拇指指纹时，可以设置大拇指类型的指纹信息的预设权重为1/2，则
其中，N为指纹信息的总数量，N≥2，A1为至少两个指纹信息的指纹叠加综合数值，p为大拇指类型的指纹信息的最高相似度，为第二个所述大拇指类型的指纹信息的所述最高相似度，为q1、q2、...、qN-2分别为其他指纹信息的最高相似度。
2、当采集的合法用户指纹中含有2个大拇指指纹时，可以设置每个大拇指类型的指纹信息的预设权重为1/4，则
其中，N为至少两个指纹信息的数量，N≥2，A2为至少两个指纹信息的指纹叠加综合数值，p1为第一个大拇指类型的指纹信息的最高相似度，p2为第二个大拇指类型的指纹信息的最高相似度，为q1、q2、...、qN-2分别为其他指纹信息的最高相似度。
将两种情况下的多指纹叠加综合算法分别存储到存储器A1和存储器A2中，便于后期调用。至此，初始录入步骤已全部完成。
在上述初始设置的基础上，当进行指纹解锁验证时，包括以下步骤：
一、输入解锁用户的指纹信息。
当用户使用指纹解锁时，用户先将指纹输入指纹识别器，指纹识别器可以先采用单指纹识别方法进行一对多对比匹配，若单指纹识别通过，则直接解锁；若单指纹识别失败，则调用上述的多指纹叠加综合方法解锁。
在指纹识别器进行一对多对比的同时，记录下每个新采集的指纹与合
法用户指纹数据库中所有指纹逐一对比获取相似度，记录每个指纹的最高相似度数值。
二、计算解锁指纹的综合数值。
根据每个指纹的最高相似度数值大小，判断新采集指纹中的大拇指个数m，则m＝1或2。
1、当m＝1时，将最大相似度数值赋予p，其余的最高相似度数值赋予q1、q2…qN-1，并调用存储器A1的计算公式计算新采集指纹的A1数值：
2、当m＝2时，将最大的两个相似度数值赋予p1和p2，其余的最高相似度数值赋予q1、q2…qN-2，并调用存储器A2的计算公式计算新采集指纹的A2数值：
三、对比输入指纹的综合数值。
调用新采集指纹的多指纹叠加综合数值A1或者A2的数值，与合法指纹数据库中多指纹叠加综合数值A＝75％进行大小比较，以判断输入指纹是否为合法指纹。其中：
(1)当A1(或者A2)≥A时，确定新输入的指纹为合法指纹，成功解锁；
(2)当A1(或者A2)＜A时，确定新输入的指纹为非法指纹，解锁失败。
图4示出了根据本发明的实施例的终端的框图。如图4所示，根据本发明的实施例的终端4，具有指纹验证功能，包括：至少一个处理器41，例如CPU，至少一个通信总线42以及存储器43；通信总线42用于实现这些组件之间的连接通信；存储器43可以是高速RAM存储器，也可以是非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。存储器43中存储一组程序代码，且处理器41用于调用存储器43中存储的程序代码，用于执行以下操作：
接收至少两个指纹信息；
确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；
根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；
判断所述指纹叠加综合数值是否达到预设综合数值；
根据判断结果，确定是否通过指纹验证。
在上述技术方案中，所述处理器41确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度，具体操作为：
确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度；以及
将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
在上述技术方案中，所述处理器41在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，计算所述至少两个指纹信息的指纹叠加综合数值之前，还执行：
根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；以及
在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
在上述技术方案中，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：
A＝s×p+sq×(q1+q2+…+qN-1)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-1分别为所述其他指纹信息的所述最高相似度。
在上述技术方案中，当所述大拇指类型的指纹信息的数量为2时，对
应的所述预定指纹叠加算法公式为：
A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)
其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、...、qN-2分别为所述其他指纹信息的所述最高相似度。
在上述技术方案中，所述处理器41在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还执行：
根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
以上结合附图详细说明了本发明的技术方案，通过本发明的技术方案，改善了现有的指纹验证功能采集指纹数量少、判别方法单一以及容易发生误识别的缺陷，增加指纹数量提升了指纹验证的安全性，再根据相似度的综合值来判断验证是否通过，还可以避免因手指污渍等客观原因造成的无法识别等情况，更加适应用户的实际需求
以上仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。
Claims (18)
- 一种指纹验证方法，用于终端，其特征在于，包括：接收至少两个指纹信息；确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；判断所述指纹叠加综合数值是否达到预设综合数值；根据判断结果，确定是否通过指纹验证。
- 根据权利要求1所述的指纹验证方法，其特征在于，所述确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度，具体包括：确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度；以及将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
- 根据权利要求2所述的指纹验证方法，其特征在于，在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还包括：根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；以及在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
- 根据权利要求3所述的指纹验证方法，其特征在于，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：A＝s×p+sq×(q1+q2+…+qN-1)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述 大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-1分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求3所述的指纹验证方法，其特征在于，当所述大拇指类型的指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-2分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求4或5所述的指纹验证方法，其特征在于，在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还包括：根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。 - 一种指纹验证装置，用于终端，其特征在于，包括：接收单元，接收至少两个指纹信息；相似度确定单元，确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度；计算单元，根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；验证单元，判断所述指纹叠加综合数值是否达到预设综合数值，以供根据判断结果，确定是否通过指纹验证。
- 根据权利要求7所述的指纹验证装置，其特征在于，所述相似度确定单元具体用于：确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度，并将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
- 根据权利要求8所述的指纹验证装置，其特征在于，还包括：大拇指数量确定单元，在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，所述计算所述至少两个指纹信息的指纹叠加综合数值之前，根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；公式选择单元，在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
- 根据权利要求9所述的指纹验证装置，其特征在于，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：A＝s×p+sq×(q1+q2+…+qN-1)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-1分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求9所述的指纹验证装置，其特征在于，当所述大拇指类型的指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-2分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求10或11所述的指纹验证装置，其特征在于，还包括：设置单元，在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
其中，sq为所述其他指纹信息的平均权重，s为所述大拇指类型的指纹信息的平均权重，N为所述至少两个指纹信息的数量，n为所述大拇指类型的指纹信息的数量。 - 一种终端，具有指纹验证功能，其特征在于，所述终端包括处理器和存储器，其中，所述存储器中存储一组程序代码，且所述处理器用于调用所述存储器中存储的程序代码，用于执行以下操作：接收至少两个指纹信息；确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似 度；根据所述每个指纹信息的预设权重与所述预设指纹信息的相似度和预定指纹叠加算法公式，计算所述至少两个指纹信息的指纹叠加综合数值；判断所述指纹叠加综合数值是否达到预设综合数值；根据判断结果，确定是否通过指纹验证。
- 根据权利要求13所述的终端，其特征在于，所述处理器确定所述至少两个指纹信息中的每个指纹信息与预设指纹信息的相似度，具体操作为：确定所述至少两个指纹信息中的任一指纹信息与多个所述预设指纹信息中的每个所述预设指纹信息的相似度；以及将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息的手指类型。
- 根据权利要求14所述的终端，其特征在于，所述处理器在所述将具有最高相似度的所述预设指纹信息的手指类型确定为所述任一指纹信息对应的手指类型之后，计算所述至少两个指纹信息的指纹叠加综合数值之前，还执行：根据所述每个指纹信息对应的所述手指类型，确定所述手指类型为大拇指类型的指纹信息的数量；以及在多个预定指纹叠加算法公式中选择与数量对应的所述预定指纹叠加算法公式。
- 根据权利要求15所述的终端，其特征在于，当所述大拇指类型的指纹信息的数量为1时，对应的所述预定指纹叠加算法公式为：A＝s×p+sq×(q1+q2+…+qN-1)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p为所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-1分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求15所述的终端，其特征在于，当所述大拇指类型的 指纹信息的数量为2时，对应的所述预定指纹叠加算法公式为：A＝s×(p1+p2)+sq×(q1+q2+…+qN-2)其中，A为所述至少两个指纹信息的所述指纹叠加综合数值，s为所述大拇指类型的指纹信息的平均权重，sq为所述至少两个指纹信息中的所述大拇指类型的指纹信息以外的其他指纹信息的平均权重，p1为第一个所述大拇指类型的指纹信息的所述最高相似度，p2为第二个所述大拇指类型的指纹信息的所述最高相似度，N为所述至少两个指纹信息的数量，N≥2，q1、q2、…、qN-2分别为所述其他指纹信息的所述最高相似度。
- 根据权利要求16或17所述的终端，其特征在于，所述处理器在所述计算所述至少两个指纹信息的指纹叠加综合数值之前，还执行：根据接收到的设置命令，设置所述大拇指类型的指纹信息的平均权重和所述预设综合数值，其中，所述大拇指类型的指纹信息的平均权重为预定数值，所述其他指纹信息的平均权重为：
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