[go: up one dir, main page]

CN113034741A - Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm - Google Patents

Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm Download PDF

Info

Publication number
CN113034741A
CN113034741A CN202110222995.6A CN202110222995A CN113034741A CN 113034741 A CN113034741 A CN 113034741A CN 202110222995 A CN202110222995 A CN 202110222995A CN 113034741 A CN113034741 A CN 113034741A
Authority
CN
China
Prior art keywords
palm vein
image
dwt
transform
palm
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110222995.6A
Other languages
Chinese (zh)
Inventor
罗笑南
陶训芳
李冀
孙波
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guilin Senming Intelligent Technology Co ltd
Guilin Xiaowei Hotel Management Co ltd
Guilin University of Electronic Technology
Original Assignee
Guilin Senming Intelligent Technology Co ltd
Guilin Xiaowei Hotel Management Co ltd
Guilin University of Electronic Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guilin Senming Intelligent Technology Co ltd, Guilin Xiaowei Hotel Management Co ltd, Guilin University of Electronic Technology filed Critical Guilin Senming Intelligent Technology Co ltd
Priority to CN202110222995.6A priority Critical patent/CN113034741A/en
Publication of CN113034741A publication Critical patent/CN113034741A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
    • G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/002—Countermeasures against attacks on cryptographic mechanisms
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06V40/15—Biometric patterns based on physiological signals, e.g. heartbeat, blood flow

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Human Computer Interaction (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Collating Specific Patterns (AREA)

Abstract

本发明提供一种基于DWT‑DCT变换加密算法的掌静脉智能锁，包括锁体、锁把手、掌静脉身份识别模块及其他身份识别模块，所述的其他身份识别模块用于开启智能锁，与掌静脉识别模块同时具备开启智能锁的功能。基于DWT‑DCT变换加密算法的掌静脉智能锁对身份注册和识别过程进行加密处理，实现识别系统受到不同攻击后依然可以准确进行掌静脉图像识别，解决现有技术的不足，提供高安全性、高鲁棒性的掌静脉识别技术。除此之外，建立的图像特征数据库可以大大缩小存储空间，形成轻量化的掌静脉身份识别系统。

Figure 202110222995

The present invention provides a palm vein smart lock based on the DWT-DCT transform encryption algorithm, comprising a lock body, a lock handle, a palm vein identity recognition module and other identity recognition modules, the other identity recognition modules are used to open the smart lock, and The palm vein recognition module also has the function of opening the smart lock. The palm vein smart lock based on the DWT‑DCT transform encryption algorithm encrypts the identity registration and identification process, so that the identification system can still accurately recognize the palm vein image after different attacks, solve the shortcomings of the existing technology, and provide high security, Highly robust palm vein recognition technology. In addition, the established image feature database can greatly reduce the storage space and form a lightweight palm vein identification system.

Figure 202110222995

Description

Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm
One, the technical field
The invention relates to a palm vein recognition intelligent lock based on an encryption algorithm.
Second, background Art
Palm vein recognition technology has become a research hotspot in the field of image processing and pattern recognition as one of the effective biometric identification technologies. However, as networks are developed more and more, information security and privacy protection become the mainstream topic of the current, and a third party masters specific and detailed personal information, so people urgently need more secure protection measures. When a user uses the palm vein intelligent lock, the registered palm vein information and the personal information are bound, illegal molecules can perform cross analysis in a plurality of registered image databases to determine the specific information of the user, and the method is particularly important for information protection of the palm vein image feature database.
The feature vector of the palm vein image is an important basis for distinguishing and identifying the palm veins, the encryption image palm vein identification method based on DWT-DCT at present is researched, the feature vector extracted from the encryption image has less research on routine, geometric, illumination and shielding attacks, most palm vein identification algorithms are carried out in a plain text domain, and the safety of palm vein image information is often ignored, so that the encryption processing on the image feature database in the palm vein identification has important significance.
Third, the invention
Aiming at the existing palm vein identification process, the invention aims to provide a palm vein intelligent lock based on a DWT-DCT (discrete wavelet transform-discrete cosine transform) encryption algorithm, which has good safety in the identification process, can still accurately identify a palm vein image after being attacked by different attacks by adopting the DWT-DCT encryption algorithm, solves the defects of the prior art, and provides a palm vein identification technology with high safety and high robustness.
The technical scheme for realizing the purpose of the invention is as follows:
a palm vein intelligent lock based on DWT-DCT transform encryption algorithm comprises a lock body, a lock handle, a palm vein identity recognition module and other identity recognition modules;
the palm vein authentication module is installed on the lock body, the built-in palm vein acquisition module acquires palm vein images of a user in a non-contact mode, and the safety of the palm vein authentication module can be improved in a non-contact mode.
The lock body is internally provided with a central processing unit which comprises a palm vein image preprocessing unit, a palm vein image encryption unit, a palm vein feature extraction unit and a palm vein matching decision identification and judgment unit, wherein:
the palm vein image preprocessing unit performs maximum ROI cutting on an original palm image acquired by acquisition equipment, performs image enhancement and suppresses noise by limiting contrast adaptive histogram equalization (CLAHE).
The palm vein image encryption unit performs Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) on the preprocessed palm vein image, and the specific flow is as follows:
s1: performing two-stage decomposition on the preprocessed palm vein image by using Discrete Wavelet Transform (DWT), and decomposing an image F (i, j) into four parts: a clearer low-frequency sub-image LL (i, j) and three high-frequency fuzzy sub-images are respectively LH (i, j), HL (i, j) and HH (i, j);
s2: performing Discrete Cosine Transform (DCT) on the four subband graphs LL (i, j), LH (i, j), HL (i, j) and HH (i, j) respectively to obtain subband coefficient matrixes which are respectively expressed as DLL (i, j), DLH (i, j), DHL (i, j) and DHH (i, j);
s3: generating a chaotic sequence H (i, j) through a Logistic Map chaotic system, and then carrying out binarization processing on the chaotic sequence H (i, j) according to the size of the palm vein image to obtain a binary matrix HB (i, j);
s4: HB (i, j) and subband diagram coefficient matrixes DLL (i, j), DLH (i, j), DHL (i, j) and DHH (i, j) are subjected to dot multiplication operation respectively to obtain encrypted image subgraphs EDLL (i, j), EDLH (i, j), EDHL (i, j) and EDHH (i, j);
s5: carrying out Inverse Discrete Cosine Transform (IDCT) on the encrypted image sub-graphs EDLL (i, j), EDLH (i, j), EDHL (i, j) and EDHH (i, j) to obtain encrypted sub-graph graphs ELL (i, j), ELH (i, j), EHL (i, j) and EHH (i, j);
s6: and performing Inverse Discrete Wavelet Transform (IDWT) on the encrypted sub-band diagrams ELL (i, j), ELH (i, j), EHL (i, j) and EHH (i, j) to obtain an encrypted palm vein image E (i, j).
The palm vein feature extraction unit firstly adopts a self-adaptive Gabor filtering method to extract palm vein features, divides a palm vein image into a plurality of sub-regions, determines a main direction of the sub-regions, calculates a standard variance for each sub-region and determines a center frequency; and secondly, carrying out VennCode coding on the palm vein features, wherein the obtained feature matrix can be used for identity recognition.
The palm vein matching decision identification and judgment unit calculates the image characteristic value after characteristic extraction and the characteristic value in the image characteristic value database by adopting a Hamming distance algorithm, sets a threshold value, if the value is smaller than the threshold value, the identity authentication is successful, otherwise, the user does not exist.
The other identity recognition modules are used for unlocking the intelligent lock and have the function of unlocking the intelligent lock together with the palm vein recognition module.
The principle of the palm vein intelligent lock based on the DWT-DCT transform encryption algorithm is as follows: the palm vein intelligent lock has other identification and palm vein identification modes to unlock. When the user adopts other identification modes, the operation can be carried out according to the authentication mode. For example: if the key is used, the key is inserted into the key hole and rotated to be opened; if the fingerprint is used for unlocking, the registered finger is placed at the finger print identification designated position of the intelligent lock; if the IC card identification is used, the IC card is placed at the IC card identification position of the intelligent lock; and so on. When a user selects a palm vein identification mode to unlock the lock, firstly, a palm of registered information is placed at the position about 8cm in front of a palm vein acquisition module, a near-infrared camera acquires a palm vein image of the user, then, the image is subjected to maximum ROI cutting, image enhancement is carried out through limiting contrast self-adaptive histogram equalization (CLAHE), a preprocessed image is obtained, then, an encryption algorithm is carried out on the image, feature extraction is carried out on the image, and finally, matching decision is carried out on a feature value to be compared and a feature value stored in the device. If the matching is successful and the identity authentication is correct, the lock can be automatically opened, otherwise, no matching item is displayed.
The palm vein intelligent lock based on the DWT-DCT transform encryption algorithm has the following advantages by adopting vein identification: the palm vein has good universality and uniqueness. The palm vein texture is different from person to person, even from the left hand and the right hand of the same person. The palm vein is positioned in the skin, and compared with biological characteristics such as fingerprints and palm prints, the palm vein anti-fake method has the characteristics of being not easy to damage and steal and the like, and compared with biological characteristics such as irises and human faces, the palm vein anti-fake method has the advantages of being high in information confidentiality, large in fake difficulty, low in manufacturing cost of acquisition equipment, easy to apply in a large scale and the like.
The invention has the beneficial effects that:
(1) compared with the traditional palm vein recognition intelligent lock, the invention provides the palm vein recognition method based on the DWT-DCT (discrete wavelet transform-discrete cosine transform) encrypted image. The method combines the feature vector of the palm vein image with the encryption technology, realizes that the palm vein image can be accurately identified after being attacked by different kinds, solves the defects of the prior art, and provides the palm vein identification technology with high safety and high robustness.
(2) The database established by the invention is an image characteristic value database, palm vein images are encrypted through a DWT-DCT (discrete wavelet transform-discrete cosine transform) algorithm to form an encrypted image database, and then the characteristics of the encrypted images in the database are extracted, so that the image characteristic database is established. The established image characteristic database can greatly reduce the storage space and form a light palm vein identification system.
(3) In the identification process, the encryption protection is carried out when the characteristic database is established, and the palm vein image to be identified is encrypted in the user identification process, so that the double encryption mode improves the higher safety of the whole palm vein identity identification system.
Fourthly, explanation of the attached drawings:
fig. 1 is a conventional palm vein recognition flowchart;
FIG. 2 is a flow chart of palm vein identification based on an encryption algorithm;
FIG. 3 is a palm vein image encryption algorithm diagram;
fig. 4 is a palm vein image feature database building block diagram.
Fifth, detailed description of the invention
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The conventional palm vein image identification process is shown in fig. 1, and each step plays an irreplaceable role in the whole palm vein identification system. Image acquisition: and shooting a palm vein image of the user by adopting a near-infrared camera. Image preprocessing: and performing maximum ROI cutting on the acquired original palm image, and performing image enhancement through limiting contrast adaptive histogram equalization (CLAHE) to obtain clearer palm vein information. Image feature extraction: and extracting the palm vein characteristics by using a self-adaptive Gabor filtering method. Image feature matching: and after the characteristic values are coded, matching and identifying by utilizing the Hamming distance.
As shown in fig. 2, the palm vein image recognition process is encrypted, first, the palm vein image to be recognized is subjected to preprocessing, then the preprocessed palm vein image is encrypted, then the encrypted palm vein image is subjected to feature extraction, finally, the distance between the feature value and the feature value in the encrypted feature database is calculated through a hamming distance algorithm, a threshold value a is set, if the distance is smaller than a, the user identity authentication is successful, otherwise, the user does not exist. Therefore, the palm vein recognition result is obtained, and the palm vein intelligent lock can be opened immediately after the user identity authentication is successful.
As shown in fig. 3, the palm vein image is encrypted, and the specific process is as follows:
s1: performing two-stage decomposition on the preprocessed palm vein image by using Discrete Wavelet Transform (DWT), and decomposing an image F (i, j) into four parts: a clearer low-frequency sub-image LL (i, j) and three high-frequency fuzzy sub-images are respectively LH (i, j), HL (i, j) and HH (i, j);
s2: performing Discrete Cosine Transform (DCT) on the four subband graphs LL (i, j), LH (i, j), HL (i, j) and HH (i, j) respectively to obtain subband coefficient matrixes which are respectively expressed as DLL (i, j), DLH (i, j), DHL (i, j) and DHH (i, j);
s3: generating a chaotic sequence H (i, j) through a Logistic Map chaotic system, and then carrying out binarization processing on the chaotic sequence H (i, j) according to the size of the palm vein image to obtain a binary matrix HB (i, j);
s4: HB (i, j) and subband diagram coefficient matrixes DLL (i, j), DLH (i, j), DHL (i, j) and DHH (i, j) are subjected to dot multiplication operation respectively to obtain encrypted image subgraphs EDLL (i, j), EDLH (i, j), EDHL (i, j) and EDHH (i, j);
s5: carrying out Inverse Discrete Cosine Transform (IDCT) on the encrypted image sub-graphs EDLL (i, j), EDLH (i, j), EDHL (i, j) and EDHH (i, j) to obtain encrypted sub-graph graphs ELL (i, j), ELH (i, j), EHL (i, j) and EHH (i, j);
s6: and performing Inverse Discrete Wavelet Transform (IDWT) on the encrypted sub-band diagrams ELL (i, j), ELH (i, j), EHL (i, j) and EHH (i, j) to obtain an encrypted palm vein image E (i, j).
As shown in fig. 4, the establishing of the palm vein image Feature Database is to encrypt the palm vein image through DWT-DCT transform to form an encrypted image Database DWTDCT _ Database, and then perform Feature extraction on the encrypted image in the Database, thereby establishing an image Feature Database DWTDCT _ Feature. The established image characteristic database can greatly reduce the storage space and form a light palm vein identification system.
Because the technical scheme of the invention is sufficient, the DWT-DCT transformation algorithm is well applied to the field of palm vein intelligent locks, and the encryption processing is carried out only in the palm vein identification process by adopting the DWT-DCT transformation algorithm, the palm vein identification method has the advantages that the palm vein image identification can still be accurately carried out after the identification system is attacked by different attacks, the defects of the prior art are overcome, and the palm vein identification technology with high safety and high robustness is provided. In addition, the established image feature database can greatly reduce the storage space, and a light palm vein identification system is formed.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (5)

1.一种基于DWT-DCT变换加密算法的掌静脉智能锁，其特征在于：包括锁体、锁把手、掌静脉身份识别模块及其他身份识别模块。1. a palm vein intelligent lock based on DWT-DCT transformation encryption algorithm, is characterized in that: comprise lock body, lock handle, palm vein identification module and other identification modules. 2.根据权利要求1所述基于DWT-DCT变换加密算法的掌静脉智能锁，其特征在于：所述掌静脉认证模块安装在锁体上，其内置的掌静脉采集模块是用非接触式采集用户的掌静脉图像，非接触的方式可以提高其安全性。2. the palm vein intelligent lock based on the DWT-DCT transform encryption algorithm according to claim 1, is characterized in that: described palm vein authentication module is installed on the lock body, and its built-in palm vein acquisition module is to use non-contact acquisition The user's palm vein image, non-contact way can improve its safety. 3.根据权利要求1所述基于DWT-DCT变换加密算法的掌静脉智能锁，其特征在于：所述锁体内置的中央处理器包括掌静脉图像预处理单元、掌静脉图像加密单元、掌静脉特征提取单元和掌静脉匹配决策识别判断单元，其中：3. The palm vein intelligent lock based on the DWT-DCT transform encryption algorithm according to claim 1, wherein the built-in central processing unit of the lock body comprises a palm vein image preprocessing unit, a palm vein image encryption unit, a palm vein image Feature extraction unit and palm vein matching decision recognition and judgment unit, wherein: 掌静脉图像预处理单元是对采集设备采集到的原始手掌图像进行最大化ROI切割，通过限制对比度自适应直方图均衡(CLAHE)进行图像增强并抑制噪声；The palm vein image preprocessing unit is to maximize the ROI cutting of the original palm image collected by the acquisition device, and to enhance the image and suppress noise by limiting the contrast adaptive histogram equalization (CLAHE); 掌静脉图像加密单元是对预处理后的掌静脉图像进行离散小波变换(DWT)和离散余弦变换(DCT)，对图像进行加密处理；The palm vein image encryption unit performs discrete wavelet transform (DWT) and discrete cosine transform (DCT) on the preprocessed palm vein image, and encrypts the image; 掌静脉特征提取单元采用首先采用自适应Gabor滤波方法提取手掌静脉特征，将掌静脉图像划分为若干子区域，并对其确定主方向，然后对每块子区域计算标准方差，确定中心频率；其次对手掌静脉特征进行VeinCode编码，得到的特征矩阵可用于身份识别；The palm vein feature extraction unit first adopts the adaptive Gabor filtering method to extract the palm vein features, divides the palm vein image into several sub-regions, and determines the main direction, and then calculates the standard deviation of each sub-region to determine the center frequency; secondly Perform VeinCode encoding on the palm vein features, and the obtained feature matrix can be used for identification; 掌静脉匹配决策识别判断单元是采用汉明距离算法对特征提取后的图像特征值与图像特征值数据库中的特征值进行计算，设置一个阀值，若小于该阀值则身份认证成功，否则不存在该用户。The palm vein matching decision recognition and judgment unit uses the Hamming distance algorithm to calculate the image feature value after feature extraction and the feature value in the image feature value database, and set a threshold value. If it is less than the threshold value, the identity authentication is successful, otherwise it is not The user exists. 4.根据权利要求3所述的基于DWT-DCT变换加密算法的掌静脉智能锁，其特征在于：所述的掌静脉图像加密单元的具体处理步骤如下：4. the palm vein intelligent lock based on DWT-DCT transform encryption algorithm according to claim 3, is characterized in that: the concrete processing steps of described palm vein image encryption unit are as follows: S1：利用离散小波变换(DWT)对预处理后的掌静脉图像进行二级分解，把图像F(i,j)分解成四部分：一个较清晰低频子图LL(i,j)和三个高频模糊子图分别为LH(i,j)，HL(i,j)，HH(i,j)；S1: Use discrete wavelet transform (DWT) to perform secondary decomposition on the preprocessed palm vein image, and decompose the image F(i,j) into four parts: a clearer low-frequency subgraph LL(i,j) and three The high-frequency fuzzy subgraphs are LH(i,j), HL(i,j), HH(i,j) respectively; S2：分别对四个子带图LL(i,j)，LH(i,j)，HL(i,j)，HH(i,j)进行离散余弦变化DCT变换获得子带系数矩阵，分别表示为DLL(i,j)，DLH(i,j)，DHL(i,j)，DHH(i,j)；S2: Perform discrete cosine DCT transformation on the four subband images LL(i,j), LH(i,j), HL(i,j), HH(i,j) respectively to obtain subband coefficient matrices, which are expressed as DLL(i,j), DLH(i,j), DHL(i,j), DHH(i,j); S3：通过Logistic Map混沌系统生成混沌序列H(i,j)，再按照掌静脉图像的大小对其进行二值化处理，获得二值矩阵HB(i,j)；S3: Generate a chaotic sequence H(i,j) through the Logistic Map chaotic system, and then binarize it according to the size of the palm vein image to obtain a binary matrix HB(i,j); S4：HB(i,j)和子带图系数矩阵DLL(i,j)，DLH(i,j)，DHL(i,j)，DHH(i,j)分别进行点乘操作，得到加密图像子图EDLL(i,j)，EDLH(i,j)，EDHL(i,j)，EDHH(i,j)；S4: HB(i,j) and subband image coefficient matrices DLL(i,j), DLH(i,j), DHL(i,j), DHH(i,j) perform point multiplication respectively to obtain encrypted image Figure EDLL(i,j), EDLH(i,j), EDHL(i,j), EDHH(i,j); S5：对加密图像子图EDLL(i,j)，EDLH(i,j)，EDHL(i,j)，EDHH(i,j)先进行离散余弦逆变换(IDCT)，得到加密子带图ELL(i,j)，ELH(i,j)，EHL(i,j)，EHH(i,j)；S5: Perform inverse discrete cosine transform (IDCT) on the encrypted image subgraphs EDLL(i,j), EDLH(i,j), EDHL(i,j), and EDHH(i,j) to obtain the encrypted subband graph ELL (i,j), ELH(i,j), EHL(i,j), EHH(i,j); S6：再对加密子带图ELL(i,j)，ELH(i,j)，EHL(i,j)，EHH(i,j)进行离散小波逆变换(IDWT)，得到加密掌静脉图像E(i,j)。S6: Perform inverse discrete wavelet transform (IDWT) on the encrypted subband images ELL(i,j), ELH(i,j), EHL(i,j), EHH(i,j) to obtain the encrypted palm vein image E (i,j). 5.根据权利要求1所述基于DWT-DCT变换加密算法的掌静脉智能锁，其特征在于：所述的其他身份识别模块用于开启智能锁，与掌静脉识别模块同时具备开启智能锁的功能。5. the palm vein intelligent lock based on the DWT-DCT transformation encryption algorithm according to claim 1, it is characterized in that: described other identity recognition modules are used to open the intelligent lock, have the function of opening the intelligent lock simultaneously with the palm vein identification module .
CN202110222995.6A 2021-03-02 2021-03-02 Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm Pending CN113034741A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110222995.6A CN113034741A (en) 2021-03-02 2021-03-02 Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110222995.6A CN113034741A (en) 2021-03-02 2021-03-02 Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm

Publications (1)

Publication Number Publication Date
CN113034741A true CN113034741A (en) 2021-06-25

Family

ID=76464885

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110222995.6A Pending CN113034741A (en) 2021-03-02 2021-03-02 Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm

Country Status (1)

Country Link
CN (1) CN113034741A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118116040A (en) * 2023-12-06 2024-05-31 珠海易胜智能科技有限公司 Palm vein recognition method

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1266346A2 (en) * 2000-03-23 2002-12-18 Cross Match Technologies, Inc. Piezometric identification device and applications thereof
US20030007674A1 (en) * 2001-04-27 2003-01-09 Osamu Tsujii Image processing apparatus and method
WO2012153021A1 (en) * 2011-05-06 2012-11-15 Morpho Methods for biometric registration and verification, and related systems and devices
CN104091145A (en) * 2013-06-02 2014-10-08 广东智冠实业发展有限公司 Human palm vein feature image acquisition method
TW201447625A (en) * 2013-06-07 2014-12-16 Univ Chien Hsin Sci & Tech Palm vein recognition method using adaptive Gabor filter
CN106446867A (en) * 2016-10-13 2017-02-22 济南大学 Double-factor palmprint identification method based on random projection encryption
CN108776790A (en) * 2018-06-06 2018-11-09 海南大学 Face encryption recognition methods based on neural network under cloud environment
CN111696228A (en) * 2020-04-22 2020-09-22 桂林森明智能科技有限责任公司 Intelligent palm print and palm vein lock based on compressed sensing method
CN112163542A (en) * 2020-10-12 2021-01-01 桂林电子科技大学 A Palmprint Confidentiality Authentication Method Based on ElGamal Encryption

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1266346A2 (en) * 2000-03-23 2002-12-18 Cross Match Technologies, Inc. Piezometric identification device and applications thereof
US20030007674A1 (en) * 2001-04-27 2003-01-09 Osamu Tsujii Image processing apparatus and method
WO2012153021A1 (en) * 2011-05-06 2012-11-15 Morpho Methods for biometric registration and verification, and related systems and devices
CN104091145A (en) * 2013-06-02 2014-10-08 广东智冠实业发展有限公司 Human palm vein feature image acquisition method
TW201447625A (en) * 2013-06-07 2014-12-16 Univ Chien Hsin Sci & Tech Palm vein recognition method using adaptive Gabor filter
CN106446867A (en) * 2016-10-13 2017-02-22 济南大学 Double-factor palmprint identification method based on random projection encryption
CN108776790A (en) * 2018-06-06 2018-11-09 海南大学 Face encryption recognition methods based on neural network under cloud environment
CN111696228A (en) * 2020-04-22 2020-09-22 桂林森明智能科技有限责任公司 Intelligent palm print and palm vein lock based on compressed sensing method
CN112163542A (en) * 2020-10-12 2021-01-01 桂林电子科技大学 A Palmprint Confidentiality Authentication Method Based on ElGamal Encryption

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118116040A (en) * 2023-12-06 2024-05-31 珠海易胜智能科技有限公司 Palm vein recognition method

Similar Documents

Publication Publication Date Title
Yuan et al. Fingerprint liveness detection based on multi-scale LPQ and PCA
CN101308542A (en) High-precision Palmprint Security Identification Method Based on Log-Gabor Mixed Filter Phase Feature Encryption
Vyas et al. Iris recognition using 2-D Gabor filter and XOR-SUM code
CN101286195A (en) High-precision Palmprint Recognition Method Based on Two-dimensional Orthogonal Log-Gabor Filter
Abdo et al. Iris recognition based on histogram equalization and discrete cosine transform
Yang et al. Cross-database attack of different coding-based palmprint templates
Pakutharivu et al. A comprehensive survey on fingerprint recognition systems
Meetei et al. A variant of cancelable iris biometric based on BioHashing
Sardar et al. Implementation of face recognition system using BioCryptosystem as template protection scheme
CN1489105A (en) Iris Recognition Method Based on Wavelet Analysis and Zero-Crossing Description
CN113034741A (en) Palm vein intelligent lock based on DWT-DCT (discrete wavelet transform-discrete cosine transform) transform encryption algorithm
Kumar et al. Finger vein based human identification and recognition using Gabor filter
Haddada et al. A biometric watermarking approach of fingerprint images by DLDA Gabor face features without altering minutiae
Shashikala et al. Palmprint Identification based on DWT, DCT and QPCA
Ghouzali Watermarking based multi-biometric fusion approach
Biradar Personal identification using palmprint biometrics based on principal line approach
Ghouzali Multimodal biometric watermarking-based transfer learning authentication
Divan et al. A fingerprint matching technique using minutiae based algorithm for voting system: A survey
Al-Ani et al. Efficient watermarking based an robust biometric features
Bansal et al. A survey on fingerprint recognition system
Kanchana et al. Quadtree decomposition for palm print feature representation in palmprint recognition system
Nguyen-Thanh et al. Multiple Watermarking with Biometric Data Using Discrete Curvelets and Contourlets
Haddada et al. Watermarking signal fusion in multimodal biometrics
Fernandez et al. Biometric watermarking: an application-based review
Qadir et al. A New Feature Extraction Approach in Classification for Improving the Accuracy in Iris Recognition

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20210625