Authors :
Boby Kumar; Deepak Sharma; Dr. Navin Kr. Tyagi
Volume/Issue :
Volume 9 - 2024, Issue 5 - May
Google Scholar :
https://tinyurl.com/ymsd24zv
Scribd :
https://tinyurl.com/34vrmsp4
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAY1763
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The process of automatically identifying a
person based on their physiological and behavioural traits
is known as biometric recognition. A unimodal or
multimodal biometric system might be based on
physiological or behavioural traits. Some shortcomings in
the unimodal biometric system include spoofing, non-
universality, intra-class differences, and noisy data. Using
the face and palm images as templates, we are
implementing a multimodal biometric system. A person's
palm image can provide a wealth of detailed information
about them. Palm image have three major lines, name as
principle line, secondary line and wrinkles which are
unique in nature. Face image have more feature than any
other biometric traits. Face image is recognized easily in
less time. Combining these two biometric template gives
higher security. Message image kept secretly in the cover
image called stego image. In this steganography technique
we are using palm image as a Message and face image as
a cover image. After getting stego image Identification
process works. The important featureof identification process
id De-Stego. This feature of identification will separate the
message image (palm image) from cover image (face
image). After separation of images the decision will take
care, weather the image identified or notidentified.
Keywords :
Steganography Technique De-Stego, Face Image, Palm Image, Stego-Image Verification And Identification.
References :
- Ammour, Basma, et al. "Face–iris multimodal biometric identification system." Electronics 9.1 (2020): 85.
- Chandran, Saravanan, and Satya Bhushan Verma. "Touchless Palmprint Verification using Shock Filter, SIFT, I-RANSAC, and LPD." IOSR Journal of Computer Engineering 17.3 (2015): 01-08.
- Joseph, Teena, et al. "A multimodal biometric authentication scheme based on feature fusion for improving security in cloud environment." Journal of Ambient Intelligence and Humanized Computing (2020): 1-9.
- Karthika, P., R. Ganesh Babu, and K. Jayaram. "Biometric based on steganography image security in wireless sensor networks." Procedia Computer Science 167 (2020): 1291-1299.
- Mishra, Ashish. "Multimodal biometrics it is: need for future systems." International journal of computer applications 3.4 (2010): 28-33.
- Mustafa, Ahmed Shamil, Aymen Jalil Abdulelah, and Abdullah Khalid Ahmed. "Multimodal Biometric System Iris and Fingerprint Recognition Based on Fusion Technique." International Journal of Advanced Science and Technology 29 (2020): 7423- 7432.
- Singh, Arun Kumar, Juhi Singh, and Harsh Vikram Singh. "Steganography in images using lsb technique." International Journal of Latest Trends in Engineering and Technology (IJLTET) 5.1 (2015): 426-430.
- Satya Bhushan verma and Saravanan Chandran. "Comparative Study of FAST MSER and Harris for Palmprint Verification System." International Journal of Scientific & Engineering Research 7.12 (2016): 855-858.
- Satya Bhushan verma, and Chandran Saravanan. "Performance analysis of various fusion methods in multimodal biometric." 2018 International Conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES). IEEE, 2018.
- Satya Bhushan verma, and Saravanan Chandran. "Touchless Region based Palmprint Verification System." International Journal of Computer Science and Information Security (IJCSIS) 15.4 (2017).
- Walia, Gurjit Singh, et al. "Secure multimodal biometric system based on diffused graphs and optimal score fusion." IET Biometrics 8.4 (2019): 231-242.
- Xiong, Qi, et al. "A modified chaotic binary particle swarm optimization scheme and its application in face-iris multimodal biometric identification." Electronics 10.2 (2021): 217
The process of automatically identifying a
person based on their physiological and behavioural traits
is known as biometric recognition. A unimodal or
multimodal biometric system might be based on
physiological or behavioural traits. Some shortcomings in
the unimodal biometric system include spoofing, non-
universality, intra-class differences, and noisy data. Using
the face and palm images as templates, we are
implementing a multimodal biometric system. A person's
palm image can provide a wealth of detailed information
about them. Palm image have three major lines, name as
principle line, secondary line and wrinkles which are
unique in nature. Face image have more feature than any
other biometric traits. Face image is recognized easily in
less time. Combining these two biometric template gives
higher security. Message image kept secretly in the cover
image called stego image. In this steganography technique
we are using palm image as a Message and face image as
a cover image. After getting stego image Identification
process works. The important featureof identification process
id De-Stego. This feature of identification will separate the
message image (palm image) from cover image (face
image). After separation of images the decision will take
care, weather the image identified or notidentified.
Keywords :
Steganography Technique De-Stego, Face Image, Palm Image, Stego-Image Verification And Identification.