A Multimodal Biometric Recognition System Based on Fusion of Palmprint, Fingerprint and Face

Chaudhary, Sheetal; Nath, Rajender

doi:10.1109/artcom.2009.224

Cited by 32 publications

(9 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The minimum distance rule (MDR) is adopt for fusion of the match score level and compare the outcome of the multimodality recognition with the results of the unimodal palmprint and face recognition. The results shows the performance of multimodality outperforms the unimodal recognition and the correctness can reach 100% based on ORL and PolyU database using the fusion rule at the match score level [3].…”

Section: Literature Reviewmentioning

confidence: 92%

Review on Face, Ear and Signature for Human Identification

Bhable¹,

Tharewal²,

Gite³

et al. 2018

IJCA

View full text Add to dashboard Cite

Biometrics is a rising technology, which has been extensively used in robotics areas financial services, forensics, secured access, prison security, medical, telecommunication, ecommerce, government, traffic, health care the security issue are more essential. Biometric-based personal identification is high applicability in an extensive range of security application but Multimodal biometrics is the way to reduce time density and give better recognition rate. The concert rate of unimodal biometric is frequently reduced due to the user mode and physiological defects. We have referred papers related to face, ear and signature. In this paper, we discuss different methods of Face, Ear and signature for recognition and identification.

show abstract

Section: Literature Reviewmentioning

confidence: 92%

Review on Face, Ear and Signature for Human Identification

Bhable¹,

Tharewal²,

Gite³

et al. 2018

IJCA

View full text Add to dashboard Cite

show abstract

“…It is generally accepted that the earlier the fusion approach is applied, the more efficient the resulting system is due to the reduction of the amount of information which occurs in the different stages of the verification system (feature extraction, scores, decisions) [4]. Table II The analysis of the works, considered in Table II, shows that image fusion is mostly carried out by relatively simple methods such as superposition and combination [20] and recently by more sophisticated methods based, among others, on discrete wavelet transformation [13], discrete cosine transformation and contourlet transformation [21] In addition, we notice that fusing signals improves the performances of the unimodal biometric system.…”

Section: State Of Art Of Biometric Signal Fusionmentioning

confidence: 99%

Watermarking signal fusion in multimodal biometrics

Haddada¹,

Dorizzi

Amara³

2014

International Image Processing, Applications and Systems Conference

View full text Add to dashboard Cite

In this paper, we propose a new approach based on watermarking for fusing biometric modalities. The main idea of the proposed approach is to use the watermark both for security purpose and as an additional information related to the person, therefore increasing the personal data used for verification. The host image of the face is watermarked in the multi-resolution space by the palmprint using a watermarking technique based on wavelet packet decomposition. For the verification stage, the characterization of the watermarked face is provided by Gabor filters while classification is performed by SVMs. The experimental results show that this technique ensures a significant performance improvement in both identity verification and biometric security over the use of a single system.

show abstract

“…A multimodal biometric recognition system based on fusion of palmprint, fingerprint and face is proposed in [10]. Palmprint and knuckleprint is used to make multimodal biometric system [11].…”

Section: Introductionmentioning

confidence: 99%

An automated multimodal biometric system and fusion

Kumar

Nigam

Tiwari

et al. 2014

2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)

View full text Add to dashboard Cite

This paper proposed an automated multimodal biometric system and fusion technique to eliminates the unimodal limitations. Unimodal biometric system has many problems like occlusion, illumination, pose variation. This proposed multimodal biometric system use face, left ear, left palm, right palmprint, left knuckleprint, right knuckleprint as biometric traits. This multimodal biometric system has auto positioning device for face and ear image acquisition. An another device is created for palmprint and knuckleprint acquisition. This proposed biometric system use an efficient image enhancement, SURF based feature extraction and SURF based feature matching techniques for all used biometric trait images. This system use two level fusion strategy. Feature level fusion is used to make more discriminative feature template for each biometric trait and score level fusion is used to make final fused score from all used biometric traits.

show abstract

A Multimodal Biometric Recognition System Based on Fusion of Palmprint, Fingerprint and Face

Cited by 32 publications

References 9 publications

Review on Face, Ear and Signature for Human Identification

Review on Face, Ear and Signature for Human Identification

Watermarking signal fusion in multimodal biometrics

An automated multimodal biometric system and fusion

Contact Info

Product

Resources

About