&amp;#x201C;Feature level fusion of face, palm vein and palm print modalities using Discrete Cosine Transform&amp;#x201D;

Gupta, Aditya; Malage, Abhijit; More, Dhiraj; Hemane, Priya M.; Bhautmage, Prayanti; Dhandekar, Duhita

doi:10.1109/icaetr.2014.7012805

Cited by 11 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gupta et al. [38] proposed another feature‐level fusion system for palmprint, palm‐vein, and face features based on the Discrete Cosine Transform (DCT). Wang et al.…”

Section: Related Workmentioning

confidence: 99%

“…At the feature level, Yang et al [37] utilised a Canonical Correlation Analysis (CCA) to measure the linear relationship between two modalities for fusion. Gupta et al [38] proposed another feature-level fusion system for palmprint, palm-vein, and face features based on the Discrete Cosine Transform (DCT). Wang et al [39] proposed a system for fusing palmprint and palm-vein based on the Locality Preserving Projection (LPP).…”

Section: Deep Learning Based Handcrafted Based Cancellable Biometricsmentioning

confidence: 99%

See 1 more Smart Citation

Extraction of intersecting palm‐vein and palmprint features for cancellable identity verification

Lee,

Oh,

Toh

2024

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

A novel method based on the cross‐modality intersecting features of the palm‐vein and the palmprint is proposed for identity verification. Capitalising on the unique geometrical relationship between the two biometric modalities, the cross‐modality intersecting points provides a stable set of features for identity verification. To facilitate flexibility in template changes, a template transformation is proposed. While maintaining non‐invertibility, the template transformation allows transformation sizes beyond that offered by the conventional means. Extensive experiments using three public palm databases are conducted to verify the effectiveness the proposed system for identity recognition.

show abstract

“…Gupta et al. [38] proposed another feature‐level fusion system for palmprint, palm‐vein, and face features based on the Discrete Cosine Transform (DCT). Wang et al.…”

Section: Related Workmentioning

confidence: 99%

Section: Deep Learning Based Handcrafted Based Cancellable Biometricsmentioning

confidence: 99%

Extraction of intersecting palm‐vein and palmprint features for cancellable identity verification

Lee,

Oh,

Toh

2024

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

show abstract

“…A feature descriptor, namely histogram of vectors was proposed in a palm vein and palm crease feature extraction stage. Gupta et al [85] proposed a multimodal biometric system using face modality combined with palmprint and palm vein modality. The proposed methodology used a local statistical method in which pre-defined block of the discrete cosine transform (DCT) coefficient was used to calculate a standard deviation and store them as a feature vector.…”

Section: Palm Vein Fusion Recognitionmentioning

confidence: 99%

Review of palm vein recognition

Elliott

Lin

et al. 2019

IET biom.

View full text Add to dashboard Cite

As a new research focus in biometrics, palm vein recognition has attracted people's attention because of high security, liveness-detection, user acceptability and convenience. Palm vein recognition exhibits high security, as it uses the network of blood vessels underneath palm skin for recognition. As palm vein is interior biological information of the body, vein patterns are much harder for intruders to copy compared to other biometric features. Palm vein is mostly invisible to the human eyes; they are commonly captured under near-infrared light. Under its natural state, the veins of the palm are concealed naturally and, for most of time people's hands are in the gesture of half fist. This study presents a comprehensive overview of recent research progress of palm vein recognition, from the basic background knowledge to data acquisition, public database, preprocessing, feature extraction and matching. In addition, the study focuses on palm vein-related fusion. Ultimately, the authors discuss the challenges and future perspectives in palm vein recognition for further works.

show abstract

“…The recognition technique of fusion is accurate and efficient. Aditya Gupta et al, [7] proposed a feature level fusion of face, palm vein and palmprint modalities using DCT for feature extraction to calculate the standard deviation and stored as feature vector. Results showed better result in multimodal rather in unimodal.…”

Section: Literature Surveymentioning

confidence: 99%

HVDLP : Horizontal Vertical Diagonal Local Pattern Based Face Recognition

Chandrakala¹,

Kumar²,

K³

et al. 2017

SIPIJ

View full text Add to dashboard Cite

Face image is an efficient biometric trait to recognize human beings without expecting any co-operation from a person. In this paper, we propose HVDLP: Horizontal Vertical Diagonal Local Pattern based face recognition using Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The face images of different sizes are converted into uniform size of 108×990and color images are converted to gray scale images in pre-processing. The Discrete Wavelet Transform (DWT) is applied on pre-processed images and LL band is obtained with the size of 54×45. The Novel concept of HVDLP is introduced in the proposed method to enhance the performance. The HVDLP is applied on 9×9 sub matrix of LL band to consider HVDLP coefficients. The local Binary Pattern (LBP) is applied on HVDLP of LL band. The final features are generated by using Guided filters on HVDLP and LBP matrices. The Euclidean Distance (ED) is used to compare final features of face database and test images to compute the performance parameters.

show abstract

“Feature level fusion of face, palm vein and palm print modalities using Discrete Cosine Transform”

Cited by 11 publications

References 11 publications

Extraction of intersecting palm‐vein and palmprint features for cancellable identity verification

Extraction of intersecting palm‐vein and palmprint features for cancellable identity verification

Review of palm vein recognition

HVDLP : Horizontal Vertical Diagonal Local Pattern Based Face Recognition

Contact Info

Product

Resources

About