Abstract
This work explores the Human identification system using the unique vein pattern of the finger image capturing through sensor module. In today’s life fingerprint-based biometrics system is commonly used in society but it can be forged, instead vein patterns cannot be forged and it does not affected by any skin damage. Training data is created by capturing finger vein information through infrared sensor. Feature extraction carried using minutia and local binary pattern. Minutia is used to train the model, followed with k means clustering algorithms using Euclidian distance metrics. Local Binary Pattern (LBP) gives the various statistical feature vector. The feature vector model is trained by combing features of the minutia and LBP. Linear discriminant (LD), Ensemble subspace and Support Vector Machine (SVM) are used for classification. It is observed that linear discriminant classifier work better for finger vein classification.
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Sadare, V.M., Ruikar, S.D. (2020). Human Identification System Using Finger Vein Image Using Minutia and Local Binary Pattern. In: Tuba, M., Akashe, S., Joshi, A. (eds) ICT Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 1077. Springer, Singapore. https://doi.org/10.1007/978-981-15-0936-0_52
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DOI: https://doi.org/10.1007/978-981-15-0936-0_52
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