IJSTR >> Volume 9 - Issue 1, January 2020 Edition

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AUTHOR(S)

Zulfia Afreen. M. A, Ramachandran. A

KEYWORDS

LDA (Linear Discriminant Analysis), PCA (Principle Component Analysis), SIFT (Scale-Invariant Feature Transform), SURF (Speeded-Up Robust Features), SWLDA ( Stepwise Linear Discriminant Analysis), HCRF (Hidden Conditional Random Fields), FER (Face Expression Recognition), K-NN (K- Nearest Neighbors), LPQ (Local Phase Quality), SVM (Support Vector Machine, ISL (Indian Sign Language).

ABSTRACT

This paper is a collaboration of appearance-based linear face recognition algorithms and image processing algorithms and few methods to recognize the face features in computer vision. It deals with human facial features, biometrics, identifying leaf species, fingerprint liveness, Indian sign language. By implementing these algorithms on various fields, we can provide increased security to the real time applications.

REFERENCES

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[2] Lu Zhang, Yili Zheng, Gangliang Zhong, Qiang Wang, ”Research on leaf species identification based on principal component and linear discriminant analysis”, Springer Science+Business Media, LLC, 2017.
[3] Samiksha Agrawal, Pallavi Khatri, ”Facial Expression Detection Techniques: Based on Viola and Jones algorithm and Principal Component Analysis”, Fifth International Conference on Advanced Computing & Communication Technologies IEEE, 2015.
[4] Chengsheng Yuan, Xingming Sun, Rui Lv, “Fingerprint Liveness Detection Based on Multi-Scale LPQ and PCA”, IEEE, 2016.
[5] Sandeep Baburao Patil1, G. R. Sinha1, “Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT)”, Springer, 2016.
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