BibTeX:

@article{IJIRSTV2I1052,
     title={A Partial Feature Adaptive SIFT model for Morphed Image Recognition},
     author={Priyanka and Dr. Yashpal Singh},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={1},
     pages={145--150},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I1052.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Facial Recognition is having various challenges associated in it. One of critical challenge is the morphed image recognition. Morphed images can be the composed picture form generated from two or more persons. In this paper, a partial feature analysis approach is defined to recognize all persons composed in morphed image. In this work, the separation of facial physical features of person is done. Now each physical feature is represented under SIFT model to represent featured image. Finally, distance adaptive mapping is performed to recognize the image. The experimentation is here applied on real time morphed images. The adaptive results show that the high accuracy for individuals is obtained from the work.

Biometrics, SIFT (Scale Invariant Feature Transform), SURF (speeded–up Robust Features), Face recognition, recognition Rate, improved SIFT