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Developing Prototype for Prosopagnosia Using PCA

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Sensors and Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 651))

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Abstract

Prosopagnosia primarily known as face blindness is a brain disorder in which a person is not able to recognize faces. In the device a portable camera is used to capture the real time movement of a person. In the main system face is detected using Voila –Jones Algorithm & hue channel detection. Using Principal Component Analysis (PCA) face is recognized. It is compared with the trained database and displays the basic information about the person if a similar trained data is found otherwise, it is declared as unknown. For new database, system can be trained at any point of time. The prototype system is trained using 30 candidates’ images including 10 images per candidate under distinct angles. The system was able to achieve 98% face detection. It provides the patients an aid to help them recognize people in front of them in seconds.

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References

  1. https://www.faceblind.org/research/.

  2. Vandermeulen, R., Morissette, L., Chartier, S.: Modeling prosopagnosia using dynamic artificial neural networks. Neural Networks (IJCNN), The 2011 International Joint Conference on, pp. 2074, 2079 (2011)

    Google Scholar 

  3. https://en.wikipedia.org/wiki/Prosopagnosia#cite_note-cnn2407-3.

  4. http://www.google.co.in/imgres?imgurl= http://www.todayifoundout.com/wpcontent/uploads/2012/12/fusiformgyrus.

  5. https://commons.wikimedia.org/wiki/File:Prosopagnosia.jpg.

  6. G.R. Bradski. Real time face and object tracking as a component of a perceptual user interface. proceedings of the 4th IEEE workshop on applications of computer vision, (1998)

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  7. Viola, Paul A., Jones, Michael J. Rapid object detection using a boosted cascade of simple features. IEEE CVPR (2001)

    Google Scholar 

  8. http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=6995&objectType=file.

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Correspondence to N. Ramesh Babu .

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© 2018 Springer Nature Singapore Pte Ltd.

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Jhawar, G., Nagraj, P., Ramesh Babu, N. (2018). Developing Prototype for Prosopagnosia Using PCA. In: Urooj, S., Virmani, J. (eds) Sensors and Image Processing. Advances in Intelligent Systems and Computing, vol 651. Springer, Singapore. https://doi.org/10.1007/978-981-10-6614-6_6

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  • DOI: https://doi.org/10.1007/978-981-10-6614-6_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6613-9

  • Online ISBN: 978-981-10-6614-6

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