Real-Time Face Recognition System Based On  Morphological Gradient Features and ANN

Real-Time Face Recognition System Based On Morphological Gradient Features and ANN

Dr. Pallab Kanti Podder

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Dilip Kumar Sarker

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Diponkar Kundu

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α to σ Pabna University of Science and Technology

Real-Time Face Recognition System Based On Morphological Gradient Features and ANN

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Abstract

Faces represent complex, multidimensional, meaningful visual stimuli. A real-time face recognition system has been implemented which is based on Artificial Neural Network. The system integrates three phases. At the initial phase, an image or a frame is grabbed from a real-time video source or webcam. Then the face region is detected using Local SMQT features and Split up SNoW Classifier and after that the detected face is sent for recognition using Backpropagation Neural Network. Feature extraction has been performed on Gray-Scale images of detected faces using Gray-Scale Morphology that are nonlinear and translationinvariant. The feature extraction and classification networks are trained together, allowing the network to simultaneously perform feature extraction and classification. This system performs extremely well under constrained conditions such as gross variation in expression, position, orientation and illumination which are the complications of face recognition.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Pallab Kanti Podder. 2012. \u201cReal-Time Face Recognition System Based On Morphological Gradient Features and ANN\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 12 (GJRE Volume 12 Issue F2): .

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GJRE Volume 12 Issue F2
Pg. 13- 17

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

Artificial Neural Network Backpropagation Face recognition Gray-Scale Morphology Real-Time SMQT Features SNoW Classifier

Submission ReceivedFebruary 5, 2012
Peer Review Double Blind
Handling Editor
Accepted March 5, 2012
Published March 15, 2012

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v1.2

Issue date

March 6, 2012

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Article Matrices

Total Score: 108

Country: Bangladesh

Subject: Global Journal of Research in Engineering - F: Electrical & Electronic

Authors: Dr. Pallab Kanti Podder , Dilip Kumar Sarker , Diponkar Kundu (PhD/Dr. count: 1)

View Count (all-time): 245

Total Views (Real + Logic): 5705

Total Downloads (simulated): 2798

Publish Date: 2012 03, Tue

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Total Views: 5705

Total Downloads: 2798

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