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Research Article

Facial Expression Recognition using Hybrid Method of Local Binary Pattern and Gabor Filter Features with Random Forest Classifier

Priyanjali Kuruvila  ·  Rasna Sharma

IJDACR Vol.5 No.9 (April 2017) ISSN 2319-4863 Open Access Peer Reviewed

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.5 · Issue 9

Published

April 2017

Access

Open Access

Licence

CC BY-NC-SA 4.0

Authors

Priyanjali Kuruvila Rasna Sharma

Abstract

The face though seems an easy object to be recognized by retina but the artificial intelligence is not yet intelligent enough to do the task easily. As the source of a face is generally an image capturing object, there are lot of variations and complexions that persists with the image like (for example: noise, rotation etc.). There are many techniques that use some or other algorithm to find similarity in face model and the test image and most of them are successful on their part to attain better test similarities. However, considering the diverse scale of applications and mode of image sourcing, a single algorithm cannot get maximum efficiency everywhere. Even after using the best algorithm for a particular task, an application has to counter with challenges of face recognition. The main aim of this paper is to analyze the Hybrid method of Local Binary Pattern and Gabor Filter features and its performance when applied to facial expression recognition. This algorithm creates a subspace (face space) where the faces in a database are represented using a reduced number of features called feature vectors and Random Forest Classifier calculates the similarity score for performance evaluation which will provide improved results in terms of recognition accuracy.

How to Cite

Priyanjali Kuruvila, Rasna Sharma (2017). Facial Expression Recognition using Hybrid Method of Local Binary Pattern and Gabor Filter Features with Random Forest Classifier. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.5, Issue 9. ISSN: 2319-4863.

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Article Info

Journal IJDACR
Volume Vol. 5
Issue No. 9
Month April
Year 2017
ISSN 2319-4863
Access Open Access

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