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IJSTR >> Volume 8 - Issue 10, October 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Modified Feature Trained Discriminative Classifier For Facial Expression Recognition

[Full Text]

 

AUTHOR(S)

Rakesh Sharma, Sukhjinder Kaur

 

KEYWORDS

Facial Expression Recognition, Local Phase Quantization, Local Direction Pattern, Support Vector Machine

 

ABSTRACT

Recognition of the human facial feature using technology is being emerged widely. In the recent times, many image processing techniques have been developed with the different approaches in order to recognize the expressions or human emotions from the image. This paper has presented a novel approach which used different components of the human face that includes pair of eyes, and mouth as the essential parameters to recognize the gesture or the expression of the face. The features are extracted using LDP (Local Direction Pattern) and LPQ (Local Phase Quantization) techniques of feature extraction. These techniques outweigh the techniques used in the traditional work (LBP and LTP). The complexity is reduced and Support vector machine is deployed for classification and recognition of the particular tasks. Simulation is performed using MATLAB and results demonstrated that the proposed system to recognize facial expressions has less complexity and more efficiency as compared to the traditional FER.

 

REFERENCES

TABLE 1
ACCURACY OF DIFFERENT METHODS OF FER SYSTEMS
Techniques Accuracy (%)
LBP 92.09
CLBP 90.53
LTP 94.11
PROPOSED 98.333
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