FACIAL EXPRESSION IDENTIFICATION USING FOUR-BIT CO- OCCURRENCE MATRIXFEATURES AND K-NN CLASSIFIER

Bonagiri C S K Sunil Kumar, V Bala Shankar, Pullela S V V S R Kumar

Abstract: The present paper proposes a novel approach for facial expression identification based on the statistical features extracted from the 4-bit co-occurrence matrix. In the present, first color image is converted into grey level image using 7-bit quantization technique. To reduce the complexity of the Grey Level Co-occurrence matrix the present paper generates the co-occurrence matrix on 4 bit grey image which is generated by quantization technique. From The 4-bit CM extract 4 features; contrast, homogeneity, energy and correlation and generate the feature vector. By using the K-NN Classification technique classify the test image and extract the four statistical features and identify the type of expression of the test facial image. The present method got better comparative results when it is tested on Japanese Female Facial Expression (JAFFE) Database

Keywords: Facial Expression identification, Classification, k-NN classifier, Quantization, and GLCM

DOI: https://doi.org/10.15623/ijret.2015.0412017