Abstract
The identification of facial expressions, due to its important academic and commercial ability, is an important topic in artificial intelligence. If we concentrate on the health care, it is an important goal of every healthcare service to identify and handle emotions of patients. Emotional health is important issues for human life. Bad emotions like depression, sad have influences in human life. To improve human social life, we need to identify their emotional conditions. Facial expressions are the most important means of discovering emotions and behavioral analysis. This paper presents framework for extracting the features by means of CS-LOP with gradient and Gabor wavelet feature and GLCM is designed for each method of feature extraction. Feature maps are fused and classified for different emotions
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