Accurate Emotion Detection of Digital Images Using Bezier Curves

2015 
Image capturing and detecting the emotions of face that have unconstrained level of problems facing potential applications. There are many efficient approaches for smile detection that differentiates intensity between pixels with grayscale features for face images. The accuracy for picture with pixels will be significantly faster. Thus in our proposed approach we can detect emotions of human from the image with the help of software. First the image will be taken by skin color segmentation and that detects human skin color thus detects the face. Then it segregates eyes and lips from the face. Afterwards it makes Bezier curves for eyes and lips then it compare those images with that already stored on database for each emotion detecting curve possibilities of human face. Then it finds the nearest Bezier curve from database and provides the result as it is stored in Bezier curve emotion as this image's emotion possibility. Thus by using this method emotions expressed by the human face can be detected easily. Accurate result will be produced even for wide image ranges. There is no constraints block for poses given or illumination in the picture. The deformity of any type of emotion is detected at low computational cost.
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