(untitled) (International Journal of Advanced Research in Computer Science, 2017)
In this paper, to increase the execution speed in face emotion recognition instead Sobel edge detector of Frei-Chen edge detector is used. The advantages Frei-Chen method are accurate and better detection, low overhead, detect corners beside with edges and less sensitive to noise than other edge detector. The Frei-Chen algorithm works on a part of image with size 3*3 similarly like the Sobel filter but instead of two masks of 4 masks are used. Of important characteristics this filter can be pointed to 4 masks of unique. For edge detection suitable masks are selected and selected mask is applied on image. This filter such as sobel filter can be used for multi-channel images. Furthermore we know Facial expression gives important information about emotion of a person. Face emotion recognition is one of important issues that widely attended in recent years. It can be used in areas of security, control, entertainment and machine vision. Nowadays for emotion recognition use of science image processing, speech signal processing, gesture signal processing and physiological signal processing. Use of image processing science than other methods can be very useful and helpful. Our proposal uses of an objective function for minimization of sum of Euclidean distance from the given points to the eye and lip curve that PSO algorithm will be used to optimize objective function. We recommend use of ellipse form as eye and lip in face emotion recognition. Face emotion recognition process like presented previous papers involves three stages pre-processing, feature extraction and classification. One of biggest problems in classification of emotions is overlap in range of values. To increase success rate in face emotion recognition we in this paper for another experience of neural networks use of LVQ neural network. We also show experiments face emotion recognition with Sobel filter and Frei-Chen filter. The results show that using Frei-Chen filter against Sobel filter reduces run time. Â Keywords: Projection Profile, Particle Swarm Optimization (PSO), Euclidean Distance Measurement LVQ Network and Frei-Chen Edge Detector.