Comparing Frei-Chen & Sobel Edge Detector in Face Emotion Recognition with Euclidean Distance and LVQ Network

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Mehdi Akhari Oskuyee


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.


Keywords: Projection Profile, Particle Swarm Optimization (PSO), Euclidean Distance Measurement LVQ Network and Frei-Chen Edge


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