Author : Pa. Andal 1
Date of Publication :26th April 2018
Abstract: The Facial Expression Recognition system has many applications in the field of machine learning and computer vision. The canny edge detection algorithm has proved to be a very successful one in many image processing applications. It uses intensity gradients of an image for successful edge identification. For feature extraction in (FER) systems many methods are there for still images and videos. HOG (Histogram of Oriented Gradients) is the feature extraction method using image gradients that is applied in many FER systems. The first step of calculation in many FER systems is image pre-processing. This step is for removing noise and ensuring normalized color and gamma values. This step can be left out when we do feature extraction using HOG descriptor computation, as the HOG descriptor normalization produces the same result. Both the algorithms use image gradients for their computation. In our paper we shall provide a review of these two successful algorithms and analyze them for effective Facial expression recognition with less computational time and memory
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