Human Face Classification using Genetic Algorithm
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 9
Abstract
The paper presents a precise scheme for the development of a human face classification system based human emotion using the genetic algorithm (GA). The main focus is to detect the human face and its facial features and classify the human face based on emotion, but not the interest of face recognition. This research proposed to combine the genetic algorithm and neural network (GANN) for classification approach. There are two way for combining genetic algorithm and neural networks, such as supportive approach and collaborative approach. This research proposed the supportive approach to developing an emotion-based classification system. The proposed system received frontal face image of human as input pattern and detected face and its facial feature regions, such as, mouth (or lip), nose, and eyes. By the analysis of human face, it is seen that most of the emotional changes of the face occurs on eyes and lip. Therefore, two facial feature regions (such as lip and eyes) have been used for emotion-based classification. The GA has been used to optimize the facial features and finally the neural network has been used to classify facial features. To justify the effectiveness of the system, several images were tested. The achievement of this research is higher accuracy rate (about 96.42%) for human frontal face classification based on emotion.
Authors and Affiliations
Tania Setu, Md. Mijanur Rahman
Keywords
Related Articles
- EP ID EP90987
- DOI 10.14569/IJACSA.2016.070944
- Views 106
- Downloads 0
Instant Diacritics Restoration System for Sindhi Accent Prediction using N-Gram and Memory-Based Learning Approaches
The script of Sindhi Language is highly complex due to many complexities including abundance of homographic words. The interpretation of the text turns so tough due to the possibility of multitudinal meanings associated...
Finite Elements Modeling of Linear Motor for Automatic Sliding Door Application
In this paper, a linear switched reluctance motor is designed and investigated to be used as a sliding door drive system. A non linear two dimensions finite model is built to predict the performance of the designed motor...
Contemplation of Effective Security Measures in Access Management from Adoptability Perspective
With the extension in computer networks, there has been a drastic change in the disposition of network security. Security has always been a major concern of any organization as it involves mechanisms to ensure reliable a...
Double Diode Ideality Factor Determination using the Fixed-Point Method
In this paper, we are interested in the diode ideality factor study of the double exponential equivalent model, based on the properties of the fixed point method. The optimal choice of this factor will improve the photov...
Location Prediction in a Smart Environment
The context prediction and especially the location prediction is an important feature for improving the performance of smart systems. Predicting the next location or context of the user make the system proactive, so the...