Golden Ratio and Its Application to Bayes Classifier Based Face Sketch Gender Classification and Recognition
Khalid Ounachad · International Journal of Emerging Trends in Engineering Research · 2020
Machine learning is a subarea of artificial intelligence based on the idea that systems can learn from data and make decisions automatically.Bayes Theorem is widely used in machine learning.The main objective of this paper is to classify the gender of the human being based on their face sketch images by using a golden ratio features and Bayes Classifier.This paper presents a method for human face sketch gender classification and recognition.It is inspired in our other model which was pre-trained on the same task, but with sixteen features and fuzzy approach.Toward this end, just two features will be extract from the input face sketch image based on two face golden ratios.The detection stage passes by Viola and Jones algorithm.The classification task is evaluated through Bayes classifier.An experimental evaluation demonstrates the satisfactory performance of our approach on CUFS database with 80% for training, 20% for testing.The proposed machine learning algorithm will be a competitor of the proposed relative the stat of the art approaches.