Open AccessHISTOGRAM OF ORIENTED GRADIENT UNTUK DETEKSI EKSPRESI WAJAH MANUSIA
Author(s) -
Marlinda Vasty Overbeek
Publication year - 2018
Publication title -
high education of organization archive quality
Language(s) - English
Resource type - Journals
eISSN - 2620-7427
pISSN - 2337-5280
DOI - 10.52972/hoaq.vol10no2.p81-86
Subject(s) - artificial intelligence , histogram , pattern recognition (psychology) , computer science , convolutional neural network , adaptive histogram equalization , histogram matching , pixel , feature (linguistics) , artificial neural network , image (mathematics) , computer vision , histogram equalization , linguistics , philosophy
This research focuses on the detection of human facial expressions using the Histogram of Oriented Gradient algorithm. Whereas for the classification algorithm, Convolutional Neural Network is used. Image data used in the form of seven different expressions of humans with the extraction of 48x48 pixels. The use of Histogram of Oriented Gradient as a feature extracting algorithm, because Histogram of Oriented Gradient is good to be used in detecting moving objects. Whereas Convolutional Neural Network is used because it is an improvement of the Multi Layer Perceptron algorithm. Of the three epoches done, it produced the best accuracy of 77% re-introduction of human facial expressions. These results are quite convincing because it only uses three epochs.